The four types of data analytics are Descriptive, Diagnostic, Predictive, and Prescriptive analytics. Descriptive analytics summarizes historical data to understand changes over time, providing insights into what has happened. Diagnostic analytics delves deeper into finding the reasons behind past outcomes, answering why something occurred.
Predictive analytics uses statistical models and machine learning techniques to forecast future events based on historical data. Prescriptive analytics goes a step further by recommending actions to achieve desired outcomes. Mastering these analytics types is crucial for any data analyst. Enrolling in a comprehensive data analyst course can equip you with these essential skills for a successful career in data analytics.
The four types of data analytics
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Descriptive Analytics: Analyzes historical data to understand what has happened in the past. It provides insights through reports and visualizations.
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Diagnostic Analytics: Identifies the cause of past events by analyzing historical data, helping to understand why something occurred.
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Predictive Analytics: Uses statistical models and machine learning to forecast future outcomes based on historical data and trends.
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Prescriptive Analytics: Recommends actions based on data analysis, suggesting possible outcomes and optimizing decisions to achieve the best result.
These analytics types help organizations make informed decisions.
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The four types of data analytics are descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics helps explain past trends, while diagnostic analytics identifies the causes behind those trends. Predictive analytics uses data to forecast future outcomes, and prescriptive analytics recommends the best actions to take. If you're looking to learn these techniques, a Data Analytics Training Course in Indore, Delhi, Noida, and other locations in India is a great option.
The four types of data analytics are descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics summarizes past data to show "what happened," while diagnostic analytics explains "why it happened." Predictive analytics forecasts future outcomes using historical data, and prescriptive analytics suggests actions based on insights and optimization. These types help businesses turn data into actionable insights.
The four types of data analytics are:
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Descriptive Analytics
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Purpose: Answers “What happened?”
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Example: Monthly sales reports, website traffic summaries.
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Use: Summarizes past data to identify trends and patterns.
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Diagnostic Analytics
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Purpose: Answers “Why did it happen?”
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Example: Investigating a sudden drop in website visits.
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Use: Digs deeper into data to find causes or correlations using techniques like drill-down, data discovery, or data mining.
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Predictive Analytics
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Purpose: Answers “What is likely to happen?”
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Example: Forecasting next month’s sales or predicting customer churn.
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Use: Uses statistical models and machine learning to forecast future outcomes based on historical data.
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Prescriptive Analytics
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Purpose: Answers “What should we do?”
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Example: Recommending the best pricing strategy to maximize profit.
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Use: Suggests actions or decisions by evaluating different scenarios using optimization and simulation.
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Each type builds on the previous one, progressing from understanding the past to guiding future decisions. Thank you so much for sharing this information.