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 modeling. Business Analytics requires maximum exposure to business (amongst these three roles) and is primarily responsible for 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.