Best Data Analytics training in Chennai

Module 1: Introduction to Data Analytics

• What is data analytics?

• Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive

• Analytics lifecycle

• Role of a data analyst

• Tools overview: Python, SQL, Tableau

• Data formats and types

Module 2: Python Basics for Data Analysis

• Setting up Python (Anaconda, Jupyter Notebooks)

• Variables, data types, input/output

• Control structures: if, for, while

• Functions and loops

• Working with packages (pip, conda)

Module 3: Data Manipulation with Pandas and NumPy

• Introduction to NumPy arrays and operations

• Creating and using Pandas Series and DataFrames

• Reading data from CSV, Excel, JSON

• Filtering, sorting, indexing

• Handling missing data

• Grouping and aggregation

Module 4: Data Visualization with Matplotlib and Seaborn

• Introduction to data visualization

• Line, bar, scatter, pie charts with matplotlib

• Heatmaps, pairplots, boxplots with seaborn

• Customizing plots: titles, labels, colors

• Exporting charts

Module 5: Exploratory Data Analysis (EDA)

• Understanding distributions, variance, outliers

• Summary statistics (describe(), info())

• Correlation and covariance

• Identifying patterns using visuals

• Hands-on EDA project

Module 6: SQL Basics

• What is SQL? Introduction to RDBMS

• Writing basic SELECT queries

• WHERE, AND, OR, BETWEEN, LIKE

• Sorting and filtering data

Module 7: Aggregations and Joins

• Aggregate functions: SUM(), AVG(), MIN(), MAX(), COUNT()

• GROUP BY and HAVING

• Table joins: INNER, LEFT, RIGHT, FULL OUTER

• Subqueries and nested queries

• Aliases and calculated columns

Module 8: Advanced SQL for Analytics

• Window functions: RANK(), ROW_NUMBER(), LEAD(), LAG()

• CTEs (Common Table Expressions)

• Temporary tables and views

• Working with complex business queries

• Data cleaning using SQL

Phase 4: Tableau for Data Visualization

???? Module 9: Getting Started with Tableau

• Tableau interface overview

• Connecting to data sources (Excel, CSV, SQL)

• Data types and fields

• Dimensions vs Measures

• Data blending and joins

Module 10: Building Visualizations

• Bar, line, scatter, area, pie charts

• Tree maps, heat maps, highlight tables

• Filters, sets, and groups

• Dual-axis charts and combinations

• Parameters and calculated fields

Module 11: Dashboards and Storytelling

• Designing interactive dashboards

• Using actions (filter, highlight, URL)

• Creating stories and presenting insights

• Exporting and sharing dashboards (PDF, Tableau Public)