We have seen since many years how traditional Business Intelligence solutions have served industries for better decision making, especially the growth of analytics, both from the analysis and visualization point of view. Let us ask an honest question to ourselves: “Is this is enough in today’s business context across industries?” The answer is that it may be helpful, but only to a certain extent. The traditional enterprise data warehouse can store transactional information captured from multiple systems, including Excel/flat files that have some structure/pattern. An analytical model can be created with or without an OLAP layer to provide rich analytics in terms of dashboards and reports. Mining models can be created and integrated with a data warehouse or OLAP layer to build predictive analytics. At the end, the target audience should be able to find out ‘What’, ‘When’, ‘How’, ‘Where’ and ‘What may (will)’ with respect to their business.
The Independent Software Vendors (ISVs) belonging to various industries have built their products and solutions along with Business Intelligence modules to provide better insights of the business processes. However, these insights are limited to the information that has been captured through the software that is structured.
The giant leap of information technology in terms of storing vast amounts of non-transactional, unstructured business data and capturing it from disparate sources has paved the way for a new generation of Business Intelligence technologies. The usage of ‘Hadoop’ as a Big Data platform either in addition to enterprise data warehouse or as substitute has started to rise. The key drivers for this paradigm shift are:
The new technologies help in ‘Enhanced Data Management’, ‘New Deployment Options’ and ‘Advanced Analytics’ for ISVs to make their software products suitable for today’s business needs. This is the game changer for Independent Software Vendors (ISVs). Usually, in the Healthcare, Retail and e-commerce space, the applications have progressed by leaps and bounds. A few of the top 5 use cases which can be applicable for ISVs across industries are as below:
In this new era of SMAC, the data is generated through either sensors, systems, machines, mobiles, web logs or interactions through social media. This data is unstructured, voluminous, varied and yet critical when combined & analyzed with structured data captured through traditional systems. Now let us see and understand how each area of Business Intelligence has undergone a transformation:
If we try to put all these pieces together, the new eco system of Business Intelligence looks like:
Let us detail the highlighted boxes:
This way the paradigm shift has taken place in Business Intelligence and is creating a dire need for ISVs to modernize, build their software products and applications with above capabilities. The ISVs that have sensed this and have started implementing the change/modernizing their products are bound to have a competitive advantage.
The rise of Cloud and Disrupting the BI / DW ecosystem
Business Intelligence analytics tools and BI analytics are ushering in a new age of business. Combined with mobile BI and open source BI tools, the BI market will surely surge ahead.
The ISVs have already realized the potential of cloud, and moved their software and applications there by offering SaaS based services to the customers. The next big question in their mind is: “Can a Business Intelligence module can be moved there?” This has its own advantages and apparent challenges that can be addressed. This has given rise to ‘AaaS – Analytics As a Service’. We shall talk in detail about his in the next blog…
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