Agenda

Richard Y. Wang is Director of the Chief Data Officer and Information Quality (CDOIQ) Program. He is a pioneer and leader in the research and practice of Chief Data Officer (CDO). Dr. Wang has significant credentials across government, industry, and academia. He conceived and chaired the Inaugural MIT-Army CDO Forum, and established the CDO Forum as an annual event at MIT. In addition, he has been chairing the Annual CDOIQ Symposium since 2007. Dr. Wang was a professor at the MIT Sloan School of Management for almost a decade. From 2005-2009, he was appointed as a Visiting University Professor of Information Quality, University of Arkansas at Little Rock. He is an Honorary Professor at Xi’An Jiao Tong University, China. Dr. Wang has put the term Information Quality on the intellectual map with myriad publications. In 1996, Prof. Wang organized the premier International Conference on Information Quality, which he has served as the general conference chair and currently serves as Chairman of the Board. Dr. Wang’s books on information quality include Journey to Data Quality (MIT Press, 2006), Information Quality: Advances in Management Information Systems (M.E. Sharpe, 2005), Introduction to Information Quality (MITIQ Publications, 2005), Data Quality (Kluwer Academic, 2001), and Quality Information and Knowledge (Prentice Hall, 1999). Prof. Wang has been instrumental in the establishment of the Ph.D. and Master of Science in Information Quality degree program at the University of Arkansas at Little Rock, the Stuart Madnick IQ Best Paper Award for the International Conference on Information Quality, the comprehensive IQ Ph.D. dissertations website, and the Donald Ballou & Harry Pazer IQ Ph.D. Dissertation Award. Dr. Wang is the recipient of the 2005 DAMA International Achievement Award. Previous recipients of this award include Codd for inventing the Relational Data model and Chen for the Entity Relationship model. In 2005, he received a certificate of appreciation from the Director of Central Intelligence and a thank you letter from the Director of National Intelligence. From 2009-2011, Dr. Wang served as the Deputy CDO and Chief Data Quality Officer of the U.S. Army, for which he received letters of appreciation from the Army’s Chief Information Officer, and the CIO at the Office of the Secretary of Defense. He received a Ph.D. in Information Technology from the MIT Sloan School of Management in 1985.

Professor Ong holds a B.A. in Mathematics (1984, Triple First), a Postgraduate Diploma in Computer Science (1985, Distinction) from Trinity College, University of Cambridge; and a PhD in Computer Science (1988) from Imperial College, University of London. He joined NTU as a Distinguished University Professor in August 2022, and will take up the appointment of Vice President (Research) in January 2023. Prior to joining NTU, he was Lecturer then Professor of Computer Science at the University of Oxford (1994-2022); Fellow of Merton College, Oxford (1994-2022); Honorary Professor of Computer Science, Bristol University (since 2022); Shaw Visiting Professor at National University of Singapore; and Prize Research Fellow, Trinity College, Cambridge (1988-1994). Professor Ong’s research is broad, ranging across semantics of computation, programming languages, verification, logic and algorithms, and algorithmic game theory. A notable feature of his work is the combination of ideas and methods from semantics and structures, with techniques from automated verification. Professor Ong is one of the leading figures and inventors of game semantics and its applications. His solution (with Hyland) to the PCF Full Abstraction Problem opened up the field of game semantics; and their constructions, known as Hyland-Ong games, have become standard notions in the semantics of programming languages. Professor Ong is also known for his pioneering contribution in the field of verification: his LICS 2006 paper co-initiated higher-order model checking, a new branch of algorithmic verification that combines ideas and methods from semantics with automata-theoretic and allied techniques in automatic verification, with applications to the verification of higher-order programs. His current research interests include computer and cyber security, higher-order logic and satisfiability modulo theories, and probabilistic and differentiable programming. Throughout his long stay in Oxford, Professor Ong has supervised well over 60 doctoral students and postdocs. His contributions to the advancement of computer science have been recognised with leadership positions in major scientific conferences and bodies. Professor Ong was General Chair (2013-2015) of the ACM / IEEE Logic in Computer Science (LiCS), and Founding Vice Chair (2014-2019) of the ACM Special Interest Group in Logic and Computation. He was founding Steering Committee Chair (2015- 2018), Formal Structures for Computation and Deduction. He has served as programme chair and on the steering committees of leading scientific meetings, including ACM / IEEE LiCS, European Association of Theoretical Computer Science, European Association of Computer Science Logic, and European Joint Conferences on Theory and Practice of Software. Professor Ong has given numerous keynote presentations and invited lectures, including well over 100 at international research meetings. Professor Ong has received several international and national accolades. He is the joint winner of the ACM / EATCS / EACSL / KGS Alonzo Church Award 2017 for Outstanding Contributions to Logic and Computation. He is also a recipient of the President of the Republic of Singapore Scholarship in 1981, Prime Minister’s Book Prize in 1980, Overseas Merit Scholarship from 1981 to 1984.

Wai Fong Boh is President’s Chair and Professor of Information Systems at Nanyang Technological University (NTU) in Singapore. She is currently the Deputy Dean of Nanyang Business School (NBS), Director of Information Management Research Centre at NBS, and she serves as co-Director for both Singapore Agri-Food Innovation Lab (SAIL @ NTU) and NTU Centre in Computational Technologies for Finance (CCTF). She received her PhD from the Tepper School of Business at the Carnegie Mellon University. She conducts research in the areas of knowledge and innovation management and entrepreneurship. She has published many articles in top management journals including Management Science, MIS Quarterly, Academy of Management Journal, Organization Science, Journal of Management Information Systems, and Research Policy. She has also won multiple awards, including awards for best papers in journals, conferences, and as a best IS professor in Asia. Professor Boh is a seasoned and versatile instructor who teaches at both undergraduate and graduate levels. She has spoken in multiple industry conferences, and specializes in research and conducting training for entrepreneurs, managers and employees in areas related to innovation and entrepreneurship. Professor Boh is also sought after by private organizations as well as government agencies to conduct training programs. She is often cited and interviewed in the media.

As Assistant Chief Executive (Data Innovation and Protection Group), Zee Kin oversees IMDA’s AI and Data Industry development strategy with the key responsibility in developing forward-thinking governance on AI and data in Singapore. He also spearheaded the development of Singapore’s Model AI Governance Framework, which won the UNITU WSIS Prize in 2019. He is currently a member of the OECD Network of Experts on AI (ONE AI), and was a member of the AI Group of Experts at the OECD (AIGO) which developed the OECD Principles on AI. In his capacity as Deputy Commissioner of PDPC, Zee Kin oversees the development, administration and enforcement of the Personal Data Protection Act (2012). His key responsibilities include managing the formulation and implementation of policies relating to the protection of personal data, as well as the issuing of enforcement directions for organisational actions. As a well-regarded expert on data privacy issues, he has spearheaded various public and sector-specific activities to raise awareness and compliance in data protection, and is currently participating as an expert in the Global Partnership on AI (GPAI)’s Data Governance Working Group, which addresses data protection issues at the intersection of AI development and deployment.

Companies across industries are investing in AI to drive logistics, improve customer service, increase efficiency, empower employees and so much more. But while AI continues to attract board level attention and investment, the AI maturity is still evolving. Accenture research of approximately 500 companies in Asia Pacific revealed that only 17% of firms have advanced their AI maturity enough to achieve superior growth and business transformation. While there’s clearly a science to AI, the findings demonstrate that there is an art to AI maturity. AI achievers are not defined by the sophistication of any one capability, but by their ability to combine strengths across strategy, processes and people. In this keynote we look at what AI Achievers are doing to master their craft.

Joon-Seong Lee leads Accenture Applied Intelligence (Data, Analytics & AI) for South East Asia region and is responsible for a large and diverse team of data scientists, data engineers and AI strategists who are helping companies achieve better performance using big data, machine learning & artificial intelligence. With more than 20 years of consulting experience with local and regional clients across industries, he has partnered with some of the leading companies in the region in developing Data and AI strategies, building big data & analytics platforms and applying data science/machine learning/AI innovations to achieve tangible business outcomes. Joon-Seong is also the Vice President of the Singapore Computer Society AI & Robotics Chapter and received his Executive MBA from INSEAD.

