Businesses are collecting massive amounts of data annually, but do they really know how to make good use of it? A recent study from NewVantage Partners finds the answer is: not really.
Nearly three-quarters of organizations in the study (73%) say Business adoption of big data and artificial intelligence initiative is a challenge. And just 38% say they’ve created a data-driven Organization.
What are the roadblocks to making better use out of all of the data we’re collecting? We asked our IDG Influencer community of experts about the biggest challenges to extracting Business value from data, and how organizations are using cloud analytics to overcome those issues. Here’s a summary of their insights.
With organizations collecting and hoarding so much data, the sheer complexity of finding value is the biggest challenge, according to Gene De Libero (@GeneDeLibero), Chief Strategy Officer and Head of Consulting with GeekHive.
“There's way too much data and not enough time to create business-critical insights,” he said. “Add to that the challenge of surfacing the right data and tools for the job, and you have a scalability and agility problem.”
Further adding to the challenge are the variety of data types and the lack of integration among different data silos across the organization. “Large enterprises have many disparate data sources, and it’s difficult to see how all the moving parts of an organization are working together if they’re in different places,” said Jo Peterson (@digitalcloudgal), VP of the Cloud Services Practice at Clarify360.
The scale and complexity of the data often make it hard for IT leaders simply to get a clear picture of what data is available to use to advance business objectives.
“One challenge I see in many organizations is the presence of dark data,” said Jason James (@itlinchpin), CIO at Net Health. “That is to say, data that lives in the proverbial shadows and is seemingly stored but unused or underutilized. In fact, they may not understand what is truly being captured or stored. If data is the new oil, then many organizations may be sitting on large, untapped reserves.”
These underutilized data reserves make it critical for organizations to invest in the tools to normalize data across disparate sources, said Isaac Sacolick (@nyike), President of StarCIO and author of Driving Digital.
“Databases and data lakes are more like data vaults,” he said. “Business people know there's value in the vault and often make deposits, but they don't have adequate tools to know when, where, and how to get insights from it.”
Scott Schober (@ScottBVS), President and CEO of Berkeley Varitronics Systems, agrees that making data accessible is an important step toward deriving value from it. “Since most large enterprises have many differing data sources, it can be challenging even for internal divisions to leverage various resources and personnel to work together throughout the organization,” he said.
Integration challenges extend beyond technical issues to data governance, said Frank Cutitta (@fcutitta), CEO of HealthTech Decisions Lab. “Some of the greatest battles in the enterprise are related to who owns the data, and more importantly who controls the messaging derived from the insights,” he said.
Beyond complexity, data quality is also a challenge. Business value extraction is only as good as the data provided, according to Dave Evans (@DaveTheFuturist), CIO & VP of Technology at The Computer History Museum.
“Quality data depends upon the sources of the data,” he said. “‘Garbage in, garbage out’ is apropos here. With a data deluge, how can organizations ensure the data is quality data? More work is now needed to extract real value, which points to the quality and capability of the tools.”
But even with the right data, many organizations still struggle to use the data to truly capture business value.
