Data Analyst Certification Course with AI & ChatGPT
- Earn Industry-recognized IBM certification
- Build real-time projects with industry-aligned tools
- Live Interactive sessions from industry veterans
- Updated curriculum designed for AI-era
- Boost employability with globally recognized IBM credentials
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Success Stories – They Believed, Learned & Achieved!
Our learners are working in leading organizations
Gain industry-ready skills and earn an official certificate from DataFlair and IBM.
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Online Data Analyst Training Course Curriculum
- What is Business Intelligence
- Stages of Business Intelligence
- Use Cases of BI
- What is Power BI?
- Benefits of using Power BI
- Real-world applications of Power BI
- Various BI Tools
- How to download Power BI Desktop
- Step-by-step installation guide
- Initial setup and configuration
Understanding Power BI components
- Desktop, Service, Mobile
- How these components work together
Power BI Desktop UI
- Introduction to Power BI Desktop
- Installation of Power BI Desktop
- Exploring the Power BI Desktop interface
- Overview of key features and tools
- Navigating through different panes and menus
Identify and Connect to a Data Source
- Types of data sources supported by Power BI
- Choosing the right data source for your needs
Get Data from Flat Files and Relational Data Sources
- Importing data from Excel, CSV, and other flat files
- Connecting to databases like SQL Server, MySQL, and more
Introducing the Power Query Editor and Power Query UI
- What is Power Query?
- Introduction to Power Query Editor
- Navigating the Power Query Editor interface
- Basic features and functionalities
Power Query Ribbon and Different Tabs Introduction
- Overview of the Power Query ribbon
- Understanding different tabs and their functions
Enhance the Structure of the Data and Table Structure
- Organizing and structuring your data tables
- Creating relationships between tables
Profile the Data
- Analyzing data quality
- Identifying and handling data issues
Evaluate and Transform Column Data Types
- Changing data types for accuracy
- Ensuring consistency across your data
Change Data Source Settings
- Updating and managing data source connections
- Handling data source changes efficiently
Identify Fact and Dimension Tables
- Understanding the difference between fact and dimension tables
- Organizing your data for better analysis
Define Relationships and Cardinality
- Creating relationships between tables
- Understanding one-to-many and many-to-many relationships
Design a Data Model Using a Star Schema
- Building a star schema for efficient data analysis
- Benefits of using a star schema in Power BI
Data Modelling and DAX
- Introduction to Relationships
- Creating Relationships
- Cardinality
- Cross-filter direction
- Use of inactive relationships
Introduction of DAX
- Why is DAX used?
- DAX syntax
- DAX functions
- Context in DAX
- Measures using DAX
Create Calculated Tables
- Adding new tables using DAX
- Practical examples of calculated tables
- Learning about table, information, logical, text, iterator,
- Time intelligence functions (YTD, QTD, MTD)
Create Calculated Columns
- Creating columns with custom calculations
- Using DAX for dynamic data manipulation
Create Basic Measures Using DAX
- Understanding measures in Power BI
- Writing simple DAX formulas for calculations
- Date and time functions
Difference Between Calculated Columns and Measures
- When to use calculated columns vs. measures
- Best practices for using DAX in your data model
- DAX advanced features
Create Report from Raw Data
- Starting your first Power BI report
- Importing and organizing your data in reports
Add Visualization Items to Reports
- Inserting charts, graphs, and other visuals
- Customizing visual elements for clarity
Choose an Appropriate Visualization Type
- Selecting the right visual for your data
- Understanding different visualization options
Formatting and Configuring Power BI Charts
- Enhancing the look and feel of your charts
- Using formatting tools effectively
Use a Custom Visual and Import Custom Visuals
- Exploring the Power BI marketplace for custom visuals
- How to import and use custom visuals in your reports
Apply and Customize Themes
- Changing the overall theme of your report
- Creating a consistent look and feel
Configure Conditional Formatting
- Highlighting important data points
- Using color rules to emphasize trends
Apply Sorting
- Sorting data to improve readability
- Techniques for effective data sorting
Apply Slicing and Filtering
