Big Data is big news. Articles abound with information clarifying its definition, whether it is just hype, and the technology that best supports it.

But how is Big Data actually viewed and used in the real world? What do real-world business people want to see as the data sources for Big Data projects? And which analytic and presentation approaches are expected?

In its white paper 2012 Big Data Survey Results, Treasure Data compiled responses from hundreds of IT and business managers from fast-moving, data-driven companies.

Recognizing that companies see proprietary vendor solutions and traditional warehousing technology as costly and behind the curve, some are looking toward open-source options to fit their Big Data project needs.

To gain insight into how this segment views these alternatives, Treasure Data asked the following questions, with some of the key findings highlighted here:

• How do you view the Big Data opportunity?  Nearly everyone (90%) agree that Big Data is an interesting concept, with 24% actively working on Big Data projects. Only 3% feel that Big Data is the latest industry fad.

• What attributes do you most associate with Big Data architectures?  The majority of respondents view traditional data warehousing approaches as costly and complex, but they also see them as secure.  Hadoop is most strongly associated with complexity and the need for specialist IT resources. Cloud solutions are seen as scalable and having speed.

• What data sources do you want to use in your Big Data projects?  Structured application data (77%) remains the most common single data source. Most are using log files as a primary source of their data, but a surprising number are also using Internet feeds (54%) and subscription services (48%).

• How do you want to analyze Big Data?  For analysis, 60% want to use standard business intelligence tools.

• How do you want to present your Big Data? Reporting, queries, and dashboards are the most common approach (75%).

Download 2012 Big Data Survey Results (registration required) for complete survey results and to see how your Big Data ideas match with your peers.

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