This has long been a subject of mystery in the Big Data and Business Intelligence (BI) industry.  How can you apply User Experience Design to Big Data?  How can it be quantified?

Almost all applications are created for a specific purpose.  Openoffice, Microsoft Office and other similar programs are for creating different kinds of documents or working with numbers.  Applications today allow you partial integration with other applications.  Even so, they are simply software applications with fairly obvious demarcation lines.

Quantifying Big Data with User Experience

What happens is that organisations use applications like Microsoft Excel to attempt to expose the needed information to make the right BI decision.  Excel is fit for purpose you may say – years ago it was I agree.  The problem today, however, is that the landscape of Big Data has changed.  Users want to discover nuances within and interact with their datasets.  They want business questions answered and others to be revealed because of the answers they get.  To do this requires more than an Office productivity tool.  It requires a heightened User Experience.

Today’s BI landscape screams for data visualisation, discovery and exploration. Yes, we are talking Matthew Henson or the Christopher Columbus type of exploration.  Today few organisations have caught on but not all realise that the process of visualising your data doesn’t have to be a complex one.  Companies such as Qlik, Logi, Think Big have made sure that statement is confirmed.

Quantifying Big Data with User Experience

How this is achieved is by simply improving the Users Experience of dabbling with their data.  Looking at their data from different angles to reveal information they never were able to match up with some of the most elusive business questions that went unsolved within their organisations.

The key is using the K.I.S.S approach – Keep it Simple Stupid.  Answer the key questions the user (or user groups) are asking.  You have to be strict in employing a UCD (User Centred Design) approach.  The user is always the most important.  It doesn’t matter what you think is “nice” or “good” or what “cool” things you can do with their data or the User Interface (UI) that the data lives within.  As long as the design best benefits the main users who will use the application then you’ve won in short.

Sure there are key stakeholders who must be catered for to their satisfaction as well.  If you’re a good User Experience professional ensuring everyone wins (subplot) is achievable, whilst still making sure the main groups of users get first “dibs” as it were on being satisfied users.

There is no bad car – it depends on the user

Using the K.I.S.S approach also means when designing the User Interface, this has to help enable the users to quickly access their data, understand their data and help them to make the correct decisions based on their data.  If the design of the UI is too complex then it only detracts from the data itself.  So an easy in and easy out approach, in short, is best.

The data has to tell the right story.  OVOTT (One Version of the Truth).  The true version.  This is where aligning the presentation of data to create the best story regardless of what conclusions the user draws is key to the success of Quantifying User Experience with Big Data.

If you’re in the process of considering a modern BI discovery tool, one that is Interactive, flexes around your data and helps you to answer your questions around your data so far from my in-depth usage of several ‘modern’ BI tools, only Qlik provides a truly responsive solution that can do all the above and embraces User Experience in ways not seen before on the BI landscape.

But that is from my own experience. There are many other companies out there that offer good solutions.

Don’t take my word for it, do your own research.

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