The process of collecting, segregating, utilizing, and analyzing business data, and using statistical models and iterative methodologies to transform the complete data into business insights is popularly known as Business Analytics. The primary goal of business analytics is to determine which datasets are useful and how these datasets can be leveraged to solve occurring issues and increase efficiency, productivity, and overall revenue.
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Components of Business Analytics
Data Aggregation
Collecting data is the first step to analytics. Before one can analyze data, it must be collected, segregated, and cleaned to avoid the duplicity, and also filtered to eradicate inaccurate, incomplete, and raw data. Data can be aggregated either from transactional records or volunteered records of any domain.
Data Mining
Data mining helps data experts search and identify unrecognized patterns and industry-relevant trends. Numerous models can be created with data mining. This practice employs several statistical techniques to achieve clarification, regression, and clustering of data.
In most of the cases, consumers perform similar or predictable actions sequentially, which can be easily revealed if the data is utilized effectively.
Text Mining
Social media plays a vital role in Business Analytics. One can also collect textual information from different social media channels including blog comments and various call center scripts to extract meaningful data. This data can be utilized by experts to improvise customer service.
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