Because of the importance of data analysis to businesses, a host of job positions are available for those with a … It is a multi-disciplinary field that uses mathematics, statistics, AI, ML, computer science, and information science to extract insights from structured as well as unstructured data. However, it can be confusing to differentiate between data analytics and data science. I’ll try to keep it simple. Data Science vs Business Analytics, often used interchangeably, are very different domains. But there’s one indisputable fact – both industries are undergoing skyrocket growth. It is this buzz word that many have tried to define with varying success. Differences Between Data Analytics vs Business Analytics. Both Data Science and Business Analytics involve data gathering, modeling and insight gathering. Mostly the part that uses complex mathematical, statistical, and programming tools. Data Analytics is more technical centric than the other in terms of technical skillset as a data analyst would be doing hands-on data cleaning, data purging, finding correlations etc. MS Business (or Data) Analytics – Overview & Case Studies Course Curriculum of MS Business Analytics at Top Universities . You can solve complex data related problems and possess the ability to automate your solution. The difference between the two is that Business Analytics is specific to business-related problems like cost, profit, etc. Data analysts examine large data sets to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions. Data science is a discipline reliant on data availability, at the same time, business analytics does not completely rely on data; be that as it may, data science incorporates part of data analytics. Now, let us move to applications of Data Science, Big Data, and Data Analytics. Applications of Data Science. A layman would probably be least bothered with this interchangeability, but professionals need to use these terms correctly as the impact on the business is large and direct. Business Analytics: Data Science: It uses statistical and mathematical concepts and methods to extract information from structured data. Here is a post by Srinivas Osuri, an alum of the MS Business Analytics program at the Carlson School of Management in the University of Minnesota, and currently employed at McKinsey on what you can expect from a Master’s in Business Analytics program. Data Analytics vs. Data Science While data analysts and data scientists both work with data, the main difference lies in what they do with it. Differences Between Data Analytics vs Business Analytics. Data Analytics is more technical centric than the other in terms of technical skillset as a data analyst would be doing hands-on data cleaning, data purging, finding correlations etc. Today, the current market size for business analytics is $67 Billion and for data science, $38 billion. It is an interdisciplinary field that works towards decoding and demystifying large datasets namely the big data by making use of a combination of maths, statistics, information science, computer science, machine learning, data analysis, and other related fields of study. Internet Search What is Data Science? Business Analytics vs Data Analytics vs Data Science. Looking at data science vs data analytics in more depth, one element that sets the two disciplines apart is the skills or knowledge required to deliver successful results. To differentiate business analytics from data science, know about data science. Looking at data science vs data analytics in more depth, one element that sets the two disciplines apart is the skills or knowledge required to deliver successful results.

The focus of Data Analytics lies in inference, which is the process of deriving conclusions that are solely based on what the researcher already knows.