Why you need a data hub for future-proofed BI
- by 7wData
Donald Farmer is the Principal of TreeHive Strategy and formerly the VP of Innovation at Qlik.
So you have chosen a platform for Business Intelligence: flexible, usable, manageable, scalable: all those great abilities in one package. Soon you'll integrate, visualize and collaborate across the company as never before. A consistent view of the data is at hand. You can see the end of spreadsheet hell. No more complaints about compliance. Except ...
It never quite works that way, does it? Your carefully crafted architecture strains to hold together from the first day of deployment.
At 10pm, the night before the quarterly business review, with numbers to crunch and new charts to create, your sales team still reaches for Excel rather than your shiny BI tool. Convenience wins over compliance, and years of practice makes Excel the easy choice. Nor should you think this scenario a bad thing: people are working hard in your company to get things done.
Elsewhere in your organization, an expert needs just that one visualization your BI tool lacks. Or that data source. Or that algorithm. Soon enough, there will be one more tool for you to manage when you find out about it, belatedly. It will be a little more specialized and gaining a foothold. And nor is this a bad scenario; we're just seeing more people working to do the right thing.
Your mergers and acquisitions will bring new architectures and applications to live alongside your own. It can take years to merge and rationalize across those orgs, and meanwhile, daily work still has to go on. And in the BI market, companies and technologies come forth, grow, stagnate and are bought and sold. So where does that leave your plans?
This is just the way of the business.
You can, however, design an architecture to cope with change from the first day. To do so, your aim should be to insulate systems from breaking changes while enabling simple integration and rapid development of new designs.
Traditionally, data warehouses held out some of these possibilities. Users might access the underlying data models from a wide variety of tools, even the latest shiny BI visualizations. Architects might add new sources to the data warehouse or even new subject areas following a merger. Administrators maintain the authority of the data by strict quality controls.
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