We are currently in the midst of a sea change in the way organizations get their Business Intelligence (BI). It used to be that IT departments would produce the reports that firms asked for, holding all the power themselves with users at their mercy. This evolved as the tools became increasingly accessible, and a rare few users with an understanding of the data and processes, were able to get the BI they were looking for.
Self-service BI is the next step, opening analytics up to all users - even those lacking prior knowledge of SQL - and transferring the power away from IT departments. The self-service BI analytics tools market is growing fast, while demand for traditional dashboard BI is in remission. Such tools allow business users to access pooled data from disparate sources, and interrogate the datasets for the information needed. Business users can then produce new business insights and validate business data requirements to support application development and data management.
There are numerous clear advantages to self-service analytics and the user having more control over the company data. Individuals will find themselves re-evaluating their new role in the company, with real-time ‘what-if’ analyses allowing for data modelling to test ideas as and when is needed. Employees will subsequently be given more license to be creative, and the level of risk attached to their ideas will be lowered.
Data no longer having to go through IT and the various other business departments means lower turnaround times. Lower turnaround times mean that decision-making processes and productivity can be increased. Self-service BI lets business users respond quickly to changes, and lets them ask and answer their own questions, on an individual basis. This means the responses they get can also be far more flexible too, as IT departments create reports for individual questions and users.
All of this is not to say that there isn’t still a lot of knowledge needed by users, as they will still have to ensure that they have clean data to work with. It is also untrue that it is completely self-service, as the data must still be accumulated at some point in such a way as to make sense, which requires somebody with expertise in data and technology.