Essay about Answering Big Datas 10 Bigge 263047

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This research note is restricted to the personal use of G00263047 Answering Big Data's 10 Biggest Vision and Strategy Questions Published: 12 August 2014 Analyst(s): Douglas Laney, Alexander Linden, Frank Buytendijk, Andrew White, Mark A. Beyer, Neil Chandler, Jenny Sussin, Nick Heudecker, Merv Adrian Gartner analysts address the most pressing vision and strategy questions that business, analytics and information professionals have, providing valuable insights on dealing with big data projects successfully. Key Challenges ■ Even as organizations are embarking on big data initiatives, many still have several vision and strategy questions regarding how to drive the most value from these vital projects. ■ As…show more content…
Whether your organization is just embarking on a big data initiative, or if you are further along the maturity curve and looking to take the next step in deriving value, Gartner can provide support and guidance. In this piece, Gartner analysts address the most pressing and prevalent questions they receive about big data vision and strategy. (For further information, read our companion piece on the biggest planning and implementation big data questions, "Answering Big Data's 10 Biggest Planning and Implementation Questions.") In this note, we tackle both the hype and practical matters surrounding big data, including questions such as: ■ Is there actually any real substance behind all these big data discussions? ■ How do you know what data can be used and what potential usage might attract public criticism? Page 2 of 11 Gartner, Inc. | G00263047 This research note is restricted to the personal use of This research note is restricted to the personal use of ■ What is the value of big data projects? ■ Where is this value found and how can it be justified and proven to the rest of the organization? ■ What sources should you gather information from, how can you collect social media and what are other leading organizations doing with big data? Finally, we look at the issue of your big data organization and skills: ■ What skills are required for big data? ■ Is there a difference between a data
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