You understand that data is the lifeblood of innovation and competitive differentiation. The key is to get the right data into the hands of business analysts when they need it. Sounds simple in theory, but challenges abound. However, for every challenge enterprises face surfacing and connecting the right data, there is an answer.
Let me explain:
From Process Bottlenecks to Busting Bottlenecks
For any data gathering process to work well, business and IT must be aligned. When they aren’t on the same page, when there needs to be a continual back and forth discussion about what data is needed, there is a bottleneck. IT doesn’t know what the data means, business analysts and data stewards don’t necessarily know what data is there.
A splash of data used to be all you needed to get attention. Today, data-smart audiences want much more: detail, what-if scenarios, and deep, multi-sourced data for any questions they may have. They also want to see your work, from initial questions to final insights.
What they want is what people have always wanted: stories. For data, that means data stories. People live and breathe stories, whether they’re aware of it or not. So it’s inevitable, now that business people have tuned in to the “data-driven” ethos, that they would want “data storytelling.”
In a recent blog post about data exploration, Forrester's Boris Evelson discusses Tableau's recent acquisition of HyPer. He notes that HyPer addresses Tableau's previous lack of in-memory data exploration capability.
Though Evelson's blog mentions Tableau and other BI providers, his broader points center around the importance of removing barriers to data discovery, especially when analyzing Big Data stores.
Enterprise search is back in the news—with a twist. Companies that really want to accelerate their results with BI and Big Data are looking to enterprise search as a way to help business analysts quickly find the data they need. Note that I said “data,” not information. Enterprise search has always been thought of as a way to find unstructured content in file shares like SharePoint. But now, it’s being applied to strucutured data as well. And if a search solution can combine data with unstructured content so much the better.
To some extent, virtually all business decision makers rely on business intelligence (BI) analytics and reporting. And, according to an online survey conducted by Forrester Research in 2014, more that 40 percent of organizations using BI achieve double-digit ROI on their investments within two years.  Not only that, but top performing companies tend to spend a greater percentage of their IT budgets on BI.  So it’s all good in the world of BI, right? Not exactly.
Recently I was thinking about the data bottleneck between BI analysts and IT that can add months to analytics initiatives before they produce any meaningful insight. It’s not just that most enterprises are saddled with legacy infrastructure for handling data. Tools like Tableau, Qlik, and Spotfire have created an order of magnitude increase in the number of data consumers in business. There just aren’t enough bodies on the IT side with the technical skills to handle the demand for data the old-fashioned way using code or ETL and MDM tools.