Data-driven companies, which get analytics to their teams faster, are three times more likely to find their financial performance superior compared to their competitors, reported the Economist Intelligence Unit.

The term Enterprise Data Warehouse has fundamentally shaped our way of thinking when it comes to information data management and analytics. Before data warehousing, reporting and provisioning data from disparate systems was a slow process that often failed to meet the organization’s need for actionable information. However, such a traditional approach to information management has become more and more problematic for being expensive, time-consuming and inflexible. As a result, companies are shifting to more agile methods to stay competitive in today’s dynamic business environment.

According to Gartner, around 85% of all big data projects are deemed to be a failure, resulting in about $159B of wasted investment. The common reason, behind this negative outcome, is that their overall data strategy is often outdated. For example, many organizations try to ensure that their data, as well as the systems around it, are perfect before opening them up to users. At the end of the day, if your data isn’t in good shape, why continue with analytics? Well, think again.

Do you want your data project to be among the successful 15%?

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