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Types of Analytics:

Modern analytics can be performed in four ways: Descriptive, Diagnostic, Prescriptive and Predictive

What is Descriptive Analytics (What Happened?)? 

Describing your current event through data is descriptive analytics. This helps us to understand what has happened in the business.  

Examples:   

  • Reports and Visualization in every domain, trend detection, performance monitoring.
  • Supply Chain Reports: Understanding your current inventory status, how many are in-stock, Out of Stock or Over Stocked. 
  • Financial reports: P&L statements, Income statement, Cash flows of company.   
  • Sales reports: Number of orders are returned, number of customers in a given month. 

Specialists:  

  • Data/Business Analyst 

What is Diagnostic Analytics (‘Findings / Why did it happen?’)?

Diagnose patterns and behaviour of data so as to find why something has happened. This helps to diagnose the reasons of failure or success of a company.  

Examples: 

  • Supply Chain report: Discovering reasons for shortage of In-stock, Out of Stock or Over Stocked.  
  • Product report: Identifying why Product Delivery is late, reasons of decrease in price.  
  • Sales report: Identifying reasons for order returns, customer preferences, discovering patterns of customer behaviour.  

Specialists:  

  • Data/Business Analyst
  • Data Engineer 
  • Data Scientist 

What is Predictive Analytics (‘What will Happen ?)?

Forecasts what will happen in the future using machine learning techniques.  

Examples: 

  • Supply chain: Predicting Out of Stock products for next week/month/quarter/year using statistics algorithms. 
  • Sales Analysis: Predict order volume of different products for next month, identifying number of customers who are likely to churn, fraud detection, predict demand.  

Specialists: 

  • Data/Business Analyst 
  • Data scientist 
  • (Big) Data Architect 
  • (Big) Data Engineer 
  • ML Engineer 

What is Prescriptive Analytics (‘How can we make it happen?’)?

Prescriptive analytics is the process of determining the course of action for the next events happening after predicting the future depending upon the data.   

  • Examples: 
  • Supply chain optimization  
  • YouTube suggestions 
  • Chat bots  
  • Digital assistance 
  • Credit risk Management 
  • Optimization recommendation 

Specialists: 

  • Data scientists 
  • (Big) Data architect 
  • (Big) Data Engineer 
  • Chief Data Analyst 

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