Getting down to the nitty gritty- BI products that are SQL-centric and optimised for structured data and Big Data sources optimised for unstructured data. Increasing focus by business users to exploit self-service BI makes it difficult to bridge the gap. But there are practical answers such as HP Enterprise's HAF-V with BI & visualisation over Vertica & IDOL (Autonomy) ((structured & unstructured data) And follow link to Logi Analytics & Big Data
The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren’t generally a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using Structured Query Language (SQL). Big data includes large volumes of data that does not fit into rows and columns, such as sensor data, text data and Web log data. Such data must be transformed and modeled before it can fit into paradigms such as SQL. The result .....many organizations run separate systems for big data and BI.