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The Growth of Business Intelligence in 2017

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The Growth of Business Intelligence in 2017

Companies must develop a new complex ecosystem of data, people, and ideas. Data analysis will soon cease to be a specialization; it will become key for every employee.

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It has been estimated that as many as 91% of the so-called facts from Donald Trump’s election campaign are untrue. The scale of this phenomenon means that the denial of false information has ceased to be effective because such messages are drowning in a sea of memes, tweets, catchy titles, and brainless posts. It's no wonder that Oxford Dictionaries declared post-truth the word of the year for 2016.

In a broader sense — not just in political terms — this could be due to the phenomenon of data pollution. Virtual reality is suffocating from too much information. Experts from Qlik say that this phenomenon is so severe that it will come to define technological trends in the coming years, just as with business. Certainly, this is the case in the field of Business Intelligence.

2017 will be the beginning of the fight against data illiteracy, which is the process of spreading the skill of reading data and understanding its analysis, verification, and selection. Other trends for 2017 are big insights, business intelligence based on context, and the increasing use of data analysis tools by employees at all levels.

Data Pollution

It is estimated that by 2018, 80% of data stored will be completely useless, with neither the possibility nor sense of processing it. This is directly related to the above-mentioned phenomenon of data pollution. Infrastructure for data storage is cheap and widely available, so companies are producing an increasing number of bytes. Unfortunately, their value is questionable at best. The collection of such data is often art for art's sake, without purpose and strategy, just a vague idea that it may prove useful sometime down the track.

The result is that even information that's important to a company often dies in the black hole of the database. Such a situation fails to facilitate the wider use of IoT. Like every great idea that originally was intended to serve the good of humanity (economical and ecological houses or cities, the comfort and convenience of senior citizens and people with disabilities, etc.), the Internet of Things is becoming a caricature of itself. The Internet can be connected to absolutely everything from the kettle to the cat’s litterbox, collecting terabytes of completely useless data. Wired Magazine mentions that the ironic term the Internet of Sh*ts is ever more popular — which basically means the imminent death of ideas, at least in their present-day, gadget-like form.

Big Insights and Data Visualization Based on Context

Everything points to the fact that the coming years will mark the end of the Big Data fetish and the beginning of big insights, which is a critical approach to the data being processed. There will be more and more of this data, and it will be more nuanced. Expanded reality and IoT will bring about the contextualization of data in the real world, which will enable the capture of specific events (our actions, decisions, and behavior) in a particular place and time. This will further blur the boundary between the physical and virtual worlds. The game Pokemon Go is just one such example. This also means that business analytics will need to exceed this limit.

Data analysis must be based on an ever wider context. Otherwise, the company runs the risk of operating in a virtual bubble. A similar phenomenon is now being observed by social networking researchers, who have noticed that their users operate in an environment of friends who are similar to each other, with access to selected information served to them depending on the choices made (the number of likes) and calculated by preference algorithms. This is the so-called filter bubble. Of course, the image of reality which thus arises is false, distorted, and harmful in many respects because it means that our choices influence the shape and content of the information presented to us.

For businesses, this situation is equally dangerous. A company functioning in the business reality created by the paradigm of their own data is on the direct route to being isolated from the expectations of customers, the situation on the market and, of course, to financial disaster. By the way, the business is completely unaware of this danger because, of course, it uses the most modern IT solutions.

The conclusion is obvious. It is not enough to analyze their own data; it is ever more important to confront this data with external data and take that into account in the decision-making process — even if (and perhaps especially) when such data makes us uncomfortable and disturbs our comfortable perspective.

The Democratization of Data Analysis

On the one hand, we must decide what data to collect, but on the other hand, we must learn to read the data. In companies, it will mean the dissemination of tools for business intelligence. What does this mean exactly? Well, access to advanced analytical tools can no longer be reserved exclusively for top-level executives. Access must also be granted to all employees who can more effectively carry out their tasks thanks to the use of data.

Not only that — analytical initiatives (i.e., how and what is to be analyzed) must be bottom-up because every employee knows their area of operation best and knows what data is most useful. An employee also adds his or her own input, a unique perspective, which significantly reduces the risk of enclosing decision-makers in a virtual filter bubble, distorting the image of reality. Companies must develop a new complex ecosystem of data > people > ideas. The IT department must be at the center of this and must be equal to the task in terms of the provision of relevant data and the mechanisms for processing it.

This is obviously a much more complicated task than simply implementing the appropriate Business Intelligence tools. Entrepreneurs should, in fact, change the operation of their businesses and focus on the education (training) of employees in the framework of acquiring, analyzing, and using data on the job. Data analysis will soon cease to be a narrow specialization for IT people only. It will become a key competence of every employee, regardless of his or her position. It will be considered on a par with language skills and the ability to work in a group, without which employment in a modern company is practically impossible.

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Topics:
business intelligence ,data visualization ,data analysis ,big data

Published at DZone with permission of Michal Soja. See the original article here.

Opinions expressed by DZone contributors are their own.

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