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Major Aspects of Business Analytics
that Every Manager should
understand
Overviews
Techniques of business analytics break down into two main areas.
1. Basic business intelligence: This involves examining historical data to understand how a
business department, team or employee has performed over a certain period of time.
2. Deeper statistical analysis: It is the second area of business analysis. This can mean
predictive analyses using statistical algorithms on historical data to predict the future
performance of any product, service or website design. Or, other advanced analytical
techniques, such as cluster analysis, could be used to group customers based on similarities
across several data points. This can help in targeted campaigns for marketing.
1. Data Mining:
The key objective of data mining is to provide practical
recommendations based on huge amount of information.
2. Correlation Analysis:
This technique allows two separate variables to be compared
to determine whether they have a relationship.
3. Factor Analysis:
This technique is generally used to compare a large number of
variables instead of only two.
4. Meta-Analysis:
Meta-analysis means research on previously conducted studies
on an issue. This approach saves time as well as money in
conducting original statistical investigations.
Key Features
Key Features
5. Regression Analysis:
This technique involves investigating whether a
variable has a significant effect on another.
6. Experimental Design:
Analytics are used in this field to check the validity of
a strategic business plan. This approach can
determine if the change improved productivity, saved
money or improved product or service quality.
7. Linear Optimization:
This technique helps organizations to reduce
information from big data sets by transforming them
into a series of actionable steps.
Thank You
Brainware University

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Business analytics

  • 1. Major Aspects of Business Analytics that Every Manager should understand
  • 2. Overviews Techniques of business analytics break down into two main areas. 1. Basic business intelligence: This involves examining historical data to understand how a business department, team or employee has performed over a certain period of time. 2. Deeper statistical analysis: It is the second area of business analysis. This can mean predictive analyses using statistical algorithms on historical data to predict the future performance of any product, service or website design. Or, other advanced analytical techniques, such as cluster analysis, could be used to group customers based on similarities across several data points. This can help in targeted campaigns for marketing.
  • 3. 1. Data Mining: The key objective of data mining is to provide practical recommendations based on huge amount of information. 2. Correlation Analysis: This technique allows two separate variables to be compared to determine whether they have a relationship. 3. Factor Analysis: This technique is generally used to compare a large number of variables instead of only two. 4. Meta-Analysis: Meta-analysis means research on previously conducted studies on an issue. This approach saves time as well as money in conducting original statistical investigations. Key Features
  • 4. Key Features 5. Regression Analysis: This technique involves investigating whether a variable has a significant effect on another. 6. Experimental Design: Analytics are used in this field to check the validity of a strategic business plan. This approach can determine if the change improved productivity, saved money or improved product or service quality. 7. Linear Optimization: This technique helps organizations to reduce information from big data sets by transforming them into a series of actionable steps.