Analyzing Big Data: What Really Matters?

If you lead an analytics or business intelligence (Bl) program, the impact of big data is palpable. Your business users want to analyze large volumes of multi-structured and fast-moving data. Power users want to build their own reports without waiting days, weeks, or months for the information technology (IT) department to do it for them. They want faster, better, and cheaper tools to access data and generate insights. You need to act fast.

You know all too well that your current Bl environment is inadequate to meet the need. But you also recognize that new data analytics platforms and technologies are in various stages of maturity, and any changes you make will be disruptive and costly. Therefore, your goal is to find new technologies and approaches that maximize the upside and minimize risk.

This paper is designed to help you navigate the shoals of selecting a Bl tool for a big data environment. There are many things to consider. For instance, how do you:

• Query terabytes or petabytes of data with near instantaneous response times?
• Load, store, and manage both summary and detailed views of data?
• Empower users to explore data without creating data silos?
• Create a standard view of data that adapts quickly to changing requirements?
• Simplify a complex data architecture with multiple data processing engines?
• Leverage the talents of the IT department without creating bottlenecks?

The answers to these questions are not straightforward. They involve a mix of people, process, and technology. This guide provides six action items to guide your efforts in selecting an appropriate Bl tool for a big data environment. It's designed to help you ignore the hype surrounding big data and focus on what's really important.

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