Exhaustive Course Curriculum

 Industry-relevant course curriculum is tailored to provide practical exposure with the theory.

Top-Notch Faculty

Trainers at GANA Tech are passionate about training and carry 13+ years of industry experience.

Real-life Projects

Learners will work on real-life data analytics scenarios from various domains to get application knowledge.

Job Readiness

Intensive interview preparation from Day 1 to prepare candidates for interviews with our network of 1500+ hiring partners.

Advanced Excel

MySQL

Tableau

Power BI

1: Python

• Introduction to Python
• Installation of Anaconda
• Data types in Python
• Operators
• Variables
• Arithmetic and String operations
• For loop
• User input & While loops
• Controlstatements
• Functions
• Lists
• Tuples
• Sets
• Dictionaries
• Numpy
• Pandas
• Data Visualization with Matplotlib
• Data Visualization with Seaborn
• Case studiesfor Visualizations using Matplotlib and Seaborn
• Data Cleaning using Python
• Univariate, Bivariate and Multivariate Analysis
• Understanding the Risk Associated in Bank (Real Time Live Project)

2: SQL

• Introduction to SQL
• Database Design
• Data Warehouse Concepts
• SQL Data Types
• SQL Operators
• DDL commands
• DML commands
• DQL commands
• DCL & TCL commands
• WHERE, HAVING, ORDER BY, LIMIT & OFFSET
• Group By
• Joins
• Window Functions
• Case Statements
• Common Table Expressions
• Sub Queries
• Frames in SQL
• LEAD() & LAG() Functions
• Views
• Triggers
• Structured Problem Solving in SQL
• Advanced SQL Queries
• IMDB movies analysis using SQL (Real Time Live Project)

3: Databricks + PySpark

• Big Data & Spark Foundations
• Spark Architecture
• What is Databricks?
• Databricks Architecture & Lakehouse concept
• Setting up Databricks
• Creating Clusters & Notebooks
• SparkSession & SparkContext
• RDDs vs DataFrames
• Reading CSV, JSON, Parquet
• Basic DataFrame Operations
• Compare Pandas vs PySpark syntax
• Spark SQL for Analysts
• Creating Temp Views
• Writing SQL queries in Databricks
• SQL joins, aggregations, filtering
• Window Functions
• Handling Nulls & Duplicates
• String Operations & Regex
• Date/Time Parsing
• UDFs (User Defined Functions)
• Data Type Conversions
• Inner, Left, Right, Full joins
• Group By & Aggregations
• Pivot/Unpivot operations
• Delta Lake & Medallion Architecture
• Delta Lake Features (ACID, time travel, schema enforcement)
• Delta Lake Features (ACID, time travel, schema enforcement
• Writing & Reading Delta tables
• Optimizing Delta queries
• Convert CSV output to Delta table
• Performance Optimization & Best Practice

4: Microsoft Excel

• Introduction to Excel
• Sort & Filter in Excel
• Basic Formatting
• Text Functions
• Statistical Functions
• Logical Functions
• Basic Formatting-I
• Basic Formatting-II
• Conditional Formatting-I
• Conditional Formatting-II
• LOOKUP functions
• INDEX and MATCH functions
• PIVOT tables
• Recording Macros

5: Tableau

• Introduction to Tableau
• Tableau Installation
• Tableau Workflow and Interface
• Tableau Data Types
• Tableau Operators
• Parameters and Calculated fields
• Groups & Sets
• Tableau Functions
• Bar chart
• Line chart
• Packed Bubble chart
• Area chart
• Tree map
• Heat map
• Box plot
• Scatter plot
• Pie chart
• Histogram
• Stacked Bar chart
• Dual Axis chart
• Dashboard Creation
• Story Creation
• IPL Visualization Using Tableau (Real Time Live Project)

6: Power BI

• Overview of Power BI
• Power BI vs Tableau vs Excel
• Power BI ecosystem: Power BI Desktop, Service, and Mobile
• Exploring the Power BI interface and basic components
• Installation and setup of Power BI Desktop
• Supported data sources (Excel, SQL Server, Web, APIs, etc.)
• Import vs. DirectQuery mode
• Connecting to on-premises and cloud data sources
• Data Gateway for on-premises data refresh
• Best practices for data connectivity
• Introduction to Power Query Editor
• Data cleaning techniques (removing duplicates, handling nulls, etc.)
• Merging & appending queries
• Column transformations (split, merge, extract)
• Understanding star and snowflake schema
• Creating and managing relationships between tables
• Cardinality and cross-filter direction
• Optimizing models for performance
• Role of Fact and Dimension tables
• Introduction to DAX (Data Analysis Expressions)
• Measures vs. Calculated Columns
• Common DAX functions (SUMX, CALCULATE, FILTER, etc.)
• Time intelligence functions (YTD, MTD, QTD)
• Performance optimization for DAX
• Designing effective dashboards and reports
• Using slicers, filters, and bookmarks
• Advanced visualizations (custom visuals, drill-through, tooltips)
• Themes and branding in reports
• Publishing reports to Power BI Service
• AI Visuals
• Introduction to Power BI Service
• Creating and managing workspaces
• Dataflows and dataset management
• Scheduling data refresh and subscriptions
• Power BI Apps and content packs
• Introduction to security in Power BI
• Implementing Row-Level Security (static & dynamic)
• User roles and access control
• Sharing reports securely
• Best practices for governance and compliance
• Best Practices in Power BI
• Bookmarks and Performance Analyzer
• Creating an Interactive Dashboard for Home Loans (Real Time Live Project)

7: Statistics

• Measures of Central Tendency
• Measures of Dispersion
• Basics of Probability
• Data Distribution
• Percentiles and Quartiles
• Sampling and Sampling Distribution
• Hypothesis Testing

Banking Risk Analysis

In this real-time project, you’ll work with banking datasets to identify and analyze potential loan defaults and credit risks. Using Python, Pandas, NumPy, and visualization tools, you’ll learn how to clean data, perform univariate, bivariate & multivariate analysis, and uncover insights that help banks make data-driven lending decisions.

IMDB Movies Data

Work on real-world movie datasets from IMDB to master SQL querying. You’ll practice joins, subqueries, aggregations, window functions, and query optimization while analyzing movie ratings, genres, box office collections, and trends. This hands-on project helps you understand how SQL is applied in real-time business analytics.

IPL Dashboard

Build an interactive Tableau dashboard using real-time IPL match data. Learn how to analyze player performance, team comparisons, season trends, and match statistics with dynamic charts and filters. This project helps you showcase your ability to create professional, business-ready visualizations from raw sports data.

IPL Dashboard 

In this real-time project, you’ll work with home loan datasets to clean, model, and visualize data using Power BI. You’ll build an interactive dashboard that tracks loan approvals, rejections, EMI status, and customer profiles. This project helps you master data cleaning, DAX calculations, and interactive reporting, preparing you for real-world business analytics tasks.