Gartner Data & Analytics Summit 2022 in London: 3 Key Takeaways

Introduction

What a week! Alation attended last week’s Gartner Data and Analytics Summit in London from May 9 – 11, 2022. Coming off the heels of Data Innovation Summit in Stockholm, it’s clear that in-person events are back with a vengeance, and we’re thrilled about it. At Gartner D&A, speakers led fascinating discussions about the future of data fabric, data mesh, governance, and synthetic data.

Let’s dive into the key takeaways from the week.

Gartner Data & Analytics Summit 2022: Keynote Highlights

Monday’s keynote began with a bang. A Gartner survey found that 57% of Boards of Directors have increased their risk appetites, and data & analytics are fueling more risky (and potentially rewarding) projects. Leaders agree: Data needs to drive business results. But how do you arrive at that end state? And how do you transform data from a liability into an asset? The keynote highlighted three key steps organizations should take.

How to use data to drive business results:

1. Establish what data you have

Active metadata gives you crucial context around what data you have and how to use it wisely. Active metadata provides the who, what, where, and when of a given asset, showing you where it flows through your pipeline, how that data is used, and who uses it most often. People are increasingly dependent on active metadata to understand a given asset’s quality, relevance, and typical use cases. And its applications are growing. Gartner shared that organizations today are using active metadata to enable data fabric, identify data drift, and locate new categories of data.

2. Leverage small data

It’s not just about big data anymore! A small set of accurate, quality data can be much more powerful than vast troves of low-quality “garbage” data. So what should people struggling with low-quality data do? Gartner advises that you create a minimum viable dataset to fuel your use case. Never underestimate the power of small data.

3. Think about what data you can create

Synthetic data is growing in popularity as a tool for data scientists. This is data that’s artificially produced to mimic and model real events: It retains the structure of the original data but is not the same as real data. Synthetic data will be invaluable for avoiding privacy violations in the future, and Gartner predicts that by 2025, synthetic data will enable organizations to avoid 70% of privacy violation sanctions. Gartner predicts that by 2030, synthetic data will completely overshadow real data in AI models.

These are three areas in which analytics is rapidly advancing. The keynote speech also emphasized the importance for analytics teams of finding important patterns, asking great questions, and knowing when to stop.

Further, automated insights are growing in popularity, and empower analysts to become “decision designers.” Advanced UIs support this transformation and can signal to data users the right insights at the right time, helping to accelerate decisions and connect them.

Data Fabric and Data Mesh

So how are leaders supporting innovative analytics? Data fabric and data mesh are popular new design concepts gaining momentum in this space. To be clear, because they are design concepts, data fabric and mesh cannot be bought, but they can be built. Gartner’s advice? Don’t look for data fabric “platforms” – instead, look for composable, tightly integrated – yet loosely coupled – services that share metadata.

According to Gartner, “an abundance of every type of metadata significantly enhances the probability of success in a data fabric initiative.” Therefore, platform that supports metadata management is crucial to a robust and powerful data fabric. Most organizations leverage an augmented data catalog as a platform for the data fabric, atop which they interweave modular technology, which share metadata to enhance operations.

The business benefits of a data fabric are real. Two-thirds of those surveyed by Gartner reported that data fabric has business value. And modern-day proponents share that a data fabric (which runs on active metadata via a data catalog) reduces their human effort by half. Gartner predicts, more conservatively, that by 2025, active metadata assisted automated functions in the data fabric will reduce human effort by a third and improve data utilization fourfold.

For this reason, the rise of data fabric is inevitable, and early adopters will outpace competitors.

Data mesh, too, was a key topic of conversation. Data mesh was on the lips of many attendees, from the hallways, to the Alation booth, to vendor presentations. Anecdotally, I’d say conversations were split 50/50 between data fabric and data mesh. Luckily, data fabric and data mesh work in perfect harmony, and together go a long way toward automating data governance in the enterprise.

Data Governance

On the topic of data governance, Gartner did not mince words: Traditional data governance has failed the average business. And while data governance is no longer about control, total freedom, without governance, is anarchy. So how are leading enterprises walking that line?

According to Gartner, governance “is the process of deciding how to get things done.” In this way, it both controls and enables people around data, fueling innovation. Data governance must be outcomes-focused, supporting agility and autonomous operations.

Innovation was a key outcome for Steve Pimblett, CDO of The Very Group, when the business embarked on its data governance journey. Steve walked listeners through that journey during his session at the Gartner summit.

How Governance Fuels Innovation at the Very Group

The Very Group is a multi-brand online retailer and financial services provider based in the UK. It has built “one of the oldest, richest and deepest consumer-focused data set/s in the UK,” and hosts 2.2 million daily website visits for shoppers perusing 2,000+ famous brands, with 49 million items shipped annually.

All that data was causing serious growing pains for the business. The Very Group faced 11 complex business domains, hundreds of systems, and hundreds of thousands of assets going back decades. As CDO, Mr Pimblett needed a solution that would help him govern and audit in a data landscape hosting complex lineage, many glossaries, and siloed data, with limited automated and siloed stewardship. He sought to shrink the timeline, from data → insight → action, dramatically.

The Very Group partnered with Alation to address these challenges. Steve leads a team that uses Alation as a hub collaboration tool that empowers colleagues with trusted data so they can drive value. Today, that team is finding and using data in half the time it once took, and welcoming new hires to data in a matter of weeks (rather than months).

Addressing these pain points for data users has empowered The Very Group to innovate on a number of fronts. With Alation, The Very Group is enhancing its customer-centric marketing and experience with smarter decisioning and improved bots and assistants. They’ve also accelerated cloud migration, reducing the time, storage and associated costs of migrating and storing data in the cloud.

Conclusion

The summit was packed with insights and success stories. Data leaders have cause to be hopeful for the future of data & analytics, as the field is advancing quickly and with great promise. Metadata – and the supporting tech that can share it, integrate it, and learn from it – is key to that future.

Want to learn more? Check out these materials:

• Join the webinar: Why an Effective Data Quality Program Includes a Data Catalog

• Get the Gartner report, Accelerate Adoption of Metadata Management Solutions

• Read the Forrester Wave: Data Governance Solutions, Q3, 2021