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Data analytics takes on new importance

First off, big data analytics is becoming increasingly important for both IT and the business side. In a 2011 survey, we asked large midmarket (500 to 999 employees) and enterprise (1,000 employees and up) IT decision makers familiar with their organization’s current database environment about the importance of big data analytics -- 6% said it was their most important IT priority and 45% said it was among their top five. In 2012, when we asked the same question (albeit a slightly different demographic that covered more of the midmarket and went to firms with as few as 100 employees), we saw the number of firms that will consider enhancing data analytics to be their top IT priority triple to 18% while 45% had it in their top five.

We added a spin to our survey in 2012 by asking about the importance of enhancing big data processing and analytics exercises relative to all business priorities. That moved the needle quite a bit, with 28% rating it as a top business priority relative to all business priorities and 38% putting it in their top five.

Next, the data is big. Our 2011 research found more than 50% of respondents processed at least 500 GB of data, on average, as part of a typical data analytics exercise. In 2012, we found the largest data set on which organizations conduct data analytics is, on average, 10 TB.

Processing and analytics is also becoming a more real-time exercise. In 2011,

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we asked about the frequency of updates in general, and discovered that 15% of those surveyed update in real-time and 38% within a day. We wanted to see the biggest of big data challenges in 2012, so we asked users how often they updated their largest data set -- 22% said they update in real-time while 45% update in near real-time (within a day).

Finally, there’s very little tolerance for downtime. In our 2012 research, 53% could only tolerate fewer than three hours of downtime before their organization would experience significant revenue loss or another adverse business impact. Of that group, 6% can’t tolerate any downtime. Only 14% of respondents indicated they could withstand downtime exceeding 24 hours.

This was first published in July 2012

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