Business intelligence initially evolved from the legacy decision support system (DSS) which began in the 1960s. DSS originated from computer-aided models that were created to assist with decision making and planning. Data analytics was initially based on statistics, statistics was marked to have originated in Egypt for building pyramids. Then governments across the world were collecting large amounts of data which brought to the next step of that is collecting and analyzing data, as there were advances in computing technology like relational databases and data warehousing this is where data analytics came into light. Implementation
Business intelligence is what drives any business and has been implemented across many organizations throughout the world. It consists of analyzing data, performing data mining, drive decision-making capabilities. Although there are some Business intelligence roles were it consists of data cleaning from various sources, data forecasting, predictive analytics, and prescriptive analysis. Data analytics focuses more on implementation for storage, recovery, and warehousing of data. Some of the tools that are available for data analytics in Microsoft are SQL Server Integration Package, Python for utilities, Azure Integration services, etc. Commonality Business Intelligence and data analytics is applied only at a stage where the company has enough data. Real-world Example: Reporting in business intelligence is a key feature and there are many tools that help for reporting needs. In order to understand how business intelligence and data analytics work lets take a real-world scenario an example: An eCommerce company's marketing team wants to understand their sales based on region and they also want the age group of purchase for a product X. The business requests the Business Intelligence team to give them a report or a dashboard. Then a business intelligence analyst needs to pull all the data based on the region for a product X and where does this data come from? This data has to be staged in a database that is were a Data Analyst collects all the incoming data from various systems that the eCommerce company uses and makes it more presentable to the business intelligence team. Then the business intelligence analyst takes this data and does some analysis using tools like PowerBI or Tableau makes the data more actionable and presents it to the business.