Data Analytics

   Converts raw data into actionable insights

Data & information

Collection of data

Organization of data

Presentation of data

Analysis of data

Data Analysis

• Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making.

• The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis.

Types

1. Descriptive Analytics:

   • Objective: Describes what has happened in the past.
   • Focus: Summarizes and provides an overview of historical data.
   • Methods: Aggregation, summarization, and data visualization.
   • Example: Generating reports on monthly sales, summarizing website traffic, or creating dashboards displaying key performance indicators (KPIs).

2. Diagnostic Analytics:

   • Objective: Examines past data to understand why a certain event happened.
   • Focus: Identifying patterns, correlations, and relationships.
   • Methods: Drill-down, data mining, and correlation analysis.
   • Example: Investigating the reasons behind a sudden spike or drop in sales, analyzing the factors contributing to customer churn, or identifying the root causes of production issues.

3. Predictive Analytics:

   • Objective: Predicts future outcomes or trends based on historical data.
   • Focus: Forecasting and making predictions.
   • Methods: Statistical models, machine learning algorithms, and time-series analysis.
   • Example: Forecasting future sales based on historical data, predicting equipment failures in a manufacturing plant, or estimating the likelihood of a customer making a purchase.

4. Prescriptive Analytics:

   • Objective: Recommends actions to optimize a particular outcome.
   • Focus: Providing advice on what actions to take to achieve desired results.
   • Methods: Optimization algorithms, simulation, and decision analysis.
   • Example: Recommending optimal pricing strategies for products, suggesting personalized marketing approaches for different customer segments, or advising on inventory levels to minimize stockouts.

Methods

Pandas

Numpy

matplotlib

Seaborn

Scikit-learn

Pandasql

Data Analytics Using Pandas

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