Data analytics has become integral to businesses – big or small, sometimes resulting in uncovering of new revenue streams. AI and machine learning have made analytics more accessible and affordable. Smaller companies who might not be able to afford to hire a ‘data specialist’ can now choose from a variety of free and paid for tools that can perform advanced analytics using multiple data sets – owned or otherwise.
Analytics is no longer about cumbersome spreadsheets or uninspiring charts. Visualisation techniques are used to bring data to life for better/easier comprehension. Data monetisation is also emerging as a key trend with businesses ability to store large amount of data using cloud services.
Business Intelligence overall has moved from an ‘experts service’ to ‘self-service’ model and the latter has further evolved with AI/ML. These technologies have made business intelligence more transparent and trusted. Natural language processing is further simplifying the analytics platforms for the users by allowing more flexibility on the queries. ‘Citizen data scientists’ (those who perform analysis using automated tools without necessarily being data/analytics experts – source Gartner) are expected to be common place across industries and data skills will be a basic requirement for any role.
IBM lists out 5 steps to train employees become ‘citizen data scientists’: