Business Analytics vs Data Science

Business Analytics vs Data Science

If you have ever wondered what is the difference between Business Analytics and Data Science and whether they overlap or not, or if they bring different skills and knowledge to organisations, then this article is for you.

Business Analytics Data Science
Concept Use of statistical concepts to extract insights from business data. Business Analytics is vital in management taking key decisions. Interdisciplinary field of data inference, algorithm building and systems to gain insights from data. Data Science analysis results cannot be used in day to day decision making of the company.
Application Financial, technology, mix of fields, CRM/Marketing, Retail Technology, Financial, mix of fields, internet-based, Academic
Language Recommendations Python, R, SAS, Scala, SQL Haskell,  Python, R, SAS, Scala, SQL, Stata (mainly used for academic purpose; not used in industry)
Coding Does not involve much coding. More statistics oriented. Coding is used widely. The field is a combination of traditional analytical practices with sound knowledge of computer science.
Statistics The whole analysis is based on statistical concepts. Statistics is used at the end of the analysis following algorithm building and coding.
Data need Uses predominantly structured data. Uses both structured and unstructured data
Application in industries such as Finance, Technology, CRM/Marketing, Retail,  Healthcare Finance, Technology, Internet-based, Academic
Trends in 2020 and beyond Cognitive Analytics, Tax Analytics Machine Learning and Artificial Intelligence

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