The big data market is predicted to be valued at an astonishing $100bn (£60bn) by 2020, according to IDC. So does that mean demand for more traditional analytics tools is rapidly giving way to adoption of newer non-relational technologies?
Channel 4 CIO Kevin Gallagher believes that a combination of older and new technologies is necessary, and that the rise of big data has meant traditional technologies are now more important than ever.
"With 4OD, we want viewers to be recommended the shows that they want to watch, so we're using our big data history to look at what people have liked before, and recommend them episodes that they haven't seen from that show or ‘people who liked this tend to like this, also viewed this' options," he told delegates at Computing's Big Data Summit.
"Big data [initiatives] are good for doing that because there is so much [data] there, and actually traditional databases are brilliant when you've got 10 million viewers' data to [sift through]," he said.
"The appetite for traditional insight and technologies hasn't gone away, in fact it has grown," he added.
Mike Gualtieri, analyst at Forrester Research, agreed with Gallagher, explaining that currently there is a lot of "cold data" on relational databases that used to be queried, and that now the data remains on these databases as an "expensive resting place".
He said that the use of big data technologies such as Hadoop enables companies to easily accumulate more data, but those organisations are then going to need to query or process that data in a very high performance platform.
"So you may see some data move off into Hadoop but then I think it's going to swell back up again into the high-performance platforms," Gualtieri suggested.
But, of course, traditional big data tools don't work for everybody, and much of this is down to the industry in question.
Charles Ewen, CIO at the Met Office, said that traditional database and business intelligence tools are inadequate for conducting BI data analysis because they cannot easily handle the "dimensions" of time and uncertainty.
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