Using, storing, and sharing private data is a necessary part of doing business for modern organizations even while that data remains both highly targeted by attackers, as well as highly governed by regulators. For years, organizations have tried to meet the regulatory and security demands of private data with some successes and some failures. In this presentation we will explore the modern demands on private information from pro-active data security, post-breach incident response, and industry regulatory requirements to the more recent consumer privacy requirements, all while highlighting public failure case studies and the questions they should have been asking themselves to close their findings and inherent security gaps. Learning objectives will include: • The relationships between data security and the regulations for privacy and industry. • How and why organizations treat data security vastly different than any other security pillar. • Where machine learning, data analytics and cloud infrastructure impact security outcomes? • What technical answers speak to a level of risk of non-compliance or breach?

Terry Ray is SVP of Data Security GTM and Field CTO, he’s also an Imperva Fellow for Imperva Inc. Uniquely, organizations today have very strict regulations, steep fines, complex environments and highly valued data that attracts bad behavior. Terry applies his decades of security experience to these organizations and their cyber security challenges. As a technology SVP & Fellow, Terry supports all of Imperva’s business functions with his more than 2 decades of security industry experience and expertise. Previously he served as Imperva’s Chief Technology Officer where he was responsible for developing and articulating the company’s technical vision and strategy, as well as, maintaining a deep knowledge of the Application and Data Security Solution and Threats Landscape. Earlier in his tenure at Imperva, he held the role of Chief Product Strategist where he consulted directly with Imperva’s strategic global customers on industry best practices, threat landscape, application and data security implementation and industry regulations. He continues to operate as an executive sponsor to strategic customers who benefit from having a bridge between both company’s executive teams. He was the first U.S.-based employee, and during his 18 years at Imperva, he has worked hundreds of data security projects to meet the security requirements of customers and regulators from every industry. Terry is a frequent speaker for RSA, FS-ISAC, Gartner, ISSA, OWASP, ISACA, IANS, CDM, NLIT, The American Petroleum Institute and other professional security and audit organizations in the Americas and abroad. Terry also provides expert commentary to the media and has been quoted in Security Week, SC Magazine, Forbes, CBS News, the BBC and others.

Data, Analytics & AI (including GenAI), as part of a strong digital core, have become a primary source of competitive advantage. The value of data as capital and driver of growth is a core tenant for any corporate strategy. Realizing the tremendous value of data is not a pipedream, it is hear and now but requires a change in how data and AI are being used & organised across your entire organization. Unlike traditional data and analytics initiatives that lived in a technical silo, Data-led Transformation is about connecting data, people, ideas and outcomes at pace.

Amit brings 29+ years of experience in data and analytics with the last 12 years focused on Artificial Intelligence (AI), he is passionate about leading & growing business and challenging organisations to drive change. His experience has helped many clients pivot their business with new & emerging data, analytics & AI technologies across industries such as Banking, Mining and Industrials. As a thought leader and innovator he has been a keynote speaker at a number of events on Artificial Intelligence, Cloud & Analytics in the APAC region. He has also been featured in a number of AI publications and mainstream media in Australia. In his current role as AI execution and Data-led Transformation lead, he helps companies across Asia Pacific realize value from their investments in data, analytics and AI to create new business revenue generating models, drive efficiency and cost to totally.

In this fireside chat, Shanmuga Sunthar Muniandy, APAC Data Architect/Evangelist at Denodo, sits down with Ann Tey, Deputy Director of the Data Services Team at Nanyang Technical University, to discuss the role of the logical data platform in their journey to become a data-driven organization and implement data architecture and governance to support key business metrics and improve self-service and data intelligence across the university faculties.

Shanmuga Sunthar (Shan) is the APAC Director of Data Architecture at Denodo. A Technologist with a career spanning over 20 years, mostly in Data Management and Analytics, Shan has garnered extensive experience in the areas of Digital Transformation, Enterprise Data Management, Enterprise Architecture, Business Advisory, Advanced Analytics Solutions, Analytics Lifecycle Management, Cloud Architecture, Innovation Centers, Enterprise Customer Intelligence Management, Enterprise Fraud Management and Enterprise Risk Management (to name a few). Shan’s passion towards understanding customers’ business challenges and evangelizing state-of-art technologies, personalized solutions, and innovative architecture approaches around these needs has resulted in successful implementations of enterprise solutions for his customers and growth for those organizations. Shan is also an active speaker in the regional technology and thought leadership forums. He is also a visiting adjunct at a number of Universities and Institutes of Higher Learning in the region.

Ann started her career as a DBA and extended her passion in the area of Data, AI Governance, and Cloud Data infrastructure. A results-oriented leader with over 26 years of Data Management experience in managing daily database operations in the education and, public and private banking sectors. She is currently leading a Data Services Team at a research-intensive public university, Nanyang Technological University, Singapore.

Data Spaces are gaining traction, as environments that facilitate inter- and exchange of data between various parties on a common topic. These intercompany exchange platforms are coming into focus for large-scale collaboration on data along supply chains as mandated by new legislation in the field of ESG – Environmental, Social, Governance. Regulation requires companies to report on those aspects to a wider degree and requires them to know more about their partners and environments they are doing business in. Aside from those regulatory requirements, this greater insight will open opportunities to actually become better “global citizens” – if the right insights are derived from the well-prepared, curated and quality controlled data. We’ll explain how these regulations and technical concepts came into being, what drives them, and what opportunities arise from their proper use.

Marcus Hartmann is a partner at PwC Germany and Chief Data Officer for PwC Germany and Europe. As a proven data expert, he has spent his entire career in the data & analytics industry, helping companies to move more easily and quickly into a data-rich world and to develop and implement new data-driven business models. He joined PwC in August 2019 and quickly established the Chief Data Office and a corresponding internal digital & delivery unit. He leads a team of data, software and digital experts to establish and grow the foundations for efficient and scalable data use within the firm, and also the realization of highly-scalable, market oriented data products, and new digital business models. Previously, he was Chief Data Officer for the entire Group at ProSiebenSat.1 Media SE and Chairman of the Executive Board of ProSiebenSat.1 Digital Data GmbH. In this role, he was responsible for all strategic and company-wide data and AI initiatives. He has also worked for Bisnode AB, one of the leading providers of digital business information, analytical services and smart data analytics, based in Stockholm. Here he most recently served as Group Vice President. In this position, he was in charge of the group-wide functions Business Intelligence, Advanced Analytics and Big Data Analytics. He also held various management positions at the global information services provider Experian, arvato infoscore and Bertelsmann Financial Services.

At Siam Commercial Bank, we set the vision to become a Digital Bank with Human Touch by 2025. Driving towards that ambition is a host of Data- and AI-led initiatives. We will discuss how we use machine learning to help realize our vision of effortless, ever-present and empathetic digital banking. We will describe how we are building a seamless omnichannel experience to our customers. This talk will describe our journey in data monetization, our successes, hiccups, and lessons learned.

Dr. Asavathiratham joined SCB in April 2020 as SEVP, Chief Data Officer. He currently holds the position of SEVP, Chief Digital Banking Officer at the company. Dr. Asavathiratham has extensive working experience at leading local and foreign companies. Prior to joining SCB, he was Chief Research Officer at WorldQuant, in charge of researching teams and data scientists in 14 countries worldwide. He also served as Portfolio Manager at Merrill Lynch, New York, and at Sun Trading in Chicago, responsible for quantitative trading. He was a Management Consultant at McKinsey & Company in Bangkok and London and an Analytics Engineer at Pivotal Systems Corporation. Dr. Asavathiratham was awarded a King’s Scholarship for his undergraduate, graduate, and doctorate degrees, all in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT).

Irrespective of where you are in your data journey, it remains challenging for organisations to have clear view on driving their modern data strategy. Understanding the capabilities and role data lake, data warehouse and data mesh as well as emerging term like “lakehouse” will enable data and analytics leader to establish their data vision and execution paths. This session is focussed on: – What are data lakes, data warehouse and data mesh ? – Why are they important on the role they play ? – How can they be used to meet the modern data and analytics needs?

Karthik Murugan has more than 20 years of experience as an IT professional and has worked with a number of senior roles across different sectors. Karthik shares the passion for innovation in data and analytics fields. As part of World-Wide Specialist Organisation at AWS, Karthik leads AWS Analytics Services with focus on uplifting business value for Public Sector customers in Asia Pacific and Japan region. Bringing experience and learnings from multiple industry sectors, Karthik has worked on several large digital transformation initiatives driven by data. He is focussed on enabling organisations to unlock the value of data using AWS service and partner solutions.

Singapore has made significant investment in developing a digital foundation for our healthcare system. This digital foundation played a key role in our fight against COVID and in launching our new population health strategic initiative (“Healthier SG”). Colin Lim, Chief Information Officer and Chief Data Officer, Singapore Ministry of Health (MOH) will share MOH’s experience in enabling Digital Health through the use of data. He will also discuss the challenges ahead (e.g. privacy, cybersecurity) as we look to increase digital adoption.

