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Data Analytics, Business Analytics and Data Science, though different connotations, has a rather thin line of demarcation between them. Data Analytics is primarily based on massaging & harmonizing the back-end unstructured data of the business; and make them usable and presentable to the business analysts (who in turn would derive insights from them). Key data related tools & technologies such as RDBMS, Hadoop/Hive, SQL etc. are a must for a successful career in data analytics.
Data science relates to the application of mathematical & statistical algorithms to the cleaned data provided by data analysts. These candidates are generally postgraduates in economics, statistics with a flair in data modelling.
Business Analytics requires maximum exposure to business (amongst these three roles) and is primarily responsible in providing a business touch to the technical/mathematical problems being solved by the data analyst or data scientists. An ideal candidate for business analytics should be an MBA-graduate with a stint in business.
hese three terms are relative and a bit confusing. You will get different definition in different place. Lets try to understand it in more concrete terms
Business Analytics: BA is broad term used in industry. Analyzing business and market, defining metrics and KPI, day to day reporting and analysis comes under BA. Anybody with good analytical skills and domain knowledge can become Business Analyst.
Analytics: Analytics is board term, Business Analytics is the subset of Analytics. You need to have all skills that required for BA plus having a good statistical knowledge.
Data Science: It is the parent set of above two. Its include everything- you need to have good business knowledge, Statistical knowledge, having command in different statistical tools (SAS, R, python), good database knowledge, etc.