There is often confusion about the difference between Big Data analysis and Business Intelligence, but there are clear distinctions between the two. On this page, we explain some of these differences. Would you like to find out more about which approach would best suit your organisation? Please feel free to Contact Get in touch with us. We're happy to help you find the right solutions.

Business Intelligence originated in the 1990s. The demand for management reports from available data grew steadily. 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 operate according to the ETL principle. This stands for extract, transform and load. In BI, the information requirement is known and a solution has been 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 analyse large and complex datasets. Big Data is a term you will likely encounter regularly. Various definitions exist, but the most commonly used is that of Gartner: “Big Data is information of extreme size, diversity and complexity and is everywhere.” Big Data solutions often work with large datasets 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 gain new insights. The basis of a Big Data solution is often not a database but a file system. The best-known and most used is Hadoop. This is an open-source system where data can be imported.

The overview below shows the main differences.