273539_l_srgb_s_glLet’s be honest. If you haven’t yet jumped on the train of self-service business analytics, you’re a bit late. Actually, you’re not only late, you’re potentially at the point of losing your audience by not meeting their requirement for insight on your company’s performance. You might be thinking… that’s some statement, how come?

Digital transformation is rapidly changing our world. Networks and devices are connecting simultaneously at staggering speeds. As a result data is exploding, and becoming bigger and more complex. Without a constructive way to show correlations, dependencies, and trends, companies are collecting tons of data without the capability to create actionable insights. This is where self-service business analytics comes in.

Let Me Explain

As an outcome of digital transformation we recognize some key changes in the way business analysts need to cope with having full insight into their organization:

  • More data from more devices increases volume and with that is a more complex structure
  • Data sources aren’t static anymore – sources vary and change constantly
  • Business analysts require making actionable insights online. Supplier and customer behavior is highly dynamic and requires a quick response
  • There is pressure outside of Information Technology to bring actionable insight to the place where it belongs – the business users

Self-service analytics tools answer the above challenges by facilitating easy access to data sources and provide agile techniques for visualizations and analyses. While respecting the lowest adoption levels, the tools are made for business users to given them limitless ways to explore data and their story telling capabilities.

But is it enough? Not if we believe the global providers of market intelligence like IDC. Today’s analysts require more from their self-service tools:

  • Let me interact; interaction is everything

As we saw earlier, analysts need to quickly correlate data and find trends and dependencies. This means they require changing, editing, and manipulating visualizations constantly. It requires tools that have a high degree of interactivity between the user and visualization. Drill down, drill anywhere, filter, and animate. Bring visualizations together in a story and have control boxes to navigate. Share your results with the world at your fingertips.

  • What’s the best that could happen

Digital transformation also affects the “known vs unknown” spectrum. More data, and data with new correlations, means uncertainty in actionable insights. Users want to know “what could happen” if insights are actioned upon. Meaning we require predictive algorithms in our self-service tools. Algorithms, like decision trees, that either forecast or simulate what could happen in pre-defined circumstances.

  • Let me blend

With the variety of sources and their structure changing constantly, the analyst – bear in mind they’re business users and not IT people – needs to cope with data integration issues. These sources will not always respect “traditional database integration rules” for joining tables, and so on. To allow for the correlation insights, the analysts need to be able to blend data. Blending is a technique to interrelate data even though technically they can’t be joined. The technique is innovative in the sense that in all circumstances the correct outcome needs to be guaranteed while respecting the limited IT knowledge analysts might have.

Interactivity, blending, and predictive capabilities of self-service tools will be key trends for the next year. They’ll separate the wheat from the chaff in the BI landscape. Exciting times ahead!