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Maximizing Business Value Through Data and AI Tops List of Data Management Trends for 2024

The coming year will be marked by trends that support a more dynamic and better-managed data environment.

As we finish out 2023 faced with a tumultuous economy and fever-pitch excitement around AI, business leaders could be forgiven if they are feeling ambivalent about the future. Despite the enthusiasm around AI, many organizations are still focused on bridging the widening gap between their business and technical teams. Cultural as well as technological change is needed, and the companies that are primed to maximize the value of data inside and outside their business are those that establish a strong data culture founded on self-service data access guided by well-governed data management.

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Looking forward, 2024 will be marked by trends that support a more dynamic and better-managed data environment.

Prediction #1: Data management will drive more investment than AI initiatives

Although most organizations have accelerated their data-driven processes in the past two years, only roughly 20% of them use data-driven decisions to realize business value “all the time.” What this tells us is that many businesses have laid the groundwork for a streamlined data practice within their organization but very few of them are achieving this insight in an automated way. Everyone wants to say they have a functional AI practice, but the reality is that most data-driven insights are still a lot closer to manually generated PowerBI dashboards than real-time predictions based on machine learning models.

The reason organizations still struggle to follow through when it comes to AI is not because the technology isn’t mature enough, but because businesses aren’t mature enough to operationalize it effectively. Without the right data environment, dropping AI into an organization is like putting a NASCAR engine in a horse and buggy.

How do companies upgrade their environment to match AI’s potential? Effective data management. Over the past two years, we’ve seen an explosion of investment in tools and processes that help eliminate the chasm between technical, data-owning teams and non-technical, business-facing teams. This divide stops business impact in its tracks. Accordingly, in 2022, 45% of enterprises were allocating budget to “data translators,” whereas only 16% of executives were scaling analytics or AI initiatives.

This budget allocation, focused squarely on better-managing data through a stronger culture, flies in the face of the narrative that all companies are “investing in AI.” The reality is that AI is a bright future that very few organizations are ready for, and to get there, most companies will need to spend 2024 investing in tools that help get their house in order so they can recognize value sooner.

Prediction #2: Data managers will become the most popular data-related hire

This prediction follows the first in an important way. In 2012, after “data scientist” was named the sexiest job of the 21st century, businesses scooped up these data professionals in droves, believing that hiring enough data science talent would result in immediate benefits for the enterprise. When transformation didn’t happen overnight, architectural models were blamed. As a result, development of the data lake and advancements in AI and ML came to the foreground to support the rosy vision of a future powered by data-driven decision-making.

In 2023, we’re more pragmatic. Data science is still an important division at most businesses, but the expectations for what that division can accomplish have been tempered by experience. For most organizations, data scientists provide an important R&D benefit. Research and development, however, is not the goal for organizations looking to win the market.

What’s needed is a way for most organizations to operationalize their business-facing teams’ use of data. This historically has been an issue, given that IT often owns the data the business analysts need.

Enter the data manager. Data managers are the people responsible for governing both data quality and access, and they act as critical facilitators for data analysts and other business users who otherwise lack the ability to serve themselves the data they need. The distributed frameworks that make this possible are supported by new technology advancements such as data virtualization, which lets organizations centralize their data access without centralizing data assets, allowing data managers to centrally manage and distribute data without an expensive lift-and-shift to the public cloud.

Prediction #3: Initiatives that save money will be prioritized over those that make moneyIf you ask any business leader, there are really only two things they care about when it comes to their bottom line: does this make me money or does this save me money? Historically, the focus for most organizations has been on the former, and the narrative around the potential of data-driven transformation has always had at its core a promise of data productization and monetization.

However, in the past two years, executives have been frustrated by the lack of success of these money-making projects. Vanishingly few of them generate revenue in their first few years and only a few break even. Most data product initiatives end up costing the company time, resources, and capital.

For business leaders who have invested heavily in data strategy and data technology over the past ten years, these results are demoralizing. Cloud costs are ballooning and most business leaders don’t want to throw good money after bad.

That’s why, technologies designed to reduce cloud costs, streamline workflows, and save critical resources (staff, time, and spending) will be prioritized in 2024. The good news is that benchmarking the success of these initiatives is often much easier than establishing a baseline ROI for money-making projects. Additionally, it will be relatively easy for organizations to report on how much money they’re saving by consolidating data contracts and integrating technologies into a common suite.

Even small projects, such as reducing the time to generate a monthly report from one week to one hour, will have cumulative downstream benefits. Business leaders will be more than happy to take a win in the first half of the year, and finding ways to improve efficiency without sacrificing innovative projects that are working will be a welcome change.

About the Author

Lewis Wynne-Jones is the VP of product at ThinkData Works, where he helps build a data management platform that helps organizations unlock the value of their data by connecting, managing, and distributing data assets from a secure and easy-to-use platform. You can follow Wynne-Jones on LinkedIn.

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