Data science is different from business intelligence.
Data science is the technology and business intelligence is the application. There can be several technologies used to build business intelligence applications, “data science” being one of those technologies. Similarly, there can be several other applications of data science technologies, “business intelligence” being one of them.
Business Intelligence solutions are used by large organizations who have grown significantly, to an extent that it is not possible to keep control on their business without managing their data effectively. They typically build large enterprise data warehouses to ensure that their data is well integrated and trustworthy. This involves the complex job of consolidating data from various IT systems that were built to facilitate business, including many old legacy systems that were built overtime to store and process data.
The applications of data science technologies can be very different. For example, identifying a spam email is a data science application, and has nothing to do with business intelligence. A self driving car uses data science technologies to process huge amounts of data, and machine learning algorithms, but has nothing to do with business intelligence.
One area of slight overlap is around data mining, where the use cases are somewhat similar. Here data science technologies are typically used to identify data related use cases in a ‘data labs’ environment, and then handed over to the business intelligence teams to build the necessary data foundation for building proper engineering solutions.