- Adding slicers for interactive filtering
- Using filters to focus on specific data
Create Hierarchies
- Building data hierarchies for better navigation
- Using hierarchies to drill down into data
Drilldown/Drillup into Data Using Interactive Visuals
- Exploring data at different levels of detail
- Making your visuals interactive and dynamic
AI Visuals – Q & A, Key Influencers, Decomposition Tree, Smart Narratives
- Utilizing AI-powered visuals for deeper insights
- How to implement and use AI visuals in your reports
Publish Reports
- Sharing your reports with others
- Publishing reports to the Power BI service
Create and Configure a Workspace
- Setting up workspaces for collaboration
- Organizing your projects within workspaces
Assign Workspace Roles
- Managing user roles and permissions
- Ensuring secure access to your data
Configure and Update a Workspace App
- Creating apps for easy access to reports and dashboards
- Updating and maintaining workspace apps
Create Dashboard
- Building your first Power BI dashboard
- Adding and arranging visuals on the dashboard
Manage Tiles on a Dashboard
- Customizing tiles for better presentation
- Organizing tiles for optimal layout
Pin a Live Report Page to a Dashboard
- Linking live report data to your dashboard
- Ensuring real-time data updates on your dashboa
- Introduction to GenAI and its integration with Power BI
- Using Power BI Copilot for report generation and data analysis
- Enhancing dashboards with AI-generated summaries and insights
- Automating data storytelling with natural language narratives
- Real-world use cases of GenAI in business intelligence
- Best practices for using GenAI features responsibly
- Introduction to Interface
- Navigating Sheets and Workbooks
- Ribbon in Excel
- Entering and Editing Data
- Basic Formatting: Fonts, Alignment, Number Formats
- Working with Cell Ranges and Selections
- Saving, Sharing and Collaborating
- Understanding Formulas: Operators and Cell References
- Basic Functions: SUM, AVERAGE, COUNT
- Working with Dates and Times
- Introduction to Logical Functions: IF, AND, OR
- Common Text Functions: CONCATENATE, LEFT, RIGHT, MID
- More on Functions: MIN, MAX, MEDIAN
- Array Formulas Basics
- Error Handling in Formulas
- ISNA and IFERROR Function
- Advanced Sheet Operations
- Jumping Between Sheets
- Mastering Multiple Workbooks
- Hiding and Unhiding Rows and Columns
- Freezing Panes and Splitting Screens
- Conditional Formatting: Highlighting Data
- Creating and Applying Cell Styles
- Working with Tables
- Sorting and Filtering Data
- Charts and Graphs: Creating Visualizations
- Customizing Charts: Formatting and Design
- Sparklines: Visual Data in Cells
- Sorting and Filtering Data: Advanced Techniques
- Working with Pivot Tables: Creating Interactive Reports
- Pivot Charts: Visualizing Pivot Table Data
- What-If Analysis: Goal Seek
- Data Tools in Excel
- Data Validation: Ensuring Data Integrity
- Importing and Exporting Data (CSV, Excel, etc.)
- Lookup Functions: VLOOKUP, INDEX, MATCH, XLOOKUP
- Statistical Functions: COUNTIFS, SUMIFS, AVERAGEIFS, STDEVIFS
- Array Formulas: Working with Ranges of Data
- Financial Functions: PMT, NPV, IRR, FV, PV
- Advanced Text Functions: LEN, PROPER, TRIM, FIND, SEARCH
- Working with Dates and Times (Advanced)
- Advanced Logical Functions
- Introduction to Power Query and Data Import
- Data Cleaning and Transformation
- Adding Columns and Combining Data
- Power Query Automation and Web Scraping
- Loading Data and Best Practices
- Power Pivot in Excel
- Introduction to Excel Automation and Macros
- Getting Started with the VBA Editor (Interface)
- VBA Fundamentals: Variables, Data Types
- Working with Objects: Ranges, Worksheets, and Workbooks
- Automating Tasks & User Interaction
- Debugging, Error Handling, & Macro Security
- Analyze Data Feature: Generating Insights and Visualizations
- Ideas Feature: Formula Suggestions, Data Patterns
- Data from Picture: Extracting Data from Images
- Forecasting with Forecast Sheet: Predicting Future Trends
- Keyboard Shortcuts and Productivity Tips
- Optimizing Performance for Large Datasets
- Planning and Designing Dashboards
- Using PivotTables and PivotCharts for Dynamic Data
- Slicers and Timelines for Interactive Filtering
- Creating Interactive Form Controls
- Introduction to SQL
- SQL Prerequisites
- What is SQL
- Purpose of SQL
- MySQL Server Installation
- SQLYog Installation
- Difference Between DBMS and RDBMS
- SQL Database and Database Server
- Comments in SQL
- What are SQL Commands
- SQL DDL Statements
- SQL DDL Statements – Alter and Drop Command
- Practical Implementation of SQL DDL Command
- SQL DML Statements
- SQL DML Statements – Delete and Update Command
- Practical Implementation of SQL DML Command
- SQL TCL Command
- Practical Implementation of TCL Command
- SQL DCL Command
- Practical Implementation of DCL Command
- What are Data Type in SQL
- String Data Type in SQL
- Numerical Data Type in SQL
- Date Data Type in SQL
- Practical Implementation of Date Data Type in SQL
- What are Operators in SQL
- Arithmetic Operator in SQL
- Relational Operator in SQL
- Logical Operator in SQL
- Practical Implementation of Arithmetic, Relational and Logical Operators
- SQL String Operators
- SQL Like and Not Like Command
- Constraints in SQL
- Practical Implementation of Constraints in SQL
- Order by Clause in SQL
- Practical Implementation of Order by Clause
- GROUP BY and HAVING in SQL
- Practical Implementation of GROUP BY and HAVING in SQL
- Like Command in SQL
- Practical Implementation of Like Command in SQL
- Between and In Command in SQL
- Practical Implementation of Between and In Command
- ANY and ALL Operators
- Alias in SQL
- Practical Implementation of Alias in SQL
- What are Joins in SQL
- Practical Implementation of SQL Joins
- Practical Implementatin of Self Join
- Primary Key and Foreign Key Constraint in SQL
- Practical Implementation of Primary Key and Foreign Key Constraint
- Injection in SQL
- Practical Implementation of Injection
- Null Functions
- Check Constraint in SQL
- Practical Implementation of Check Constraint
- Default Constraint in SQL
- Practical Implementation of Default Constraint
- Null Value in SQL
- Practical Implementations of Null Value in SQL
- Auto Increment in SQL
- Practical Implementation of Auto Increment in SQL
- Aggregate Functions in SQL
- Practical Implementation of Aggregate Functions
- String Functions
- Nested Query in SQL
- Practical Implementation of Nested Query
- SQL Window Function
- Practical Implementation of Window Function
- Bulk Insert in SQL
- Backup and Restore in SQL
- SQL Library Management System Project
- SQL Sales Data Analysis Project
- SQL Restaurant Billing System Project
- SQL Patient Record System Project
- SQL Vehicle Service Booking System Project
- SQL Simple Inventory ans Sales System Project
- SQL Movie Rating System Project
- SQL E-commerce Product Refund and Return Analytics System Project
Tools & Technologies
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Join 1,67,950+ learners enrolled in our Data Analyst Course – Try before you Buy
Benefits:
- ✓ Live Classes with Expert Mentors
- ✓ Practical-based learning
- ✓ Hands-on Projects & Case Studies
- ✓ Dedicated Job Assistance & Resume Building
- ✓ Lifetime Course Access
Benefits:
- ✓ Everything in Live Online Course, plus:
- ✓ Earn Global IBM certificates
- ✓ Professional-level training from IBM
- ✓ Masterclasses from IBM experts
- ✓ IBM-aligned labs for job-ready output
Enroll in Self-paced Data Analyst Course
Key Features:
- ✓ Self-paced Expert-led Course
- ✓ Practical-based Curriculum
- ✓ Full Notes + Study Material
- ✓ Real-world Practicals
- ✓ Assessments to Test Skills
- ✓ Interview Ques of Top MNCs
- ✓ Real-time Live Projects
- ✓ Beginner to Advanced
- ✓ 3 years Access Duration
- ✓ Professional Certificate
Key Features:
- ✓ Everything in “PLUS” plus:
- ✓ Job-Ready Skill Training
- ✓ Live Industry Case Studies
- ✓ 1:1 Expert Counselling
- ✓ Dedicated Job Assistance
- ✓ Resume & Interview Prep
- ✓ Additional live Projects
- ✓ Latest Tools/Tech Covered
- ✓ Lifetime Course Access
- ✓ Learn with ChatGPT & AI
Key Features:
- ✓ Everything in “PRO” plus:
- ✓ Global Certification from IBM
- ✓ IBM-aligned curriculum
- ✓ Industry-grade projects
- ✓ Company-wise Interview Ques
- ✓ Pro-level training from IBM
- ✓ Additional Real-time Projects
- ✓ IBM-aligned labs, job-ready output
- ✓ Masterclasses from IBM experts
- ✓ Enhanced Career Opportunities
Data Analyst Course Objectives
- Master Essential Tools and Technologies
- Develop Statistical and Analytical Thinking
- Learn Data Visualization and Reporting
- Work with Real-World Datasets
- Explore Domain-Specific Applications
- Understand Advanced Data Analysis Concepts
- Enhance Problem-Solving Skills
- Foster Continuous Learning
- Understand the basics of data analysis in a simple, beginner-friendly way
- Learn to use non-programming tools like Excel and Power BI to analyse and visualise data
- Work on practical projects to develop job-ready skills
- Build a portfolio to showcase your abilities to potential employers
- Learn how to present data insights in an easy-to-understand format
Why should you learn Data Analysis?