Colin is the Chief Information Officer and Chief Data Officer of the Singapore Ministry of Health. He is also Group Director, InfoComm, Technology and Data Group. Prior to MOH, he was the founder and CEO of mobilityX, a start-up that received funding from SMRT and Toyota Tsusho. His previous experience includes the private (IBM UK and SMRT) and public (Singapore Administrative Service – Ministries of Home Affairs, Manpower and Transport as well as the Land Transport Authority) sectors. He graduated from the London School of Economics and Oxford University.

Artificial Intelligence (AI) is the most powerful business discipline of our generation. The ability for AI to drive effective and responsible decisions is uber highly dependent upon high-quality, accurate, complete, unbiased data sets. Data management focus on manufacturing high-quality, accurate, complete, unbiased data sets is instrumental to the economic growth in the 21st century. Thusly, Data Management is the most important Business Discipline of the 21st century. The ability for AI to drive effective and responsible decisions is highly dependent upon high-quality, accurate, and complete data sets. The ramifications from poor-quality or incomplete data on the AI model’s effectiveness and fairness can have disastrous, unintended consequences in areas ranging from employment, criminal justice, and healthcare. As data becomes the ubiquitous source of economic value creation, organizations need an end-to-end data-driven value creation process that speaks to and aligns the business executives and the data and analytics teams around the business mandate to unleash the business (or economic) value of the organization’s vast data reserves. The analytics challenge is generating actionable insight (the data-to-insight process) and embedding (insight-to- action) that insight so that it can be used at scale. Successful organizations recognize that analytic models are essential corporate assets that produce and deliver answers to production systems for improved customer relationships, improved operations, increased revenues, and reduced risks. So of course, they seek to create the best models possible. Increasingly, this responsibility is falling to the Chief Data Officer (CDO). In many respects, it makes sense; although AI is driven in part by technology, data is the fuel for AI. With the remit of delivering good quality data pipelines and sound data governance, the CDO is essential in ensuring that AI projects are not short-circuited by avoidable data management issues. Can CDOs use their stewardship of AI and Analytics projects as an opportunity to cement a more valuable role within the C-suite? Where are the opportunities for CDOs to make their mark in driving AI success? As the stewards of data quality and data governance, CDOs will have more impact than any other individual on driving the success or failure of AI projects in the years to come. As more organizations seek to leverage the power of artificial intelligence for creating new efficiencies and sustainable competitive advantages, CDOs should spearhead these transformational programs. Here are some questions the CDO will try to answer: What is needed to launch an AI project? Can AI outcomes be trusted? What are the main ways in which AI can fail? How can those failures be avoided? What new tools and techniques can help business leaders turbocharge and operationalize their data and AI programmes? In this presentation, I will share some best practices, learned from successful ML projects at industry-leading clients, that can help CDOs how they think about AI and data, democratizing data and AI, the data-to-insight-to-action loop, and see stronger results.

Michael Taylor is the AI Chief Data Scientist for Siemens Mobility Rail Analytics Center in Singapore with a mission to democratize Data Science, reliable AI, and deeply committed to designing innovative solutions to solve customer’s business problems. Michael is a Fellow at the Royal statistical society, Member of the Operations Research Society, and a Guest Lecturer in Big data for Business analytics at Bocconi University in Milan since 2019.

Future growth areas like Software Defined Vehicles, Autonomous Driving, and Autonomous Mobile Robots are all fueled by large amounts of data. While we at Continental, as a leading automotive technology provider, have been managing data for some time, new and more integrated technologies are shifting the way data is used and managed in the organization. Using innovative R&D projects in Singapore, we demonstrate how this evolution of data management will help accelerate the development of our future products and services.

He heads the Software & Central Technologies in Singapore where research and innovations activities in the area of Autonomous Driving, Artificial Intelligence, Robotics, Cyber Security are carried out. Vincent leads the strategisation, proposition and execution of technological projects relevant to the eco-system of the Singapore and the region. Prior to his current role, Vincent leads the application and platform development group for Business Unit Instrumentation & Driver HMI Singapore. In this role, Vincent is responsible for the R&D activities of Singapore and Malaysia to serve global automotive customers. As chairman of the Technology and Transformation Function Committee and a EXCO Council member of the Singapore Manufacturing Federation, Vincent proactively drives initiatives to support the Singapore manufacturing sector. In-addition, Vincent is a member of the Institute of Technical Education (ITE) Electronics & Info-Comm Technology Academic Advisory Committee. With over 20 years in the automotive industry, Vincent drives collaboration partnership with public agencies, academia, corporate companies, SMEs and startups

It is estimated that 2.5 quintillion bytes of data (equivalent to 1,000 petabytes) is produced each day globally. Data is a non-rivalrous resource, and its transformative potential means that real value can be generated when data is used and shared across the data value chain in a responsible and accountable manner. In Singapore, the Personal Data Protection Act (2012) (PDPA) was amended in 2020 to strengthen consumer trust through organisational accountability, and enhance data use for innovative purposes. Reliance on the exceptions under the PDPA allow organisations to use data to perform research, streamline business operations, as well as perform other legitimate uses. The Singapore government is also working to build trust internationally by encouraging global convergence through the alignment of common standards and systems to facilitate cross-border transfers of data, and the promotion of contract-based mechanisms and certifications. For example, global or regional organisations based in Singapore can apply to certify themselves under the APEC Cross Border Privacy Rules (CBPR) and/or the Privacy Recognition for Processors (PRP) Systems certifications, to demonstrate accountability in the transfer of data across borders. Local organisations can also apply to certify themselves with the Data Protection Trustmark (DPTM) to demonstrate accountable data protection practices. With an increase in the use of advanced analytics, data science, and AI, policymakers around the world are looking at innovative ways to tackle the new frontier of fostering growth of data ecosystems, while continuing to emphasize the collection, use and sharing of personal data in a responsible and accountable manner. To this end, we have published various frameworks such as the AI Model Governance Framework, and several technical guides to help organisations with the adoption of emerging technologies. In addition, we have also put in place industry programmes such as the Privacy Enhancing Technologies (PET) Sandbox to facilitate the engagement with industry players who wish to experiment with solutions such as PETs. Undeniably, with increased digitalisation across various sectors, data breaches and identity theft are also becoming more commonplace. This can erode consumer trust and confidence in the way organisations collect, use and share data. As such, organisations will need to have in place a robust data strategy that will not only support their strategic objectives and decision-making, but also preserve the trust that consumers have in their data management and protection practices. In this respect, the Personal Data Protection Commission (PDPC) and Infocomm Media Development Authority (IMDA) hope to be able to continue to develop progressive policies and programmes, which will evolve to meet the needs of both organisations and individuals and enable the value of data to be maximised in a trusted ecosystem.

Ms Adeline Tung is Director, Policy and Technology, in the Data Innovation & Protection Group, Infocomm Media Development Authority (IMDA) and the Personal Data Protection Commission (PDPC). She oversees and drives the formulation of data policies to enable the use of data in a responsible and trusted manner. Adeline has spent majority of her career in the public sector, with experience in various economic and industry development, as well as planning and policy roles. With the Singapore Economic Development Board (EDB), she was involved in formulating and implementing industry strategies and plans, and was also part of the EDB’s Global Operations, based in Europe. She has also done a policy stint with the Ministry of Communications and Information (MCI), and most recently, leads the strategic and corporate planning team at the Agency for Science, Technology and Research (A*STAR) under the Ministry of Trade and Industry (MTI). With her current role, Adeline is interested in emerging data technologies, and to advance how the field of data is contributing to and shaping our Digital Future. Adeline graduated with a Bachelor of Science in Engineering from the University of Michigan, Ann Arbor, and a Master of Science in Mechanical Engineering from Stanford University.

At Kenvue, we combine the power of science with meaningful human insights and digital-first thinking to help people live healthier lives every day, from their first day through our iconic products that people know and love. This does not stop at product innovation and research and development. We adopt a data-driven, analytical approach from sales, marketing, to supply chain so that we can reach more people and deliver more value to them. In this talk, two case studies will be shared on how we adopt a data-first approach in the consumer health industry.

Dr. Wang Deliang is a seasoned technology and data leader. He is currently the Head of Data Science for APAC at Kenvue, part of Johnson & Johnson Family of Companies. He has extensive experience in designing and implementing end-to-end digital and data transformation for organizations. At Kenvue, Dr Wang serves as a strategic thinker and analytics expert to partner with business leaders to solve challenging problems through data science and AI solutions. He also helps formulate data strategy for the company to achieve data-driven business decision making.

