Data Analyst with AI

Data Analyst with AI

Data Analyst roles are the fastest entry point into the data career ladder — and in 2026, the analysts who win are the ones who pair classical SQL/BI skills with AI-augmented workflows. In two months you'll master advanced SQL, Excel, Power BI, Tableau, and Python (Pandas + NumPy), then learn to use ChatGPT, Claude, and Copilot to ship insights 3-5× faster than analysts at most companies. Four capstone projects across retail, finance, healthcare, and marketing leave you with a portfolio hiring managers actually care about.

0 lessons

What you'll learn

  • Write complex SQL with window functions, CTEs, and performance tuning
  • Build interactive Power BI and Tableau dashboards from scratch
  • Use Python to clean, transform, and analyze real-world datasets
  • Apply AI tools to generate SQL, explain anomalies, and accelerate analysis
  • Communicate insights through clear, story-driven dashboards
  • Run hypothesis tests + A/B test analysis with confidence
  • Land Junior Analyst / BI Analyst roles paying ₹4-10 LPA
  • Move up to Senior / Lead Analyst tracks (₹12-25 LPA) within 2-3 years

Technologies Taught

Advanced SQL — joins, window functions, CTEs, indexesMicrosoft Excel — VLOOKUP, Power Query, Pivot Tables, Power PivotPower BI — DAX, data modelling, dashboards, Power BI ServiceTableau Desktop + Tableau Cloud — LOD, parameters, storytellingPython — Pandas, NumPy, Matplotlib, Seaborn, JupyterChatGPT + Claude for SQL generation and data explorationGitHub Copilot in VS Code + ExcelStatistics + hypothesis testing fundamentalsGoogle Analytics 4 + Looker Studio

Course Unique Features

  • Hands-on with real, messy business datasets — not textbook samples
  • Build a 4-project portfolio across retail, finance, healthcare, and marketing
  • AI tools woven into every module — not bolted on at the end
  • Daily 90-minute live sessions + dedicated doubt-clearing time
  • Power BI + Tableau covered side-by-side so you can pick your tool
  • Resume + LinkedIn polish with mock interview rounds
  • Direct referrals to companies actively hiring junior analysts
  • Trained by analysts with 8+ years of cross-industry experience
  • Lifetime access to course recordings + dataset library
  • Excel + SQL interview-practice packs worth ₹5,000 included

Job Opportunities

Top job positions you can apply for after completing this training.

Job RoleExperienceSalary Range
1. Junior Data AnalystFresher to 1+ Year₹3–5 LPA
2. Power BI DeveloperFresher to 3+ Years₹4–8 LPA
3. Business Intelligence Analyst2 to 4 Years₹6–10 LPA
4. Data Visualization Specialist2 to 4 Years₹7–12 LPA
5. SQL + Power BI Analyst2 to 5 Years₹8–14 LPA
6. MIS / Reporting Analyst3 to 5 Years₹9–15 LPA
7. BI Consultant4 to 6 Years₹12–18 LPA
8. Senior Power BI Developer5 to 7 Years₹14–20 LPA
9. Analytics Manager (BI focus)6 to 8 Years₹18–28 LPA
10. Data Analytics Lead / BI Architect8+ Years₹25–40 LPA

You Can Work As

Data AnalystBusiness AnalystBI AnalystMarketing AnalystFinancial AnalystProduct AnalystOperations Analyst

Upcoming In-Demand Jobs

AI-Augmented AnalystAI Insights EngineerSelf-Service BI AnalystAnalytics Engineer

Course Curriculum

POWER BI Course Content

4 topics
  • Core Components: Power BI Desktop, Power BI Service, Power BI Mobile
  • Data Flow in Power BI: From Source to Visual
  • Understanding Power BI Gateways for Data Connectivity
  • Introduction to Power BI API and Developer Capabilities

Introduction to Power BI

6 topics
  • Introduction to Microsoft Fabric
  • Introduction to Power BI
  • Overview of Power BI Architecture
  • Connecting to Software as Services
  • Exploring the Power BI Community
  • Hands-on: Setting Up Your First Report

Connecting to Data Sources

6 topics
  • Connecting to File System (Excel, CSV, etc.)
  • Connecting to Data on the Web
  • Connecting to On-Premises Databases (SQL, Oracle, etc.)
  • Connecting to Cloud Databases (Azure, Snowflake, etc.)
  • Troubleshooting Data Source Connections
  • Hands-on: Data Source Integration

Transforming Data Using Power BI Desktop

10 topics
  • Overview of Power Query Editor Interface and Tools
  • Basic Data Transformations: Filtering, Sorting, and Shaping Data
  • Understanding Power Query's M Language
  • Importing and Cleaning Data with Power Query Editor
  • Managing Query Groups and M Queries
  • Conditional Columns and Advanced Transformations
  • Merging and Appending Data from Multiple Sources
  • Automating Data Refresh and Optimization
  • Understanding Power Query's M Language
  • Hands-on: Data Transformation Techniques

Data Modelling in Power BI Desktop

6 topics
  • Managing Data Relationships
  • Creating Calculated Columns and Measures
  • Optimizing Data Models for Performance
  • Time Intelligence and Hierarchies
  • Using Calculated Tables and Grouping Data
  • Hands-on: Building Data Models

DAX – Data Analysis Expressions

21 topics
  • Advanced Usage of SUM, SUMX, AVERAGE, MIN, and MAX
  • Practical Scenarios and Performance Tips
  • Key Differences in Context, Calculation, and Usage
  • When to Use Columns vs. Measures in Your Reports
  • Working with Date Calculations: YEAR, MONTH, DAY, etc.
  • Do's and Don'ts of Date Calculations in Power BI
  • Building Custom Date Calculations for Specific Needs
  • Advanced Scenarios with IF, SWITCH, AND, OR, and NOT
  • Nested IF Logic: Handling Complex Conditional Calculations
  • Understanding RELATED, RELATEDTABLE, and LOOKUPVALUE
  • Cross-Table Calculations and Their Applications
  • Cross-Table Calculations
  • Techniques for Performing Calculations Across Related Tables
  • Best Practices and Performance Optimization
  • Manipulating Text Data in DAX
  • Formatting and Parsing Text Fields: CONCATENATE, LEFT, RIGHT, UPPER, LOWER
  • Working with CALENDAR, SAMEPERIODLASTYEAR, PARALLELPERIOD, and DATEADD
  • Creating Dynamic Time Calculations for Business Insights
  • Practical Scenarios to Apply DAX Functions
  • Real-world Challenges and Problem-Solving Using DAX
  • Step-by-Step Exercises to Solidify Understanding

Visualizing Data in Power BI

7 topics
  • Creating Basic Charts: Pie, Donut, Bar, and Line Charts
  • Advanced Visuals: Scatter, Waterfall, KPI, Gauge
  • Using Slicers, Filters, and Drill through
  • Customizing and Formatting Visuals
  • Working with Map Visualizations and Analytics Pane
  • Hands-on: Designing Interactive Dashboards
  • Publishing Reports and Implementing Security

Hands-on: Setting Up Your First Report

4 topics
  • Creating Your First Report from Scratch
  • Connecting to a Sample Dataset
  • Applying Basic Transformations and Building Visuals
  • Publishing Your First Report to Power BI Service

Working with Power BI Service

6 topics
  • Overview of Power BI Service and Dashboards
  • Publishing Reports to Power BI Service
  • Configuring Dashboards and Adding Widgets
  • Sharing, Collaborating, and Configuring Data Refresh
  • Alerts, Notifications, and Data Exports
  • Hands-on: Managing Power BI Service Dashboards

Apps, Security, and Groups – Collaboration

4 topics
  • Creating and Managing Power BI Apps
  • Row-Level Security Implementation
  • Collaboration with Workspaces and Groups
  • Hands-on: Security and App Management

Exploring the Power BI Community

4 topics
  • Engaging with the Power BI Community Forum and Blogs
  • Accessing Power BI Templates and Best Practices
  • Learning from Community Showcases and Use Cases
  • Networking with Other Power BI Professionals

Exploring Power BI Content Online

2 topics
  • Navigating Report Galleries and Public Content
  • Learning from Published Reports and Best Practices

In-Class Project

5 topics
  • Tips and Tricks for Building Effective Reports
  • Best Practices for Report Design and Layout
  • Advanced Techniques for Data Visualization
  • Common Pitfalls and How to Avoid Them
  • Enhancing User Experience with Interactivity

Building the In-Class Project

4 topics
  • Applying Skills Learned to Build a Real-World Report
  • Step-by-Step Guidance on Project Execution
  • Hands-on Problem Solving and Data Analysis
  • Integrating Data Sources and Building Visuals

Presentation and Peer Feedback

4 topics
  • Presenting Your Project to the Class
  • Receiving Constructive Feedback and Suggestions
  • Discussing Challenges and Solutions
  • Refining Your Report Based on Feedback

Final Reflection and Learnings

4 topics
  • Reflecting on Key Learnings from the Training
  • Identifying Areas for Improvement
  • Planning for Future Power BI Projects
  • Final Q&A and Course Wrap-up

Microsoft Fabric Overview

11 topics
  • What is Microsoft Fabric?
  • Key Features of Microsoft Fabric
  • Unified Data Platform
  • Integrated with Power BI
  • Lakehouse Architecture
  • Dataflows and Pipelines
  • Synapse Integration
  • Security and Compliance
  • Collaboration and Data Sharing
  • AI and Machine Learning Integration
  • Benefits of Microsoft Fabric

Course Instructed By

MC
Ms. Chaitali Arankalle---

A seasoned Data Analytics professional with 9+ years of experience turning complex data into meaningful business impact. Skilled in data strategy, analytics, and cloud platforms, she has built dashboards, predictive models, and marketing analytics pipelines. As an experienced trainer, she has empowered working professionals, freshers, managers, and team leaders worldwide to achieve their data analytics career goals through her engaging style and strong industry insights. Approved trainer by Raj Cloud Technologies.

Approved trainer by Raj Cloud Technologies

Course content

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Certificate included

On 100% completion

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₹16,499

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