The term Business Intelligence (BI) easily confused with some related processes. These include data analytics, big data and data science. Business Intelligence or SQL Business Intelligence (BI) helps users derive actionable intelligence/information from analyzing available data through software tools. These tools, Business Intelligence software, help business managers take better decisions. Sometimes, these insights can provide a completely new business decision or tactic that would not have been obvious otherwise. These tools came as an improvement of the decision support systems that were in widespread use in the sixties to the eighties.

The BI tools need to operate on data derived externally, for example about the products of the business and their behavior in the market (both own and competitors’). Data, internal to the company, such as financial and operations data are useful for analysis and derivation of the business insights. Often about 80% of the data in the business intelligence domain can be unstructured and the tools should be able to analyze them with ease. These SQL Business Intelligence (BI) tools let you discover relations between the available data and help drive the decision making through these insights developed. Strategic decisions would typically include identifying the way forward for a business and long-term goals while tactical decision making would cover such operational issues like determining pricing and market position of the company product. The following formal definition of BI is attributed to Howard Dresner. He defines Business Intelligence as “concepts and methods to improve business decision making by using fact-based support systems.” The concepts and tools are usually lumped together as analytics or data analytics in the SQL Server BI tools available in the market.

The features available in order of higher business value delivered by these Business Intelligence (BI) tools include a set of reporting functions at the bottom of the pyramid. These just provide business owners with reports that indicate what happened to the business during a given period. Analysis functions on top of these reporting tools describe reasons behind these happenings. These and part of the next level function, described as monitoring (of current events), are supported by basic statistical functions in the SQL Business Intelligence (BI) product offerings. Next level of outcomes from the system would support forecasting functions. Regression analysis techniques are useful here.

Predictive functions of the SQL Server BI tools attempt to predict the directions the analyzed data will likely change. Possible actions are often part of the business intelligence repertoire at the next level of reporting. These techniques need support of “what if” kind of simulation tool in the BI tool.

With bigger businesses one needs to handle a huge amount of data. Managing techniques of handling such large body of data is called “big data”. As the needs of analyzing and discovering trends and patterns grow, the sophisticated needs of analysis can only be met by customized set of tools. No amount of standardized tools available with the Business Intelligence (BI) products may be sufficient. What such customized analysis should be, get decided by the characteristics of the data involved and the science behind analyzing such large data. That is the domain of data science and the persons trained in these techniques are the data scientists.