data-revolution
Statistical Data Analysis

How tech providers have evolved with the data revolution

This is a contributed piece by Stuart Wilson, VP EMEA at Alteryx

When The Guardian gained access to a huge cache of diplomatic cables in 2010, it was faced with a big problem: how to sift through and extract from this huge, unwieldy mass of data – all 1.73 gigabytes of it – into stories. The newspaper’s answer was to invite its readers to comb through the documents themselves to find the most interesting nuggets that could be turned into news.

Unsurprisingly, The Guardian did not seek the help of the established business intelligence (BI) giants of the time, who would most likely have refused to analyse what is now termed “the largest set of confidential documents ever to be released into the public domain”. Since the newspaper broke the State Department cables story, however, the world of analytics has been turned on its head.

The commercial analytics space used to be dominated by software giants such as SAP and Oracle. Powerful as these tools were, they required users to surrender their information to teams of specialist analysts and data scientists to write code over weeks or months in order to make everything work. Self-service analytics simply wasn’t an option, unless your company was big enough to employ its own data experts.

Fast forward to today, and there are a wealth of data analysis and BI technologies available, ranging from consumer – or education-grade visualisation software, to powerful cloud-based analytics platforms for enterprise data. The recent announcements of Amazon’s QuickSight and Microsoft’s improvements to its heavyweight analytics tool, Power BI, are great illustrations of this shift, which has important implications not just for newspapers and publishers, but for any person or organisation that uses information.

The big difference between 2010 and now is that the new generation of technology providers are focused on encouraging users to take data analytics into their own hands. Instead of having the technology firm crunch the numbers, businesses are now learning how to extract value from their own huge data sets; and to build their own data visualisations that make sense of enormous volumes of information.

It is not an overstatement to say that these companies have completely transformed the established narrative of “Big Data.” As businesses began to measure their information assets first in terabytes, then in petabytes, commentators warned that we were at risk of ‘drowning in data.’ Today, the story is all about how ordinary people are harnessing even bigger data sets – including the exabytes of the web – to derive real, actionable, and timely insights.

The tools used to achieve these results fall into two categories: powerful, in-depth business intelligence platforms such as Microsoft’s Power BI; and data visualisation tools from the likes of Tableau and Qlik, which enable ordinary users to make turn large amounts of raw information into easily-understandable dashboards and charts.

What unites these different technologies is their focus on the end user. Providers expect and encourage their customers to take charge of analytics and BI themselves; indeed, the tools themselves are usually designed for self-service.

This is already having a profound and exciting impact on businesses of all sizes. It’s not just that they can instantly analyse their internal data, their marketplace, social media, and the wider web to answer urgent questions and shape their strategy, revolutionary as that is. It’s the fact that ‘ordinary’ workers employed in a huge range of industries – from healthcare to construction, marketing to journalism – are increasingly expected to be capable of analysing, and basing their decisions on data.

A few years ago, this would have been unthinkable – both for the workers themselves, and for the big BI firms that were paid to perform the analysis. Today, technology providers understand that the best people to interpret data aren’t always professional analysts, but often the subject matter experts themselves, whether they are clinicians, marketers or architects.

We are only beginning to scratch the surface of what data can do, but the tools to turn information into insight are already with us. There’s no telling what data will teach us in the next few years, but one thing is certain: analytics and BI will become ever-more central to our working lives, and this can only happen if our analytics tools are made easier to use for business.

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