BI City

Take a look at what predictive modelling is, how different it is from traditional business intelligence, what are the industry trends around the mathematical/statistical side of it and how it is being supported from a systems perspective.
The predominant single point of failure for most BI initiatives is the lack of good and timely data. Take a look at a back to basics overview of what enterprise leaders and architects should focus on to make themselves ready for the journey ahead.
As business needs evolve and technology landscapes change, it becomes imperative for today's BI/IM professionals to adopt and adapt. Here is an overview of how BI/IM professionals can leverage the technology evolution and innovation to become successful in their spheres of work.
Look at the key steps that will help you tackle the "Big" data challenge keeping all enterprise challenges in mind. Right from having the right technology at the database end to store the unstructured data to having the correct set of tools that enable valuable analytics to be performed over it.
Information Management is standing at the cusp of next generation BI, which will have Social Data , Real time analytics , Visualization, Big Data etc. Look at Why, What and How we can integrate social data into our BI systems and provide holistic information to the business to take informed decision.
Any enterprise has 6 mutually exclusive, collectively exhaustive (MECE) types of organizational data, which are: Transaction Structure Data, Enterprise Structure Data, Reference Data, Transaction Activity Data, Metadata and Audit Data.
Business Intelligence is the leveraging of Data Warehouse to help make business decisions. Since SuperValu  is a company built through acquisition of various banner brands,  they walked in to a situation of having to face a unique challenges of multiple customer, sales and financials, hosted data models or data warehouses. But not all of them were categorizing the information in the same manner and SuperValu was left with data not being in sync with each other.
The key components of the any project are Technical Constraints, Functional Constraints and Commercial Constraints. These components are critical in any project but their coupling is of far greater relevance in Business Intelligence/Data Warehouse Implementations.
Business Intelligence Programs often fail to make business impact for the reasons such as: BI is seen as disconnected from the organizational processes, BI still not seen as delivering enough business impact, many organizations still not get “analytics” and BI Organization is seen as not being able to innovate.  
One of the influencers of BI trends is Cloud Computing. Cloud Computing emerged from the web 2.0 movement. In a nutshell,it covers the concept of having internet accessible and always available resources ‘in the clouds’, so that the physical location of a user or device becomes irrelevent.
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