When you’re shopping online, you’ve already shared most of your personal information, such as your name, email address, phone number, and address. According to the Thoughtworks Looking Glass report 2023, brands can compete more effectively by taking a “privacy-first” stance. Making sure that your company values privacy as much as its clients, can help you stay ahead of this trend. In today’s data-driven world, organizations must treat data privacy with the utmost respect. In order to build digital trust with their customers, one must ensure the privacy of personal information. It is difficult to protect data privacy yet gain insights from data. In order to become data-driven, organizations must strike a balance between protecting privacy and utilizing data. In this situation, PETs (Privacy Enhancing Technologies) could play a significant role. Personal data can be protected while still being used for specific purposes by organizations using privacy enhancing technologies (PETs). By enabling businesses to incorporate privacy into their services, products, and business processes from the beginning, they enable a data privacy first design. PETs are emphasized as one of the key technological enablers of digital trust in SGTech’s study on the state of digital trust. In this session, we’ll dig deep into data privacy issues, including how they differ from data security concerns and how PETs offer a novel method for safeguarding data privacy on a large scale within our organizations.

Sowmya leads the Data and AI service line for Thoughtworks SEA. In her current role, she works towards the vision of enabling businesses to become data-driven. She has more than 13 years of experience in the industry, which started with building low-latency trading systems, architecting and building modern data platforms to driving data strategy at scale. Her recent publication is around data strategy for trusted public sector sharing in Singapore. Sowmya is a member of the SGTech Digital trust committee that focuses on establishing Singapore as a global node for digital trust. She leads the Privacy Enhancing Tech workgroup as part of the committee, focusing on building awareness, capability and thought-leadership in this space in Singapore and the region. Sowmya has a Masters in Software Engineering and has always remained a technologist at heart. She is passionate to leverage data and tech for social good.

Although Universities maybe leading research in the areas of data engineering, cloud technologies, ML and AI, they are the late comers when it comes to establishing a role of CDAO and implementing data and analytics strategy. And yet, Universities are complex institutions with ambitious and very important roles in our society that cannot be fully realised without data and digital transformation. With diverse infrastructure and systems and the need to make effective decisions about their students, life-long learners, alumni, staff, researchers, industry partners etc, their dependency on data literacy, good quality data and analytics models that support every part of the University, including learning analytics, research analytics, marketing analytics, people analytics and others is very high. • What is the relationships between data strategy and culture? • How do you ensure support of executive stakeholders? • CIO and CDAO – How do you build great relationships with CIO? • Where data governance fits in? • Priorities – who defines them? • How do you build capability to support data and analytics initiatives? • How do you measure success?

Nonna is Chief Data & Analytics Officer at RMIT University and is helping RMIT to improve the lives of students, staff and community through trusted insights. Through the development and implementation of Data & Analytics Strategy, Nonna is establishing data-driven culture and foundations for better decision-making to support learning, teaching and research and deliver innovative outcomes using data, ML and AI capabilities. With wide range of industry experience in consulting, telecommunications, finance and IT, Nonna is an award winning Data and Analytics Champion. She is a thought leader in data quality and use of analytics to improve customer service and productivity of Australian businesses. Nonna partners with business stakeholders and IT to drive data strategy, develop enterprise Data Governance and deliver large, complex data and analytics related initiatives, significantly improving business bottom line. Nonna has been recognised by IAPA in the top 10 Analytics Leaders in Australia in 2021 and by Corinium in the top 100 Data and Analytics Innovators in the world in 2020. Nonna is a frequent presenter at Australian and International conferences and podcasts.

Learn how integrated data insights can help organisations to enhance, scale and optimise the human experience. Explore practical approaches for implementing zero-click intelligence, enabling collaborative analytics, and embracing data storytelling across the enterprise. In this session, KW will share how Pfizer successfully scaled rapid, personalised insights for senior leadership, analysts and field reps across the organisation.

As Head of Sales Engineering, KW Chung leads a team of Sales Engineers’ across Asia Pacific who develop and execute enterprise intelligence applications for MicroStrategy customers—transforming the way they do business. KW provides executive leadership for development and training of sales engineering personnel, ensuring the execution of technical and professional excellence. KW is a frequent speaker at MicroStrategy and partner events, as well as seminars in the region.

The Chief Data Officer (CDO) role has become increasingly important in organizations worldwide. CDO is a senior executive responsible for managing an organization’s data assets and related important issues, including data quality, data security, data governance, data analytics, and data privacy. It is important in the era of digital economy for CDO to increase the value of data elements and enhance data governance. It is a difficult task to promote and implement a solid CDO system in organizations as well. This talk will introduce CDO research and practice in China, starting with the first company in the country, Alibaba, to establish CDO system in 2012 and the first research center on data quality and CDO in the management school of Xi’an Jiaotong University (XJTU) collaborating with MIT in 2012. The current status of the marketization of data elements and Big Data Trading Exchange market in China, as well as challenges and possible development in the future will be presented.

Wei Huang (Wayne) is a Distinguished National Yangtze Chair Professor and founding dean of the college of business, The Southern University of Science & Technology (SusTech), Shenzhen, and a honorary professor of Xi’an Jiaotong University (XJTU), Xi’an, China. Other current/past academic appointments include the director of Digital Economy Research Center of NCAMS, SusTech, a Visiting Fellow of Harvard University, Tenured Full-Professor/Faculty of Ohio University (USA)/University of New South Wales (Australia), Dean of Management School of XJTU. He has had more than 30 years’ full-time teaching and research experiences in top-tier research universities of USA, Australia, Hong Kong, Singapore and China. His research publications include more than 200 peer-reviewed research papers in international academic outlets such as in MIS Quarterly (MISQ) , Journal of MIS (JMIS), Journal of AIS, IEEE Transactions, DSS, Communications of ACM , OMEGA, EJOR, ACM Transactions, European Journal of Information Systems (EJIS). His research has been cited by top international academic journals including Management Science (MS), Operations Research (OR), MISQ, Information Systems Research (ISR). He received Sandra Slaughter Service Award in 2018 by AIS (Association of Information Systems, the prestigious academic association of IS in the world), and was elected as an AIS-Fellow in 2020.

Data is an integral part of all good decision making. Connecting data and insight with decision makers is important, but so is having a strong data culture throughout the whole organisation. Being enabled by data and insight is contingent on a data culture that has a defined data strategy aligned with organisation outcomes, ensuring data and insight is fully integrated in all decision making. There are a number of key ingredients for this, including all participants’ involvement. In this talk Kate Kolich will share her inclusive approach to data leadership, in her role as Assistant Governor/ General Manager of Information, Data, and Analytics at The Reserve Bank of New Zealand (RBNZ). This talk will provide a high level overview of how the RBNZ as custodian of financial and economic data, uses and produces data and insight to enable decision making. Kate will outline how having a data strategy which embraces the needs of data practitioners, consumers and decision makers leads to data innovation and data driven decision making.

Kate is Assistant Governor/General Manager Information, Data, and Analytics at Reserve Bank of New Zealand – Te Pūtea Matua. Kate has had an extensive career in digital, data and technology leadership roles across the public and private sectors. Her experience includes almost 20 years in banking at the Bank of New Zealand where she held a number of data leadership roles including Head of Enterprise Data and Information Services. In her time at BNZ, Kate led many strategic data initiatives and teams across the bank. Prior to joining the RBNZ, Kate led the Evidence, Insights and Innovation team at EECA (Energy Efficiency and Conservation Authority). Prior to that, she was the Director of Data Systems and Analytics at the Social Wellbeing Agency. Kate is a recognised thought leader on digital and data innovation, and is active in promoting women in STEM through her volunteer work as a Global Women in Data Science Ambassador.

As a CEO of health services, my focus is to create differentiated and rich customer experience through health services that are affordable, simple, and predictable with the support of business partners, technology, innovation and importantly, data that is our strategic and competitive asset and is our lifeblood. The digital transformation in healthcare is accelerating the use of Data and analytics by bringing relevant intelligent insights that changes the way how healthcare practitioners optimize their services for their patients and develop new solutions that can help resolve their ailments. The ultimate goal for Cigna is the wellbeing of its patients by being proactive – a good patient care experience at an optimal cost. Technology coupled with Data and analytics in healthcare can help streamline different types of patient data, innovate forward-thinking treatments, reduce costs, and, most importantly, save lives. It is the way forward. Achieving measurable business value out of data is a two-way street. The data and analytics function should partner with the business leaders closely to determine the analytics use cases that would create sustainable value. But equally important is the commitment of the business to operationalize the analytical solutions developed and the business should make sure that they have a clear strategy to implement the tangible actions using the developed solution to extract the value. In this presentation, I will discuss how at Cigna Singapore, we achieve this. We then present a case study on how analytics is providing proactive value add service to our customers through an effective care management program.

