Business Intelligence over the period of time has reshaped itself from being a tool to create reports, to a system which can help business understand its key drivers and make their strategic decisions.
Changing face of BI
Organizations have started using Business Intelligence as a tool to support Decision Engineering. To adapt to this new role BI tools are undergoing a series of evolutions. The expectation from the BI tools are increasingly larger now. Decision makers are expecting the Business Intelligence systems to answer each and every business questions. And this requires the BI systems to have a control over each and every section of the business. Through this process the organization wants to move away from those in silos decision making habits to an Institutionalized Decision Support Systems.
Transforming Data Integration
To transform itself into an Institutionalized Decision Support System the BI system needs to mark its presence in every section of the business. And for that it is required to have all elements of information on a single plate. The requirement for the BI tools is to imbibe in itself every piece of data which is getting generated in the organization instantly and irrespective of its variety and source, to enable the quick decision making process. So that the business can have a single source of truth on which it can make its strategic decisions.
Business requirement from the BI reports or Dashboards were not only to get the small and specific business insights but to get support while making large scale strategic future decisions. And to cater to this requirement the Business Intelligence systems needed the capabilities to build or discover the co-ordination among the different sources of data pertaining to different section and different users of the business.
So Data Integration became the primary focus of the BI tools. And with the rise of the different types of data along with the different databases the ability for the BI tools to connect with the leading data storage tools becomes inevitable.
The ease of connectivity to the different databases became the primary parameter for any organization while selecting the BI vendor for its business. Now the organizations have started harnessing the big data with the advent of tools like Hadoop and Teradata. The BI tools are coming up with new technologies to handle the huge amount of structured and unstructured data coming with high velocity and to allow data mining on them to gain insights and to predict the future consumer behavioural patterns and many other insights from these data.
As Business Intelligence systems has started to play a key role in the Decision Support Systems of the organizations. It has to take care of the changing business process and the ever changing business questions it needs to answer. So it becomes increasingly important for the BI Vendors to make the architecture of their tools such that the tools are agile enough to take into considerations the change in the business processes and requirements with minimal effort.
In Memory Analytics
While focusing on giving the connectivity options to a diverse range of databases, some of the BI vendors also focused on implementing the In-memory data holding capability of the tool. The key features of the In-memory Databases are:-
It allowed to leverage the power of the tool instead of databases to get quick responses from the system.
Helped in increasing the user interactivity with the developed reports or dashboards as the response time was much faster.
And at the same time it also allowed to avoid the large scale implementation of the OLAP Cubes and pre-defined aggregations in the data systems.
Scalability and Web and Mobile Access
And with the growth of BI from the small medium term decision assistance tool to a large scale Institutionalized Strategic Decision Support System, the need for scalability and sharing of the required information on real time with the key business stakeholders started gaining importance. Features like online sharing of the dashboards, ad-hoc reporting and at the same time the need for offline analysis also became the key requirements. Now as the in-memory BI tool holds the data in itself, they were used for offline analysis of the reports and there vendors gained a competitive advantage over the others. The BI tools also came up with Server- Client architecture which allowed end-users access to the reports or dashboards lying on the web through Mobile and Desktop devices. It enabled decision making anytime and anywhere.
BI and Analytics
The evolution of the Business Intelligence to be a Strategic Decision Support System was not complete without the use of analytics. So the journey which started from investigating the historical data now is reaching to the milestone of doing advanced analytics on them. Techniques like Predictive analytics and Data mining started falling under the purview of Business Intelligence. And with this expectation from the market the BI tools started to incorporate in itself the statistical algorithms to allow the end user to do advanced analytics on the available data and to help the decision making body of the organization see the forecast and the trends of the business KPIs. Tools like Tableau is stressing on the integration of statistical languages like R and adding features like Trend lines, Forecasting in its newer versions.
Now along with this evolution of the BI tools it was also necessary to scale up the user base for the BI applications. And with that came the shift from On-Premise BI systems to Cloud based BI applications which can offer easy deployment, ease of use and cheaper scalability in terms of end users for an application. Even the smaller businesses having very less IT budgets can now afford to use the services of Business Intelligence on cloud. Over the last few years a significant percentage of businesses have moved their BI applications to cloud and the trend is still on rise.
There has been a Paradigm shift in the way organizations are looking towards their Business Intelligence systems. The responsibility of BI vendors and the organizational Business Intelligence capability is not only limited to generation of reports and addressing the medium term issues. But it has a much important role to play in bringing the co-ordination among the different segments of the business. This can be achieved by integrating data from all the disparate sources of the organization irrespective of its variety, velocity and volume. And allowing the key decision makers to have a common platform in terms of dashboards or reports to analyse the health of the business. The platform should be capable of performing advanced analytics in terms of Predictive analytics and forecasting on the data so as to help the end user in taking strategic decisions regarding the business processes. The system should be scalable enough, so that the actionable insights generated from it can reach to maximum number of users in an easy and cost effective manner.