Industry, business and government are all growing in data. And they’re adding more data every day. And more and more companies are developing devices that collect data and other product manufacturers are putting more and more sensors into their products. Then there’s the overwhelming number of analytics tools, from the top end Big Data solutions down to small business solutions from a range of companies. So are we drowning in data or are we lost for ways to analyse that data? Do we really need all these data? Do we really need all these analytics tools?
The Implications of Overload
There are now thousands of case studies on the value of harnessing data for improving productivity to safer driving and better health care. And there are, it seems, as many solutions that promise to deliver.
 There are however, some potential ramifications as senior management struggles to harness the data. The biggest is that companies and governments step back from analytics, perhaps thinking it is simply too overwhelming and to costly to do much more than they already are. This is a trough of disillusionment and some might argue we are in it right now within Gartner’s hype cycle.
 The upside is that in economic terms, the market views analytics as being in over-supply and demand trails off. This leads to consolidation and forces survivors to innovate.
The Swan Song of Analytics
Having been deep into the analytics software space since 2008, I’ve seen a lot of change. On the one hand, such as the social media monitoring analytics tools, there’s been very little innovation. On data visualization, there’s been a lot of innovation, especially with Tableau Software, IBM Watson and Microsoft Azure tools. The marketing promise of too many however, is that they can distill a complex story into a simple graph to pop up on the CEO’s tablet with instant understanding. None have delivered.
We Are In An Experimental Phase
Having worked at the C-suite level of guidance on developing analytics programs and solution selection, we still see a lot of confusion within enterprise companies and small business is mucking about in a dark swamp with a small lantern. In medium sized enterprises is where we’ve seen the most organized and innovative approaches to implementing analytics solutions.
 So much of the analytics tools coming out today are still very experimental. Many claim to leverage Artificial Intelligence. They do in a way, using some degree of machine learning, text analytics or natural language processing (NLP.)
Getting Beyond the Hot Mess
Already companies have “data lakes” and  some clever marketer is surely going to move that to “data oceans.” Not only do we have “cloud computing”, but now we have “fog computing” and edge services. Confused yet? The world of data collection, storage, management and analytics is a very hot mess. So how does a company manage?
 In the short term it’s a sticky wicket. There are multiple choices all along the way. As a company or government, it’s about taking more measured approach. Not getting caught up by the hype and taking the time to find a no-nonsense outside advisor; preferably one that isn’t married to any one solution.
 Over the next year, the market will sort itself out more. No matter which solution you have though, a good part of it will be experimental. But backing away from analytics isn’t a solution either.

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