Raymond Ng is the CEO and Country Manager of Cigna Healthcare Singapore and Australia. Prior to becoming CEO, Ray held leadership roles across the business, in areas including distribution, sales and business development in his decade long tenure with Cigna. This allowed him to gain exposure and insights to the organisation which has helped him understand the enterprise strategy better and how it could be executed locally. Raymond has over 21 years of experience in the insurance industry and has previously worked for Prudential Assurance, Chartis, and AIA. Raymond has wide experiences and expertise in green field operations, and has a successful track record in building market share. He holds a Bachelor of Commerce (Finance and Marketing) from Curtin University of Technology Western Australia.

Neha Gupta is Cigna Healthcare’s Head of Data and Analytics, APAC, furthering the company’s vision to increase access to quality healthcare for everyone. Neha has 18+ years of experience in insurance industry building and implementing innovative analytical solutions. Neha is a Fellow member of the Institute of Actuaries of India and a Fellow member of the Institute and Faculty of Actuaries, UK and holds a first-class degree in Mathematics from University of Delhi.

Nikhil Dwarakanath is a seasoned Technology professional with ~15 years of experience, in the Product, Customer & Technology domain. He joined Grab in 2017 to help build the Data function for the organization. In his current role, he leads the Data & Analytics function at Grab, as well as the Product charter for Data Platforms. At Grab, he has also been instrumental in institutionalizing a culture of experimentation and data led product development firm-wide, and continues to champion the cause. Nikhil is also a member of the Grab Data Governance Council and helps drive compliance and governance, both internally and with regulatory agencies in Southeast Asia. Before Grab, he was an early member at Snapdeal, a horizontal e-commerce company, and helped build their entire Data Science practice. While at Snapdeal, he also led the roadmap for Growth, Product Analytics, Search & Ads. In this role, he co-owned revenue outcomes, and managed DAU & repeat rates. Outside of work, Nikhil is passionate about supporting and mentoring early stage entrepreneurs. He currently advises and supports several direct to consumer, AI and Web3 startups. He is currently also volunteering his time on the Advisory Board at Nanyang Polytechnic, Singapore, trying to shape the academic curriculum in Singapore and on the APAC Board of PMF.

Eric Yau, Chief Operating Officer at Precisely explores the goals of today’s data-driven organizations, the challenges imposed by external macro forces, and the imperative for data integrity to enable innovation and drive business success. Eric will share key insights from the latest global survey, 2023 Data Integrity Trends and Insights, to discuss the state of the industry based on the opinions of over 400 data professionals worldwide.

Eric Yau is the Chief Operating Officer at Precisely. In this role, he is responsible for Precisely’s full software and data portfolio as well as company transformation and integration initiatives. Eric’s teams include Product Management, Engineering, Cloud Services, Pre-sales and Professional Service, Customer Support and Integration Management & Transformation. Eric brings more than 25 years of senior leadership experience, most recently serving as EVP, Software at RMS where he transformed the company from a catastrophe modeling business into the industry-leading insurance risk data and analytics platform. Before RMS, Eric was SVP of Solutions at BMC Software with responsibility for the full $2.2B portfolio of mainframe and distributed software segments, as well as cloud operations and support. Prior to BMC, Eric was IBM’s VP, Business Intelligence & Performance Management. Eric earned degrees in Mathematics, Computer Science, and Computer Engineering from the University of Waterloo.

Like many other knowledge work professions, the augmentation of AI into clinical work is inevitable as clinical work requires assessing, processing, and synthesizing large volumes of information. Many clinical tasks are highly equivocal and complex; hence, healthcare workers should benefit from the augmentation of capabilities through the application of AI. In many hospitals, the use of AI in healthcare work is ad-hoc and opportunistic; hence, a more systematic, hospital-wide approach is called for. In this talk, we will discuss how to develop a lens to view clinical work opportunities for AI augmentation.

Kim Huat Goh is an Associate Professor of IT and Operations Management at Nanyang Business School, Nanyang Technological University. He is a Senior Editor for the Journal of the Association for Information Systems, and Academic Director for the Nanyang MBA program. He received his Ph.D. in business administration specializing in information systems from the Carlson School of Management, University of Minnesota, Twin Cities. His research interests include using analytics and behavioral economic theories to model consumer behavior in technology-mediated environments and examining the value of IT and analytics in the healthcare and financial services industry. He has published numerous articles in top Nature Index and Financial Times top-ranked management journals such as Nature Communications, MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of Consumer Psychology, and Human Resource Management Journal. He has worked with various organizations such as the Federal Deposit Insurance Corporation (United States), Khoo Teck Puat Hospital, Ng Teng Fong General Hospital, Tan Tock Seng Hospital, Rockwell Automation, Telenor (Norway), and Singapore Exchange in executive training, research and business analytics related projects. Since 2018, he has been the Principle Investigator for various competitive grants with a total amount exceeding S$3.5 million.

In recent years, AI models have been applied to different application domains to generate real-world impact. However, with increasing size and complexity of AI models, AI needs to rely on big training data and has generated significant carbon footprint. This talk will introduce some of the challenges of current AI models and present potential new technologies (including computation-efficient AI and data-efficient AI) that can be developed to make AI models green, to reduce its environmental impacts and make AI models more sustainable.

Xiaoli is currently a department head (Machine Intellection department, consisting of 130+ AI and data scientists, which is Singapore’s largest AI and data science group) and a principal scientist at the Institute for Infocomm Research, A*STAR, Singapore. He also holds adjunct professor position at Nanyang Technological University (He was holding adjunct position at National University of Singapore for 6 years). He is also serving as KPMG-I2R joint lab co-director. He has been a member of ITSC (Information Technology Standards Committee) from ESG Singapore and Infocomm Media Development Authority (IMDA) since 2020. In adidtion, he serves as MOH (Ministry of Health) health innovation expert panel, as well as AI advisor for Smart Nation and Digital Government Office (SNDGO), Prime Minister’s Office.

Data Quality issues and Data Privacy are common challenges faced by Data leaders, Data users and Data consumers. The issues often lurk behind the scenes until discovered or exposed. How do we manage the data quality issues and privacy proactively?

Ram Kumar is the Chief Data and Analytics Officer of Cigna’s International Markets where he is responsible for driving data and analytics strategy and its execution for 30+ countries covering The Americas, EMEA, and Asia Pacific. Prior to Cigna, Ram was the CEO of Quantium India where he was responsible for the overall management and operations of the organization that serves as a Centre of Excellence for Data Science and AI consulting, Data Product development, Technology Operations and Innovation, serving the Quantium Group, a global Australian company, that is No.1 in Data Science. Ram commenced his career in Australia and has over 30 years of solid background in Information Technology coupled with over 22 years’ experience in data strategy and execution. He has held many executive roles in his career including as Group CTO, CIO of Asia and as Group Head of Data and Privacy for Insurance Australia Group and as Chief Data and Analytics Officer of QBE Insurance. He implemented his first data governance and monetization program in 1992. He has a strong basic and applied R&D background in AI and Machine learning and was actively involved in this field between 1986 and 2005, and has worked closely with some of the pioneers in this field. His first big data based advanced analytics project was in 1992. Ram has served as a member of the Data Research Advisory Board of MIT Sloan School from 2016-2019. He spent over 16 years building open data standards under OASIS, a Global Standards Body and his standards have been implemented globally and notably by Google Maps. Ram has published over 150 articles and is a regularly invited keynote speaker in conferences globally and has spoken extensively. Ram is recipient of several IT and Data related awards globally. His work has been published as chapters in books as global best practices. Ram holds a Master’s degree in Computer Science and Engineering and a Bachelor’s degree in Electronics and Communications Engineering with Artificial Intelligence as the major in both.

