In today’s data-driven world, managing data as an asset is essential for the success of any enterprise. Digital-native, data-driven enterprises like Facebook, Amazon, Netflix, and Google have built their data infrastructure from scratch, managing their data proactively as an asset from day one. This approach has enabled them to avoid data debt, a common problem for traditional companies grappling with massive legacy data debt. Today, savvy leaders of established companies taking on digital transformation look to the examples of digital-native companies, recognizing that managing data proactively is the first foundational step for their digital transformation.
Enterprises today can find, shape, and deploy data for any given characteristic use case. Many analyst-oriented tools are available for “wrangling” data from great companies such as Trifacta and Alteryx. These distinctive approaches, however, are inadequate for solving broader data debt problems and enabling companies to compete on analytics. Next-level leaders are looking to use data aggressively and iteratively to create new value daily as new data becomes available. The biggest challenge faced in enterprise data is repeatability and scale. Finding, shaping, and deploying data reliably with confidence is crucial.
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