Why do companies keep releasing new data platforms? Because we haven’t solved the problem yet. Whenever I see a product landscape (View Highlight)
Customers don’t fully understand their needs, and solutions providers aren’t done guessing. The amount of money flowing into the data platform space proves there’s ROI to be had by whichever business finally figures it out. (View Highlight)
Smaller startups have the advantage and will build best-in-class solutions for a targeted set of use cases better than incumbents. The only way for a company to become a macro technology platform is to create a partner ecosystem (View Highlight)
The ecosystem model is the only one that makes sense, so the move towards developing them is unavoidable. A strong core product with a best-in-class ecosystem is the way this should work (View Highlight)
Implementing a technical-strategic architecture (I’ll explain that concept more next) like data fabric is impossible without an open ecosystem. (View Highlight)
Opensource components can add massive value and should also be part of the ecosystem. That’s an even more significant challenge for large enterprise software companies, but it’s not a true ecosystem without opensource being a part of it. (View Highlight)
Pricing touches every part of the retail business, and building the model required data from multiple organizations. I spent more time getting the data engineering side working than building and improving the model. (View Highlight)
The biggest challenge was rebuilding the business context required to support that part of the pricing model. The connections between product size, margin, sell-through rate, floor space, and inventory planning lived in a few employees’ heads. (View Highlight)
It’s painful and expensive. Businesses keep every piece of data because they don’t know which data contains signal that helps reassemble the business context. (View Highlight)
The need to connect data from across the business to support use cases makes technology a top-level strategic construct. Business data fabric is a strategic and architectural construct that fits into the macro technology platform paradigm (View Highlight)
Data fabric solves the challenge of maintaining business context as much as it solves the challenges around data engineering and governance. (View Highlight)
C-level technology leaders and teams are strategic partners. The macro technology ecosystem must support that goal by prioritizing the business need vs. the data or technology (View Highlight)