Dr Geraldine Wong is Chief Data Officer at GXS Bank, one of the two successful applicants of Singapore’s Digital Full Bank License. At GXS, Dr Wong is responsible for driving the bank’s data strategy with the goal of leveraging ecosystem data assets, promoting data-driven financial inclusion and reimagining the way customers engage and experience the digital economy. Her career spans both within industry and academia, where she has led teams in developing and executing Artificial Intelligence (AI) initiatives across the public, transport and infocommunications sectors. Dr Wong was named in the SG100 Women in Tech list by Infocomm Media Development Authority (IMDA) (2021) in recognition of her contributions to the technology industry in Singapore. For her achievements in data analytics, she was most recently named one of the global top 100 Innovators in Data and Analytics by Business of Data. Dr Wong is an alumnus of the NUS Faculty of Science where she obtained her Bachelor of Science (Major in Statistics and Minor in Mathematics). She received her PhD in Statistics and a Bachelor of Mathematical Sciences (First Class) from the University of Adelaide in Australia, where her research focused on climate change and the prediction of global extreme climate events. She is also currently an Adjunct Associate Professor at the NUS Department of Statistics and Data Science, an active mentor for Girls in Tech and Singapore Deep Tech Alliance, and an Executive Committee member of the Free and Open source software group at the Singapore Computer Society.

Tony Wan is currently serving as the chief data officer for PwC China, responsible for PwC China’s data-related strategic work in China, including data governance, data security and compliance, and data application research in multiple fields. His area of expertise includes computing strategy consulting, data strategy consulting, etc. He also has extensive practical experience in the secure and reliable deployment and use of cloud computing services for cloud service users. Along with the CDO, Mr.Wan is also a partner in PwC Shanghai’s Risk and Control Services Department, specializing in information system auditing and risk control, information security system certification, security governance and compliance, data security and privacy protection. He has assisted various enterprises in industries such as banking, automobile, high-tech, Internet in mitigating business and network security risks, and established sustainable security capabilities.

Vincent Koc is a seasoned, results-driven technology leader with extensive expertise in data-driven disciplines. As the Head of Data at publicly listed company hipages Group (ASX:HPG), he leads the data department and develops the company’s data strategy. He also holds a fellowship at the Institute of Managers and Leaders Australia, where he serves as a mentor and thought leader for the next generation of data professionals. With over a decade of experience in various industries, including finance, telecommunications, travel, and consumer goods, Vincent has a proven track record of delivering data-driven projects for major organizations such as Qantas, Telstra, Volkswagen, Expedia, the Australian Federal Government, and the NSW Government. He has held key positions at major Australian organizations. Vincent is also a guest lecturer and volunteer mentor at universities in Australia and the United States, sharing his knowledge and shaping the next generation of data professionals. In 2020, he was recognized as one of the Top 25 Analytics Leaders by the IAPA Institute of Analytics Professionals of Australia and was a finalist in the AC&E 30Below Young Marketeer of the Year in 2017. He also holds multiple awards for his data-driven projects, including the Content Marketing Association’s (CMA) awards, and Content Marketing Institute’s awards for effective campaigns in the field of data. Vincent is passionate about data and empowering the next generation of data practitioners, and is a regular speaker at international and Australian conferences.

The new wave of generative AI systems, such as ChatGPT, have the potential to transform entire industries. To be an industry leader in five years, companies need a clear and compelling generative AI strategy today. 1) In fact, ChatGPT is just one of the generative AI applications based on foundation models, building upon prior advances in AI, machine learning and deep learning. The rise of foundation models is fueled by three primary factors: new algorithm advances for pre-training, exponential increase in computational power, and availability of high-quality training data. 2) The value of generative models has already been deployed at scale for early use cases. For example, generative AI enables drug discovery, GitHub CoPilot automates coding, CarMax replaces time-consuming manual summarization processes and so on. Adoption maturity intrinsically depends on error tolerance and creative requirements of the task which broadly segment use cases into 4 key categories including creative, high error tolerance use cases in the near term; repetitive, lower error tolerance use cases in the near to medium-term; explorative, high error tolerance use cases in the medium term; and operational, no error tolerance in the long term. From our study, Generative AI is expected to achieve ~30% share of the overall AI market by 2025, reaching ~60B TAM. 3) The companies that have scaled AI across the business and achieved meaningful value from their investments—typically dedicate 10% of their AI investment to algorithms, 20% to technologies, and 70% to embedding AI into business & people transformation. In other words, to companies who want to win, capability building and change management should be given twice as much as attention as algorithms and tech. 4) ChatGPT will change many things, but it won’t change everything. Business leaders can’t ignore the fact that, when the hype is stripped away, Generative AI systems are just technology. And, like any technology, what ultimately matters most is not just whether businesses use it, but how its use will affect business models and how it can change businesses’ relationships with customers. Those who stay focused on the fundamentals will reap the biggest rewards from adopting Generative AI. 5) As emerging categories of artificial intelligence, such a generative AI, play a more central role in business and society, so does the need for ensuring responsible use. Responsible AI should not be viewed strictly as a defensive manoeuvre—but also as a source of value.

Mr. Jeff Walters is a Managing Director and Senior Partner of Boston Consulting Group. He joined BCG in 2003 and has been in Asia for almost 20 years, primarily helping companies grow in China. He leads the Technology and Digital Advantage practice in Asia Pacific and BCG X (Tech Build & Design Unit) in Greater China. Jeff has advised a wide range of primarily consumerfacing, spanning multiple categories including FMCG, telco, luxury, durables and fashion. Across these industries, he has supported clients in their growth aspirations through topics such as sales, CRM, personalization e-commerce and omni-channel and route-to-market. He supports companies to build AI capabilities and bring these advanced techniques to make better decisions and drive business impact. Jeff is the author of 15 publications over the past decade, including recent partnerships with Alibaba, leveraging their data and exploring omni-channel behaviors more deeply. Jeff was a Ph.D. candidate in Electrical Engineering at Stanford University, where he also received an M.A., and holds a B.A. in Physics from Dartmouth College.

As the diversity of data and the opportunities for its use grow, it is increasingly difficult to describe the foundations of information quality and the responsibilities of the Chief Data Officer (CDO). There is simply so much variety to deal with. In the face of this difficulty, I suggest that CDOs can benefit from viewing many of the foundations of information quality as problems of organization, running from the micro level (involving the organization of data representations and infrastructure) to the macro level (involving the organization of institutions and ecosystems). I will ask whether there are common principles of organization that can span these levels and whether the organizational sciences can give us insights into these principles. I will use examples from healthcare to illustrate my points.

Andrew is a Professor of Business Information Systems at UQ Business School. Andrew graduated from UQ’s Commerce program in 1998 and worked for several years in IT risk management for one of the Big-4 accounting/consulting firms. He then moved to Georgia State University in Atlanta, USA, to complete his Ph.D., followed by seven years at the University of British Columbia in Vancouver, Canada, where he became a tenured Associate Professor. He returned to UQ in May 2012. Andrew has taught information systems in undergraduate, graduate, and executive programs, in several counties. He has extensive experience in teaching IT governance and control, IT development, and digital health. He undertakes research in three areas. His first area focuses on how effectively organisations use IT. For example, he has been studying the effective use of electronic health records in health authorities. His second research area focused on improving methods to analyse and design IT systems. For example, he has examined ways to improve the specification of user requirements. His third research stream focuses on improving theories and methods used by researchers in the Information Systems discipline. He has published in and served on the editorial boards of many journals in the Information Systems field. He has also served on the councils of the Association for Information Systems and the Academy of Management (OCIS/CTO Division). He is a Fellow of the Association of Information Systems and Fellow of the Academy of Social Sciences of Australia. He is currently Editor-in-Chief of MIS Quarterly.

As our world continues to rapidly evolve and become increasingly complex, the need for data to enable adaptation and growth has become more important than ever before. While many have compared data to oil as a valuable resource, the truth is that data is much more than just a commodity to be extracted and traded. Rather, it is a powerful growth enabler that has the ability to create entirely new business models, products, and services. In this conference session, attendees will have the opportunity to explore the key technology drivers that are shaping the world of data, as well as gain insights into how data can transform their specific industry or business. Through a series of engaging presentations and interactive discussions, participants will learn about the latest trends and best practices in data strategy, including how to develop and implement effective data projects, and how to foster a culture of ethical, data-driven decision-making. By attending this session, you will gain a deeper understanding of the critical role that data plays in shaping the future of business, as well as the skills and knowledge necessary to leverage this powerful resource to drive growth, innovation, and competitive advantage. Whether you are a business leader looking to stay ahead of the curve, or a data professional seeking to enhance your skills and expertise, this session is the perfect opportunity to gain valuable insights and connect with like-minded individuals who share your passion for data-driven innovation.

