Justin Borgman kicked off the third annual Datanova event with a powerful keynote that exposed some of the big data lies that have influenced us over the last ten years. He balanced each lie with an argument for the truth. If you haven’t watched the video yet, watch it first, and then read my reactions in this blog. I’ll wait right here…
Wasn’t the keynote great?
As I listened to the keynote, I thought about the five lies from a CDO’s perspective. I wondered how they had negatively impacted the key business commitments that CDO’s have made. How many CDO’s had overcommitted, how many of us had set the wrong expectations? I thought about how a CDO might communicate these missed expectations to a business leader, and whether it was time for a painful reset of the data strategy.
As I listened to the five truths, I felt more optimistic. This isn’t the time to reset or take a step back. In fact, CDO’s should take this opportunity to deliver a positive message to the business. The CDO can modify their approach and actively accelerate the strategic outcomes. The CDO can save money and time by rethinking their migration approach. The business can accelerate their data projects and they can reinvest the savings into new analytics projects. Less money on migration, more money on actual data insight.
Reframing the business message
My message to the business is that we can begin to provide immediate access to their data assets and that we will enable them to use self-service capabilities to drive their own data insights. Let’s take a look at how three of the lies impact the business:
- Instead of waiting for data centralization projects, we are going to access the data at the source, in the cloud or on-prem. For the business, this means that we can begin to integrate data across various existing sources and that we will be able to rapidly integrate any new sources that may be acquired in the future.
- Rather than talking to the business about a modern technology stack, let’s talk about the modern data ecosystem. For the business, this means a greater focus on simplifying processes and promoting consumer enablement. To be data driven, we need to empower the consumer to work with self-service tools.
- We’ll need to improve the data foundation before we can fully exploit AI and ML capabilities. According to a recent Boston Consulting Group study, just 54% of managers believe that their company’s AI initiatives create tangible business value. These AI and ML projects suffer because finding the trusted data that they need takes far too long. These are innovative initiatives that require rapid iteration, and need the ability to rapidly find and integrate new data sets. Business driven AI and ML projects will deliver greater tangible results if we can enable faster access to enterprise data assets, regardless of the source.
I don’t need a yacht, I need a fast engine to manage all my lakes. I need Starburst.
Starburst Galaxy workshop, April 4, 2023
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