Gartner identifies three data and analytics trends for 2022

Data and analytics leaders should embrace these three key factors when leveraging top data and analytics trends this year according to Gartner.

The three trends are: activate dynamism and diversity, augment people and decisions, and institutionalise trust.

The findings can be found in the Gartner report, Top Trends in Data and Analytics, 2022.

Rita Sallam, distinguished research vice president at Gartner said, “This year’s top data and analytics trends represent business, market and technology dynamics that will help organisations anticipate change and transform uncertainty into opportunity, both of which have come under the purview of the data and analytics leader.”

Activate Diversity and Dynamism

The rise of adaptive artificial intelligence (AI) systems, such as AI engineering, drives growth and innovation while coping with fluctuations in global markets. Innovations in data management for AI, automated, active metadata-driven approaches and data-sharing competencies, all founded on data fabrics, unleash the full value of data and analytics.

As one example, the trend “always share data” reinforces data sharing as a business-facing key performance indicator that an organisation is achieving effective stakeholder engagement and increasing access to the right data to generate public value.

The coronavirus pandemic and other recent large-scale global events created urgency to share data in order to accelerate independent and interrelated public and commercial digital business value.

Gartner expects that by 2026, applying automated trust metrics across internal and external data ecosystems will replace most outside intermediaries, reducing data sharing risk by half.

Augment People and Decisions

To make insights relevant to decision makers, data and analytics leaders must deliver enriched, context-driven analytics created from modular components by the business. This includes prioritising data literacy and putting in place strategies to address the scarcity of data and analytics talent.

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.

Gartner research shows that organisations that deal with the human elements of data and analytics are more successful than organisations that only consider technology. A human focus fosters broader digital learning, rather than simply delivering core platforms, datasets and tools.

Institutionalise Trust

Achieving value from data and analytics at scale is only possible by managing AI risks and enacting connected governance across distributed systems, edge environments and emerging ecosystems.

AI is becoming more pervasive, yet most organisations cannot interpret or explain what their models are doing, resulting in a lack of trust and transparency.

Organisations are not prepared to manage the risks of fast-moving AI innovation and are inclined to cut corners around model governance including security, escalating the negative consequences of mis performing AI models, such as incorrect business decisions or worse, those impacting life or death.

As AI regulations proliferate globally, they are mandating certain auditable practices that ensure trust, transparency and consumer protection. By 2026, Gartner anticipates organisations that develop trustworthy purpose-driven AI will see over 75 percent of AI innovations succeed, compared to 40 percent among those that don’t.