Data science is basically a field in which information and knowledge are extracted from the data by using various scientific methods, algorithms, and processes. It can thus be defined as a combination of various mathematical tools, algorithms, statistics, and machine learning techniques which are thus used to find the hidden patterns and insights from the data which helps in the decision making process. Data science deals with both structured as well as unstructured data. It is related to both data mining and big data. Data science involves studying the historic trends and thus using its conclusions to redefine present trends and also predict future trends.
Business intelligence(BI) is basically a set of technologies, applications, and processes that are used by enterprises for business data analysis. It is basically used for the conversion of raw data into meaningful information which is thus used for business decision making and profitable actions. It deals with the analysis of structured and sometimes unstructured data which paves the way for new and profitable business opportunities. It supports decision making based on facts rather than assumption-based decision making. Thus it has a direct impact on the business decisions of an enterprise. Business intelligence tools enhance the chances of an enterprise to enter a new market as well as help in studying the impact of marketing efforts.
Below is a table of differences between Data Science and Business Intelligence:
|Factor||Data Science||Business Intelligence|
|Concept||It is a field that uses mathematics, statistics and various other tools to discover the hidden patterns in the data.||It is basically a set of technologies, applications and processes that are used by the enterprises for business data analysis.|
|Focus||It focuses on the future.||It focuses the past and present.|
|Data||It deals with both structured as well as unstructured data.||It mainly deals only with structured data.|
|Flexibility||Data science is much more flexible as data sources can be added as per requirement.||It is less flexible as in case of business intelligence data sources need to be pre-planned.|
|Method||It makes the use of scientific method.||It makes the use of analytic method.|
|Complexity||It has a higher complexity in comparison to business intelligence.||It is much simpler when compared to data science.|
|Expertise||It’s expertise is data scientist.||It’s expertise is business user.|
|Questions||It deals with the questions what will happen and what if.||It deals with the question what happened.|
|Tools||It’s tools are SAS, BigML, MATLAB, Excel etc.||It’s tools are InsightSquared Sales Analytics, Klipfolio, ThoughtSpot, Cyfe, TIBCO Spotfire etc.|
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