“As D&A professionals we should always be asking ourselves not just whether we are collecting, integrating and storing our data in the best way possible, but more fundamentally, whether we have the right data.”

“Having the right varieties of data is more important than volume.”

D&A leaders can ensure they have the right data by doing four things: 1) stop collecting data just in case; 2) consider substituting big data for small data, 3) swap real data for synthetic data, and 4) ensure your active metadata tells you not only what data you have, but also what it means.

“The most valuable data will be the data we create, not the data we collect.” 

Gartner estimates that by 2030, the majority of the data used to build models will be synthetic data.

“Data alone is unlikely to drive decisions. Design better decisions by improving the timing of decisions, accelerating decisions and connecting decisions.”

Learn more from the Gartner Opening Keynote in the associated Gartner press release.

“The world is becoming consumerized and highly contextualized, so must analytics and business intelligence (BI).”

“A Gartner survey found that 44% of respondents said that automated insights is the capability they require when selecting a new analytics and BI platform.”

Gartner estimates that by 2025, data stories will be the most widespread way of consuming analytics, and 75% of stories will be automatically generated using augmented analytics techniques.

Automation adoption in analytics and BI is growing, with 36% of survey respondents currently using automated augmented analytics for information workers. Another 40% plan to do so in the next 12 months.

Scaling analytics adoption through automation consists of six steps: Align to business value, then pilot and validate; update roles and invest in data literacy; scale analytics across the enterprise; mitigate expert resistance; invest in explainability of insights and models; assess vendors.

“Start with small data to demonstrate value and build trust. Invest in ongoing data literacy and user enablement, as this will be a significant factor for success.”

Trend #1: Adaptive AI Systems - As decisions become more connected, more contextual and more continuous, D&A leaders increasingly need to reengineer decision-making. Use adaptive AI systems that can offer faster and flexible decisions by adapting more quickly to changes.

Trend #2: Data-Centric AI - Without the right data, building AI is risky and possibly dangerous. Formalizing data-centric AI as part of your data management strategy will ensure AI-specific data considerations, such as data bias, labeling and drift, are addressed. 

Trend #3: Context-Enriched Analysis - It helps identify and create further context based on similarities, constraints, paths and communities. By 2025, context-driven analytics and AI models will replace 60% of existing models built on traditional data.

Trend #4: Skills and Literacy Shortfall - Through 2025, the majority of CDOs will have failed to foster the necessary data literacy within the workforce to achieve their stated strategic data-driven business goals.Organizations must  foster broader data literacy and digital learning, rather than simply delivering core platforms, datasets and tools.

Trend #5: Connected Governance  - Connected governance provides a means to connect disparate governance efforts, including D&A governance, across different organizations, both physical and virtual, as well as geographies.