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Big data analysis demands new tools to create actionable insights

Data’s long been an important asset in a company’s competitive toolkit. Over the past few years, new digital solutions and the advent of cloud-based technology has given it a lot more attention though. Businesses are rushing to accumulate massive “data lakes”, intending to mine them for valuable insights.
Adopters of big data are starting to run into unforeseen challenges. B2C reports that with 50 percent of data now originating from external sources, cataloguing and storing it all isn’t as simple as firms first though. Although there may be actionable information within the data lake, it’s getting harder to separate the useful bits from the noise of the rest.
Companies harvest data from an increasingly varied range of sources. Analytics is being used in every major field and industry, from sports through to human resources. Whether a company sells to consumers or other businesses, it’s likely data influences some part of its everyday processes.
Companies are now looking for data catalogues capable of surfacing the interesting portions of their reserves. They need an intelligent solution that can automatically extract actionable insights from across the entire data lake. It’s also got to be accessible, available to everyone from the IT department to senior managers.
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Unless all the key players can access the data’s insights, the entire reserve is effectively meaningless. Too often, firms task their IT staff with managing their data lakes. The idea of “data” is still associated with IT support workers and complex database software.
Although IT can assist in making data usable, it’s not the endpoint for the analysis process. It doesn’t possess the wider context of the business that makes the data useful to decision makers. For companies to truly harvest the value of their ever-growing data lakes, it needs to be high-level leaders who are looking at the insights.
Some firms are already moving beyond big data. Having failed to fully align themselves with the big data movement, companies are shifting from traditional business intelligence platforms towards AI-powered systems.
These have the advantage of offering real-time insights, allowing companies to monitor their data while an event’s still ongoing. They can also perform much of the filtering, organising and analysis automatically, producing digestible reports for decision makers that increase data visibility. The result’s a more actionable data lake that the business can tap into as required, creating clear data pools instead of an overwhelming lake.

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