As Chief Data Officer Dr. Meri Rosich leads talented data teams in generating value from data. For the past 25 years, she has built high-performing global teams for great organizations such as Bertelsmann, Amex, Samsung, Docomo, Visa, and Standard Chartered; and lived internationally based in New York, London, Barcelona where is is originally from; Hong Kong, Tokyo, and for the past 15 years in Singapore. As a lifelong learner, she recognizes the importance of personal development and values the joy of growth. Meri holds an MBA from the London Business School with a special graduation award, a PhD Summa cum Laude in Tech Strategy from the University of Barcelona, and a Doctor Europeus Honorific Mention. Inspired by great professors, she continues to learn by teaching, as an Adjunct Professor of Data Strategy and Sustainability at Globis University, a renowned MBA in Japan. She has balanced a corporate and entrepreneurship career and founded four start-ups. Some worked, and others were great learning experiences. She enjoys supporting inclusive leadership and data literacy initiatives and mentoring women to lift the next generation of tech leaders. Over the years, she served on the advisory board of the Data Literacy Project; as the United Nations Development Program Fintech mentor, Ambassador for the UN Women STEM program and board member of the United Nations Association of Singapore. Co-founded the Female Founders think-tank, the Women Data Leaders network and is currently serving as a committee member of SG Women in Tech, and the Singapore Computer Society Business Analytics Chapter. Some recognitions include 30 People Who Are Changing The World by London Business Review, Top 100 CDO, 100 Women in Tech, Most Promising Female Developer, Top voice and Moebius Digital Award among others.

Historically, data and its privileges (e.g., access, ownership, knowledge) have been in the hands of a chosen few, creating tribal knowledge. This has blocked data and analytics from being integrated and leveraged throughout all corners of the organization to reach its full value potential. To enable data-driven innovation, firms need to democratize their data so that more employees without “data” in their title, or “regular people,” are able to work with data in order to contribute to business value creation from their own functional position or domain. This presentation summarizes research insights on data democratization initiatives at born-digital firms (e.g., AirBnB, Uber) and compares them to approaches taken by incumbents. We derive a framework composed of five pillars for managers to focus their efforts on when constructing a data democracy: (1) Broaden data access by rolling-out data catalogs, (2) Stimulate the generation of data-driven insights through self-service, (3) Level up data literacy with specific curricula for personas or role families, (4) Promote data through various corporate communication channels, and (5) Advance data practices by creating communities.

Christine Legner is a Professor of Information Systems at the Faculty of Business and Economics (HEC), University of Lausanne in Switzerland. Her research fields are data strategy and data management, enterprise architecture and strategic IT planning. She is the co-founder and academic director of the Competence Centers Corporate Data Quality (CC CDQ), an industry-funded research consortium and expert community with 20 Fortune 500 companies (including BASF, Bayer, Beiersdorf, Bosch, Nestlé, Schaeffler, SAP, Siemens and Tetrapak). In the CC CDQ, she and her research team collaborate with industry experts to develop concepts, tools and methods that advance data management. Together with Dr. Olivier Verscheure, she is co-director of the Executive Certificate in Data Science and Management (CAS), a joint program offered by University of Lausanne and EPFL. Professor Legner has published more than 150 peer-reviewed articles in academic journals and conference proceedings. She is also editor of a book on Strategic Enterprise Architecture Management and has co-authored eBooks on data strategy and data catalogs. She received a post-doctoral qualification (Habilitation) and doctorate from the University of St. Gallen (Switzerland) and has been visiting researcher at INSEAD, Stanford University and HEC Montreal.

Modern AI has been deployed to create value in many diverse aspects of businesses, from assisting in the creation of Intellectual Property (IP) to monitoring ESG. In the healthcare and medical fields, AI has also been utilised for the mass screening of diseases such as tuberculosis in less developed countries. What are the boundaries for the use of AI in creating value? This session will explore some of these boundaries including expounding the use of AI to create value without infringing on copyright, trade mark and patent laws. It will also explore the UK government’s March 2023 White paper A pro-innovation approach to AI regulation, as well as the Institute of Directors’ AI in the Boardroom released in late March 2023, and other recent developments in the EU on civil liability rules of AI and regulation of Artificial Intelligence.

Hannah Yee-Fen LIM is an Associate Professor of Business Law at NTU. She is uniquely qualified with double degrees in Law and Computer Science from the University of Sydney. She is an internationally recognised legal expert on all areas of technology law, including IP, data protection, AI, Blockchain, Fintech, Cryptoassets, NFTs, health technology, cybersecurity and ethics. She is an appointed legal expert by international bodies, including the WHO and UNCITRAL advising on areas including AI and Fintech. Hannah is one of 15 international legal experts appointed by UNIDROIT on its Digital Assets Project Working Group. She is also serving, by invitation, as a legal expert on the Law Commission of England and Wales Expert Advisory Panel on its Digital Assets Project concerning Cryptoassets and NFTs. She is the author of six scholarly books published by publishers such as Oxford University Press, including pioneering books on Cyberspace Law in 2002 and AVs and the Law in 2018. She has authored hundreds of papers and her research has been cited with approval by the High Court of Australia and the Singapore Court of Appeal. She is currently PI or co-PI in grants on data and AI totalling more than S$57 million.

In line with FWD’s vision of changing the way people feel about insurance, we are focused on making the insurance journey simpler, faster and smoother for customers. Our AI+ Smart Insurance was launched in 2021, and is an extensive two-year roadmap to transform FWD into a digital organisation, leveraging AI to innovate and transform the insurance journey for our customers, partners and employees. From modernising our enterprise data architecture to using MLOps, we have built innovative in-house AI models and products, to support our distribution partners, marketing and customer care teams in providing personalised recommendations and improving the customer journey experience.

Yuhui Yao, PhD on Machine Learning, has 18 years Big Data Analytics experience in FWD, PingAn, UOB, IBM and Cisco. He is strong on both technique with 10+ data mining research papers published and business acumen which always deliver more than business asked. He has lead more than hundred data mining projects that have generated hundred millions of incremental revenue. The excellent results have won big recognitions such as National Center for Database Marketing Gold Award, IBM AP Best Practice and was voted the most useful, and Best Practice from the perspective of Cisco’s ISO-9001 Quality Program. To have big business impact, he believes business value is target, data mining is tool and platform is critical to scale. Currently he is leading the big data strategy and analytics for FWD group based in Singapore. He likes to share his knowledge and was often invited as a speaker from many conference such SAS Forum, Global Data Mining Conference, and China Finance Industry Big Data Conference.

Generative AI is a subset of machine learning that involves generating new data based on existing data. AI is becoming increasingly important in creating value for various industries, including improving efficiency, reducing costs, and providing new insights and opportunities. Innovative generative AI techniques are driving advanced value creation across industries. In this section Sachin will share the latest developments and applications of innovative generative AI for advanced value creation. He will also share how generative AI works and some of key applications of generative AI in business. He will also highlight techniques for innovative generative AI.

Sachin Tonk is currently Deputy Chief Data Officer leads talented data and analytics teams in GovTech. Govtech has a vision empowering Singapore nation with possibilities through infocomm technology and related engineering technology playing a vital role in materialising Singapore’s Smart Nation vision. For the past 17 years, he has established global data and analytics teams for global organisations to enable business growth and achieve organizational KPIs. He is a Diverse professional exposure in international settings across India, Singapore, United Kingdom and the Middle East. He has an Outstanding track record in automation, artificial intelligence, data analytics, business intelligence, Innovation, business transformation, governance, and architecture. Sachin holds an MBA degree from National University Singapore and Anderson school of management. He has successfully launched his podcast “Making Data Speak” where latest data and AI related topics are discussed by industry leaders, and he has won several data and analytics awards including “Indian Achievers Award”

This presentation discusses the ethical challenges in AI automation and algorithms, contextualized against the Fourth Industrial Revolution. We start with a call back to the transition between the First and Second Industrial Revolutions in 1894 and discuss the recent emergence of Generative AI algorithms such as Latent Diffusion Models and Generative Pre-Trained Transformers in the mainstream. We conclude with a challenge to Data and AI Engineers to be at the forefront of ethical algorithms and leads on how to address Data Ethics.

Data analyst, researcher, software developer, entrepreneur and technologist. Advocate for data literacy, data ethics and social impact from data. His current work focuses on human rights, public health, food security, political risk and fighting disinformation and infodemics through the use of computational social science, social listening, remote sensing, artificial intelligence and data engineering. Dominic founded CirroLytix, a social impact AI company and co-founded Data Ethics PH, an online community focused on social issues such as data privacy, data security, AI-driven discrimination, data liabilities, data ownership rights, and data poverty. Doc also co-founded the Analytics Association of the Philippines (AAP) and is a Board of Trustees member of the Philippine Center for Investigative Journalism (PCIJ). Doc’s teams are back-to-back global winners in the NASA International Space Apps Challenge for data-driven dengue surveillance and COVID-19 global pandemic response monitoring and also the Global Winner of the Technology Award in the European Space Agency EO Dashboard Hackathon for mobility and air quality.

