There is a lot of uncertainty between Big Data Analysis and Business Intelligence. However, there are clear differences. On this page we list some of the differences. If you want to know more about the differences between Big Data vs Business Intelligence you can: Contact record with us. We can then explain to you what the different applications can be within your organization.

Business Intelligence originated in the 1990s. The demand for management reports from available data was increasing at that time. BI is primarily intended for creating reports with management information. Data from databases is loaded into a special data warehouse. Standard reports then distil the necessary information from the data warehouse.

Most BI environments work according to the ETL principle. This stands for extraction, transformation and loading. At BI, the information need is known and a solution has been built that can meet this information need. The implementation of a BI environment is usually complex and can take a long time.

big data Analysis arose from the need to analyze large and complex data sets. Big Data is a concept that you probably come across on a regular basis. There are several definitions of it, but the most commonly used is Gartner's: "Big Data is information of extreme size, diversity and complexity and is everywhere." Big Data solutions often work with large data sets and can handle both structured and unstructured data.

The goal is often not to generate a report within a second, but to investigate the data and thus gain new insights. In many cases, the basis of a Big Data solution is not a database but a file system. The best known and most used is Hadoop† This is an open source system where the data can be loaded.

The overview below shows the main differences.