Data lakes provide an economical means for storing and processing data. However, gaps remain in the maturity and capability of data lakes, leaving organizations struggling with how to reap their benefits in analytic scenarios.
Enterprises are trying to support two ends of a spectrum: agile, decentralized discovery and governed, trusted, centralized BI. The dirty secret is this dual approach creates more data silos with increasing data feeds and extracts. Conversely, leading organizations are breaking the mold, by connection their enterprise through an interwoven fabric of data: enabling agile, trusted discovery and centralized BI.
If money talks, then CIOs’ spending habits have a lot to say about the state of Business Intelligence (BI). For the past decade, BI and analytics have been a top investment priority for businesses, but the technology has yet to meet business needs and live up to the promise of BI.
I have been in the tech industry for a long time. Since before Taylor Swift was born, even. Over the years, many innovations have struck me as interesting ideas that would never gain any traction, simply because there was no data infrastructure to support them, or no way to get real business leverage from “innovation.” (Remember smart appliances?)
It was Rumpelstiltskin who had an amazing alchemic device – a spinning wheel – that turned straw into gold. Since then, many companies have attempted to replicate this type of magical transformation, with limited success. But, in all seriousness, business-savvy CIOs are now using enterprise analytics to monetize the vast stores of data generated every day through customer interactions and the businesses itself.