Small Steps For Data Analytics
By Sachin Yadav
In the rapidly evolving IT space, the notion of creating and leveraging data analytics is rapidly gathering momentum, for the all right reasons, including the nature of the complex problems we are trying to solve, the volume of data we need to store and the velocity at which we need to process it to be able to create data models swiftly to answer our complex business questions in real time. For Einstein aptly said, “The solution of the problem cannot be the simpler than the problem itself.”
However, for a multitude of reasons, getting started on this journey remains challenging, where and how to undertake this big effort, being one of the biggest impediments toward its adoption. With the underlying technology, hardware and software, for data analytics reaching a new level of maturity, the strategic framework to formulate the journey is not as much a question of technology, or its underpinning elements, but rather of structural and systemic cross-functional elements that need to be aligned to ensure the journey is effective. On the outset, we will define effectiveness as the ability to achieve the intended business results within anticipated costs and timelines.
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