Business analytics may be trending. The question is whether growth threatens to outstrip capacity.
Yesterday, Tableau released an interesting breakdown of the specific ways in which business analytics is trending right now. Of course, Tableau is a business analytics vendor, so any trend looks like good news to the company. But its outlook is persuasive.
It emphasizes the importance of "self-reliance" -- users being empowered to generate their own analytical queries and reports rather than relying on IT. It predicts that Hadoop will be big in 2013, which goes hand-in-hand with the growing importance of unstructured data.
"Predictive analytics" and "pervasive analytics" strike me as marketing smoke and mirrors (since when do enterprises use analytics exclusively to understand the past?), but on the whole this is a shrewd take on the directions in which BI is headed.
But there's a potential problem with this. At least, there is if you believe Gartner's latest research on the challenge of scale.
It's not called "big-data" for nothing. IBM estimates that we create 2.5 quintillion bytes of information every day (that's a billion billion, if you're counting). It's safe to assume that no enterprise wants or needs to analyze all that, but simply keeping up with the global conversations on platforms like Facebook and Twitter can stretch capacity -- especially as we're talking about unstructured data here, and not number-crunching.
This dovetails neatly with Tableau's prediction for Hadoop. With its developing reputation as the premium tool for organizing very large sets of unstructured data across multiple servers, Hadoop, and its various modules, Gartner's prediction is hardly surprising:
While IT organisations conduct trials over the next few years, especially with Hadoop-enabled database management system products and appliances, application providers will go one step further and embed purpose-built, Hadoop-based analysis functions within packaged applications. The trend is most noticeable so far with cloud-based packaged application offerings, and this will continue, it said.
Cloud is the other part of the puzzle, of course. Enterprises looking to scale BI in response to the apparently irreversible growth in volume of data are just about compelled to consider cloud-based options.
Hadoop is certainly a solution for distributed data storage within internal datacenters, but internal datacenters will surely be increasingly left behind, not only by the volume, but by the velocity of data requiring processing -- a trend on which the mobile explosion is also bound to have an impact.
The right storage for the right data loads -- which probably means cloud platforms; Hadoop, or comparable software frameworks, to organize the data; and employees with the confidence and understanding to query it. These are elements far-sighted businesses need to have in place, before we go from zettabytes to hellabytes.
I agree. Specialists are needed to compile, clean, and supervise the storage of the data. End users need accessible dashboards so that they can query the data and get intelligible, useable results. The demand for real-time data means IT (or data analysts) can't act as go-betweens on each query.
The end users is where the value will be created, otherwise we will continue to build towers of Babel.
I think, to Mitch's point, we need both. We need distributed data to the end user that is more functional and intuitive to deliver useful information for business decision making. But we need people trained in analyzing data and applying to complex and changing dynamics to provide new insights that are useful - thus our analysts and data scientists.
Clearly, beyond learning how to integrate with cloud solutions, the ability to begin to understand and effectively use data in meaningful and productive ways to the organization is a total study in itself - going far beyond just creating software and reading reports - otherwise we will not scale effectively.
The emphasis I keep hearing is putting the data in the hands of end users. Rich Luciano is very good on this in the Corner Office videos at the top of our home page.
It emphasizes the importance of "self-reliance" -- users being empowered to generate their own analytical queries and reports rather than relying on IT.
Is that best? Are users equipped to do their own analytics?
Analytics seems to be emerging as its own specialized field of knowledge. Are we seeing it emerge as its own department, just as IT, legal, marketing, and customer service are their own specialized disciplines?
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