Big Data: Avoiding Major Pitfalls

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Each week, DailyTekk connects you with leading experts on a given topic as part of our Understanding series. This week we are focusing on explaining Big Data. Yesterday we highlighted some creative examples of companies who have harnessed the power of Big Data and today we’re focusing on avoiding pitfalls associated with implementing a Big Data strategy. Last week we focused on Instagram Marketing.

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What Major Pitfalls Can and Should Be Avoided?

Sanjay Sarathy: “When thinking about big data, there are two fundamental issues to think about. The first is how an organization searches for and analyzes the data about which it knows something (the “known unknowns”). However, what is far more difficult and more relevant in the realm of big data is how companies analyze data about which they know nothing (“the unknown unknowns”). The biggest pitfall to avoid is to ensure you think about both ‘types’ of data when you implement a big data solution, rather than just the former which is more intuitive and, honestly, easier to manage.”

“Know what specific business problem you are looking to address, and how any insights will get ‘deployed’ into real-time business operations. Companies that set up an environment to collect data with no idea of what problem they will solve, or how the insights will get used in business operations, often flounder. Successful companies are building a real-time data platform that manages data capture, storage, processing, analysis, and finally embedding insights directly into business processes. The really smart companies are leveraging the power of in-memory platforms, such as SAP HANA, to build their data foundation,” says David Jonker.

“There are many potential pitfalls when implementing Big Data, but the biggest is not starting with the “end” in mind. Big Data is only successful if it solves a business challenge and provides the business with the intelligence it needs to beat the competition, evolve strategy, and increase revenue. The opportunity is enabling IT to truly partner with the business and be able to directly tie a technical initiative with customer acquisition and revenue. Without doing that, Big Data becomes technology for technology’s sake and will fail or not get the funding and support required,” says Margaret Dawson.

Matthew Standish: “The Best Buy example [from the previous post] is a perfect example of a company that desires to be a pioneer while not being able to effectively use the data. Companies ...

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