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There is much talk about the commercialization of Big Data. Many understand its benefits, but there is a lack of awareness on how it actually happens. Some organizations join the Big Data game with misconceptions that it is a simple, easy, and quick implementation and have no real strategy in place to derive value from the data. The truth is that there is a disconnect between Big Data expectations and reality.
Working with data is a complex process that needs time, effort, and a proper strategy. Unless organizations have the necessary skills in-house, they would need to have the right partner or vendor that has the data engineering and data transforming solutions in place to turn raw data into a high-quality data product–one that is both accessible and consumable.
Before embarking on Big Data investments, the first step an organization needs to do is to set a data strategy. This refers to the overall vision, as well as the definitive action steps, which serve as the platform for an organization to harness data-dependent or data-related capabilities. Data architects and engineers need to have clear and specific objectives to achieve the organization’s data goals. A misconception when it comes to data investments …
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