There is often confusion about the difference between Big Data analytics and Business Intelligence, but there are clear differences between the two. On this page we explain some of these differences. Do you want to know more about which approach is best suited to your organization? Feel free to contact us Contact with us. We are happy to help you find the right solutions.

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 distill the necessary information from the data warehouse.

Most BI environments work according to the ETL principle. This stands for extract, transform and load. In BI, the information requirement is known and a solution is built that can meet this information requirement. 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 term that you probably encounter regularly. There are different definitions, 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 examine the data and gain new insights. The basis of a Big Data solution is in many cases 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.