- Step Into the Data Era: With businesses relying on data more than ever, your skills will be highly valuable.
- No Programming Required: You’ll learn tools like Excel, SQL, and Power BI that are easy to use and don’t need coding expertise.
- Practical, Real-World Learning: Work on projects that mimic real business challenges, helping you build skills you can apply immediately.
- High-Demand Skills: Data Analysts are in demand everywhere—this Data Analyst course prepares you for those opportunities.
What is Data Analysis?
Data Analysis is making sense of data to solve real-world problems. Imagine transforming messy spreadsheets into clear insights businesses use to make decisions—this is what data analysis is all about.
You don’t need coding skills or programming knowledge to start; this Data Analyst course will teach you how to analyse data step by step. Fun fact: By 2025, companies worldwide will generate over 180 zettabytes of data and need people like you to help them understand it! Data analysis is your gateway to an exciting and rewarding career, from identifying trends to creating easy-to-understand visuals.
What to do before you begin?
You don’t need programming knowledge to join this Data Analyst course! We ensure smooth learning for you all.
Here’s what you need to get started:
- Basic Computer Knowledge: You’re already prepared if you can browse the internet or use tools like Word and Excel.
- Analytical Thinking: Data analysis will be fascinating if you enjoy solving puzzles or finding patterns.
- Basic Math Skills: Understanding simple mathematical concepts like averages, percentages, and statistics is enough.
- Eagerness to Learn: A curious mind and a willingness to explore new ideas are all you need.
Good News! Even if you feel unsure about these prerequisites, our Data Analyst course is designed with beginners in mind. From fundamentals to advanced topics, we’ve got you covered. All you need to bring is your enthusiasm to learn; we’ll take care of the rest!
Who should go for this Data Analyst course?
The Data Analyst course is designed for anyone who wants to learn about data. Whether you’re a beginner or looking to upskill, this course is for you.
- Students and Fresh Graduates
- Career Switchers
- Working Professionals
- Entrepreneurs and Small Business Owners
- Freelancers and Aspiring Consultants
- Anyone Curious About Data
By enrolling in our Data Analyst course, you can expect the following benefits:
- Easy to Use: It is made for those who are not programmers, thus anyone can use the tool.
- Practical Experience: Project-based learning to prepare you for real directions.
- Tools Used in the Industry: Learn Excel, Power BI, and SQL — no coding required!
- Career Versatility: Your skills are transferable to marketing, healthcare, etc.
- Professional Certificate: Showcase your expertise with a certificate upon completion.
Jobs after Learning this Data Analyst Course
After completing this Data Analyst course, there are many high-paying, in-demand career opportunities across various industries. Exciting job roles you can pursue:
- Data Analyst
- Business Analyst
- Financial Analyst
- Marketing Analyst
- Operations Analyst
- Product Analyst
- Freelance Data Consultant
- Data Visualization Specialist
- Risk Analyst
Our students are working in leading organizations
Features of Data Analyst Course
Looking for Industry Expert Counselling?
We are a team of trainers who have 20+ years of Industry Experience. They provide project based training and cover real time scenarios during the interactive training sessions.
Contact our Industry Experts & get answers to all your queries.
Data Analyst Online Training FAQs
This Data Analyst course is designed to teach you the fundamentals of data analysis, equipping you with the skills to collect, clean, analyze, and visualize data. It covers industry-standard tools like Excel, SQL, Power BI, and real-world projects.
Whether you’re a student, working professional, entrepreneur, or someone switching careers, this Data Analyst course is perfect for anyone looking to enter the high-demand field of data analysis.
No prior experience is required! Basic computer knowledge and an eagerness to learn are all you need. The Data Analsyt course is beginner-friendly, and we’ll guide you step by step.
Absolutely! This Data Analyst course equips you with skills to transition into data analysis from any field.
You’ll work on real-world datasets and projects, such as sales trend analysis, customer behavior analysis, creating dashboards, and predicting future trends using statistical methods.
This course prepares you for roles like Data Analyst, Business Analyst, Data Scientist, Financial Analyst, Marketing Analyst, and many more across various industries like technology, healthcare, and finance.
The Data Analyst course is self-paced, so you can complete it in approximately 8–10 weeks, depending on how much time you dedicate daily. You can learn at your own pace without compromising your current commitments.
Yes! Upon completing the course, you’ll receive a verifiable certificate, which you can showcase on your resume, LinkedIn, or portfolio.
It’s specifically designed for non-programmers, with hands-on learning and tools that are easy to use.
This Data Analyst course is designed with a hands-on, practical approach, focusing on real-world applications and job readiness. You won’t just learn tools; you’ll gain the confidence to solve real business problems and showcase your skills to potential employers.
