Answering Big Datas 10 Bigge 263047

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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.

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Table 1. Key Questions and Answers
Question Summary

Answer Highlights

Big data hype or substance?

Beyond all the discussions, adoption of big data is simply inevitable.

What are others in my industry doing?

Evaluate what leaders are doing in other industries to identify best practices. Range of sources of big data projects?

Operational data, social media and enterprise dark data are all sources for big data.

Do we have a big data problem?

Your IT infrastructure should support the growth of big data; and your business should be able to achieve its objectives with the range of data being analyzed.

What is the value of big data projects?

The ability to analyze data in new ways, leveraging new sources, all in economically quicker ways.

Do we still need a data warehouse?

Gartner predicts that 90% of data warehouses will not be replaced.

What is big data analytics?

The application of analytic capabilities on enormous, varied or rapidly changing datasets.

What data can we use?

Privacy is both a legal issue and an executive-level ethics issue.

What skills do we need for big data?

Beyond data scientists, the systems supporting data scientists will require configuration, administration and management.

Data scientist versus a statistician or BI analyst? Data scientists tend to embody a more inclusive range of skills.

BI = business