While businesses and society test new ideas to realize the benefits and value of Analytics, Machine Learning, and AI, what are the key data governance principles, frameworks and best practices that should be in place? How do we ensure that we stay within ethical bounds when developing AI and Machine Learning algorithms?

Wai Fong Boh is President’s Chair and Professor of Information Systems at Nanyang Technological University (NTU) in Singapore. She is currently the Deputy Dean of Nanyang Business School (NBS), Director of Information Management Research Centre at NBS, and she serves as co-Director for both Singapore Agri-Food Innovation Lab (SAIL @ NTU) and NTU Centre in Computational Technologies for Finance (CCTF). She received her PhD from the Tepper School of Business at the Carnegie Mellon University. She conducts research in the areas of knowledge and innovation management and entrepreneurship. She has published many articles in top management journals including Management Science, MIS Quarterly, Academy of Management Journal, Organization Science, Journal of Management Information Systems, and Research Policy. She has also won multiple awards, including awards for best papers in journals, conferences, and as a best IS professor in Asia. Professor Boh is a seasoned and versatile instructor who teaches at both undergraduate and graduate levels. She has spoken in multiple industry conferences, and specializes in research and conducting training for entrepreneurs, managers and employees in areas related to innovation and entrepreneurship. Professor Boh is also sought after by private organizations as well as government agencies to conduct training programs. She is often cited and interviewed in the media.

Alvin Ong is the Chief Information Officer (CIO) of Nanyang Technological University (NTU), working closely with the NTU senior management team to deliver University-wide digital initiatives to enhance teaching and learning, enabling cutting-edge research, and modernising NTU’s administrative capabilities and IT Infrastructure. Prior to joining NTU, Alvin was the group CIO for Alexandra Health System and has more than 20 years of experience in the public healthcare sector. Alvin is currently serving in the boards and committees of National Kidney Foundation Singapore, HCA Hospice Limited, Ang Mo Kio-Thye Hua Kwan Hospital, NTUC Tech Talent Assembly and Singapore Computer Society (SCS) CITPM Board of Assessors, as well as being a fellow with SCS. Alvin holds a Bachelor of Mechanical Engineering (Honors) from the National University of Singapore and a MBA from the University of Surrey, United Kingdom. He is a certified Chief Information Security Officer (CISO), CITPM(Senior) and COMIT(Senior).

Bhavna Rawlley is a Business Analytics professional with over 18 years experience in Risk/Marketing Analytics and Data Strategy Development. She has led data strategy and transformation initiatives for companies across India, North America, South Africa and Southeast Asia. For the past 2+ years, she has been closely associated with the Veritas consortium led by the Monetary Authority of Singapore, helping to define Banks’ Responsible AI methodology and the roadmap for its adoption. In addition, as Centre for Data & Insights & Sustainability Data Lead for Accenture Southeast Asia, she helps companies action data and insights innovatively to deliver business results and achieve net zero goals

As Head of Data Strategy Group, Taran brings with him over 15 years of experience in Data and Financial Services across APAC, Middle East and Europe from Bloomberg LP. He joins GIC in 2021 and drives GIC enterprise data management to develop a more robust way of governing and leveraging data for business needs. Prior to joining GIC, Taran was Head of Asia Pacific Sales & Business for Bloomberg LP in Hong Kong, where he owned the strategy for all of Bloomberg’s Enterprise Technologies under the Financial Products umbrella.

Richard Y. Wang is Director of the Chief Data Officer and Information Quality (CDOIQ) Program. He is a pioneer and leader in the research and practice of Chief Data Officer (CDO). Dr. Wang has significant credentials across government, industry, and academia. He conceived and chaired the Inaugural MIT-Army CDO Forum, and established the CDO Forum as an annual event at MIT. In addition, he has been chairing the Annual CDOIQ Symposium since 2007. Dr. Wang was a professor at the MIT Sloan School of Management for almost a decade. From 2005-2009, he was appointed as a Visiting University Professor of Information Quality, University of Arkansas at Little Rock. He is an Honorary Professor at Xi’An Jiao Tong University, China. Dr. Wang has put the term Information Quality on the intellectual map with myriad publications. In 1996, Prof. Wang organized the premier International Conference on Information Quality, which he has served as the general conference chair and currently serves as Chairman of the Board. Dr. Wang’s books on information quality include Journey to Data Quality (MIT Press, 2006), Information Quality: Advances in Management Information Systems (M.E. Sharpe, 2005), Introduction to Information Quality (MITIQ Publications, 2005), Data Quality (Kluwer Academic, 2001), and Quality Information and Knowledge (Prentice Hall, 1999). Prof. Wang has been instrumental in the establishment of the Ph.D. and Master of Science in Information Quality degree program at the University of Arkansas at Little Rock, the Stuart Madnick IQ Best Paper Award for the International Conference on Information Quality, the comprehensive IQ Ph.D. dissertations website, and the Donald Ballou & Harry Pazer IQ Ph.D. Dissertation Award. Dr. Wang is the recipient of the 2005 DAMA International Achievement Award. Previous recipients of this award include Codd for inventing the Relational Data model and Chen for the Entity Relationship model. In 2005, he received a certificate of appreciation from the Director of Central Intelligence and a thank you letter from the Director of National Intelligence. From 2009-2011, Dr. Wang served as the Deputy CDO and Chief Data Quality Officer of the U.S. Army, for which he received letters of appreciation from the Army’s Chief Information Officer, and the CIO at the Office of the Secretary of Defense. He received a Ph.D. in Information Technology from the MIT Sloan School of Management in 1985.

Wai Fong Boh is President’s Chair and Professor of Information Systems at Nanyang Technological University (NTU) in Singapore. She is currently the Deputy Dean of Nanyang Business School (NBS), Director of Information Management Research Centre at NBS, and she serves as co-Director for both Singapore Agri-Food Innovation Lab (SAIL @ NTU) and NTU Centre in Computational Technologies for Finance (CCTF). She received her PhD from the Tepper School of Business at the Carnegie Mellon University. She conducts research in the areas of knowledge and innovation management and entrepreneurship. She has published many articles in top management journals including Management Science, MIS Quarterly, Academy of Management Journal, Organization Science, Journal of Management Information Systems, and Research Policy. She has also won multiple awards, including awards for best papers in journals, conferences, and as a best IS professor in Asia. Professor Boh is a seasoned and versatile instructor who teaches at both undergraduate and graduate levels. She has spoken in multiple industry conferences, and specializes in research and conducting training for entrepreneurs, managers and employees in areas related to innovation and entrepreneurship. Professor Boh is also sought after by private organizations as well as government agencies to conduct training programs. She is often cited and interviewed in the media.

Ram Kumar is the Chief Data and Analytics Officer of Cigna’s International Markets where he is responsible for driving data and analytics strategy and its execution for 30+ countries covering The Americas, EMEA, and Asia Pacific. Prior to Cigna, Ram was the CEO of Quantium India where he was responsible for the overall management and operations of the organization that serves as a Centre of Excellence for Data Science and AI consulting, Data Product development, Technology Operations and Innovation, serving the Quantium Group, a global Australian company, that is No.1 in Data Science. Ram commenced his career in Australia and has over 30 years of solid background in Information Technology coupled with over 22 years’ experience in data strategy and execution. He has held many executive roles in his career including as Group CTO, CIO of Asia and as Group Head of Data and Privacy for Insurance Australia Group and as Chief Data and Analytics Officer of QBE Insurance. He implemented his first data governance and monetization program in 1992. He has a strong basic and applied R&D background in AI and Machine learning and was actively involved in this field between 1986 and 2005, and has worked closely with some of the pioneers in this field. His first big data based advanced analytics project was in 1992. Ram has served as a member of the Data Research Advisory Board of MIT Sloan School from 2016-2019. He spent over 16 years building open data standards under OASIS, a Global Standards Body and his standards have been implemented globally and notably by Google Maps. Ram has published over 150 articles and is a regularly invited keynote speaker in conferences globally and has spoken extensively. Ram is recipient of several IT and Data related awards globally. His work has been published as chapters in books as global best practices. Ram holds a Master’s degree in Computer Science and Engineering and a Bachelor’s degree in Electronics and Communications Engineering with Artificial Intelligence as the major in both.