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June 9, 2021

Gartner Data & Analytics Summit APAC: Day 2 Highlights

We are bringing you news and highlights from the Gartner Data & Analytics Summit, taking place this week virtually in APAC. Below is a collection of the key insights coming out of the conference. You can read highlights from Day 1 here.

On Day 2 from the conference, we are focusing on how to assess, optimize and articulate data and analytics value, digital ethics, and why small and wide data is important for the future of artificial intelligence (AI). Be sure to check this page throughout the day for updates.

How to Optimize Data and Analytics Value: The New Strategic Imperative

Presented by Rita Sallam, Distinguished VP Analyst, Gartner

Data and analytics is a business function that fuels digital acceleration. Yet, most organizations don’t have a systematic way to assess, optimize and articulate data and analytics value. In this session, Rita Sallam, Distinguished VP Analyst at Gartner, highlighted how CDOs, CIOs, and data and analytics leaders can optimize business impact and align to key business initiatives.

Key Takeaways

  • “We know from our chief data officer research and surveys that data and analytics leaders that are involved in strategy development are able to deliver far more business value than those who aren’t.”

  • “Data and analytics leaders struggle to optimize business value, and there’s often a lack of alignment to mission-critical priorities.”

  • “You as data and analytics leaders need to function as your organization’s ‘chief value officers.’”

  • “The ROAR (Risk, Opportunity, Appetite, and Return) Model gives you a systematic way to score both benefits and risks for each initiative and then think about the combination of those initiatives in terms of an optimal portfolio.”

  • “While we have models that can help you think through and prioritize, it’s what goes behind those models that’s important. Thinking trumps doing.”

  • “Optimizing value from data and analytics is a continuous process. It’s not just a once a year activity, it’s not just a quarterly activity — you need to think about it as central to everything else that you manage.”

Learn how to use data & analytics to re-engineer decision making in the free Gartner e-book “The Future of Decisions.”

Why Small and Wide Data Are the Future of AI

Presented by Jim Hare, Distinguished VP Analyst, Gartner

As organizations experience the limitations of big data as a critical enabler of analytics and artificial intelligence, new approaches known as 'small data' and 'wide data' are emerging. In this session, Jim Hare, Distinguished VP Analyst at Gartner, explained what small and wide data are and why they matter.

Key Takeaways

  • “Small data looks at analytical techniques that require less data,but offers useful insights.”

  • “Large data gives us the context. It allows organizations to use more of their data to enrich their existing data.”

  • “Both approaches reduce an organisation’s dependency on big data and enable a richer, more complete situational awareness or 360-degree view.”

  • “Small and wide data give D&A leaders more explainability than what they get from big data approaches. They make AI more resilient, focused and less data hungry.”

Read more in the Gartner press release here.

 

Digital Ethics: From “Why” to “How”

Presented by Frank Buytendijk, Distinguished VP Analyst, Gartner

Digital ethics is becoming a key topic of concern among executives worried about the unintended consequences of their use of data and technology, and in particular, artificial intelligence. In this session, Frank Buytendijk, Distinguished VP Analyst at Gartner, discussed how data and analytics leaders can operationalize principles and address the dilemmas that come with digital ethics. 

Key Takeaways

  • “What we’ve seen in the last two years is that the conversation has shifted from the ‘why’ to the ‘how.’ That is a great sign of progress, because it shows that we’re moving towards a more operational and more practical use of ethics.”

  • “The use of artificial intelligence, and the use of technology in general, should be human-centric and socially beneficial, fair, explainable and transparent, secure and safe, and accountable.”

  • “Ethics is not a topic that lends itself to exhaustive discussion; there are always more questions than there are answers.”

  • “Operationalize your principles by addressing their underlying dilemmas. If you look at AI that needs to be human-centric and socially beneficial, who gets to decide what is socially beneficial?”

  • “If you can create an advisory board with a lot of diversity, the chances that you can circle a dilemma from all kinds of perspectives and come up with perspectives that satisfy multiple needs are much higher.”

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