Data Analysis Certification Course in Hyderabad with AI & ChatGPT
- Earn Industry-recognized certification
- Build real-time projects with industry-aligned tools
- Live Interactive sessions from industry veterans
- Updated curriculum designed for AI-era
- Dedicated Job Assistance and Resume Building
Success Stories – They Believed, Learned & Achieved!
Our learners are working in leading organizations
Gain industry-ready skills and earn an official certificate from DataFlair
Online Data Analyst Course in Hyderabad Curriculum
- Understanding Business Intelligence
- Phases of Business Intelligence
- Use Cases of BI
- Introduction to Power BI?
- Perks 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
- Working of these components together
Power BI Desktop UI
- Overview of Power BI Desktop
- Installation of Power BI Desktop
- Exploring the Power BI Desktop interface
- Introducing 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
- Understanding Power Query
- Knowing About Power Query Editor
- Navigating the Power Query Editor interface
- Basic features and functionalities
Power Query Ribbon and Different Tabs Introduction
- What is a Power Query ribbon?
- Knowing 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
- Knowledge about the difference between fact and dimension tables
- Organizing your data for better analysis
Define Relationships and Cardinality
- How to create relationships between tables
- Learning one-to-many and many-to-many relationships
Design a Data Model Using a Star Schema
- Building a star schema for efficient data analysis
- Advantages of using a star schema in Power BI
Data Modelling and DAX
- What are Relationships
- Creating Relationships
- Cardinality
- Cross-filter direction
- Use of inactive relationships
Introduction of DAX
- Reasons to use DAX
- 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
- Getting started with your first Power BI report
- Importing and organizing your data in reports
Add Visualization Item to Reports
- Adding charts, graphs, and other visuals
- Customizing visual elements for clarity
Choose an Appropriate Visualization Type
- Choosing the right visual for your data
- Learning different visualization options
Formatting and Configuring Power BI Charts
- Improves 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
- Process to import and use custom visuals in your reports
Apply and Customize Themes
- Modifying the overall theme of your report
- Creating a constant look and feel
Configure Conditional Formatting
- Marking important data points
- Using color rules to enhance trends
Apply Sorting
- Sorting data to improve readability
- Techniques for effective data sorting
Apply Slicing and Filtering
- Inserting slicers for interactive filtering
- Using filters to focus on specific data
Create Hierarchies
- Making data hierarchies for better navigation
- Utilising 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
- Workspaces set up for collaboration
- Projects organization within workspaces
Assign Workspace Roles
- Managing user roles and permissions
- Enabling secure access to your data
Configure and Update a Workspace App
- Making apps for easy access to reports and dashboards
- Updating and maintaining workspace apps
Create Dashboard
- Making your first Power BI Dashboard
- Adding and arranging visuals on the dashboard
Manage Tiles on a Dashboard
- Styling tiles for better presentation
- Arranging tiles for optimal layout
Pin a Live Report Page to a Dashboard
- Connecting live report data to your dashboard
- Maintaining real-time data updates on your dashboard
- Understanding 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
- Interface Fundamentals
- 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
- Learning about 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
- Understanding Excel Automation and Macros
- Know about 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
- Performance Optimization for Large Datasets
- Planning and Designing Dashboards
- Using PivotTables and PivotCharts for Dynamic Data
- Slicers and Timelines for Interactive Filtering
- Creating Interactive Form Controls
- SQL Overview
- SQL Prerequisites
- What is SQL?
- Why do we use 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
- Understanding SQL Data Types
- String Data Type in SQL
- Numerical Data Type in SQL
- Date Data Type in SQL
- Practical Implementation of Date Data Type in SQL
- Know about SQL Operators
- 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 the 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
- Defining Joins in SQL
- Practical Implementation of SQL Joins
- Practical Implementation 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 the 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 and Sales System Project
- SQL Movie Rating System Project
- SQL E-commerce Product Refund and Return Analytics System Project
Tools & Technologies
Data Analytics using Python Projects
-
Sales Forecasting with Time Series Analysis
Predict future sales trends to support business planning and inventory management.Customer Segmentation
Group customers based on their behavior to improve marketing strategies and product targeting.Customer Churn Prediction
Identify customers likely to stop using a service to implement effective retention strategies. -
Market Basket Analysis
Discover purchasing patterns to recommend relevant products and increase sales opportunities.Sentiment Analysis
Analyze customer feedback to understand public opinion and improve brand perception.Web Traffic Trend Analysis and Anomaly Detection
Analyze website logs to detect unusual traffic spikes or drops using seasonal decomposition -
Credit Card Fraud Detection
Detect suspicious transactions to minimize financial losses and enhance transaction security.Supply Chain Demand Forecasting
Predict product demand accurately to optimize inventory levels and reduce stockouts.E-commerce Recommender System
Suggest personalized products to customers to improve shopping experience and boost sales. -
IoT Sensor Anomaly Detection
Monitor sensor data to identify unusual patterns and prevent potential system failures.Predictive Maintenance for Manufacturing Equipment
Anticipate equipment failures in advance to reduce downtime and maintenance costs.IoT Sensor Data Analytics for Smart Homes
Analyze smart home device data to optimize energy usage and improve living comfort.
Objectives of the Data Analyst Course in Hyderabad
- Learn about data analysis and visualizing data for generating reports that can be used to make decisions.
- Understand applying data operations methods using dataframes to organize, summarize, and interpret data distributions, correlation analysis, and data pipelines.
- To identify patterns and insights, use libraries such as Pandas, NumPy, and SciPy.
- Learn how to develop and evaluate regression models using Scikit-learn. This will help in predictions, giving data-driven, smart decisions.
- This Data Analyst course in Hyderabad will include live projects that help in creating a strong portfolio for future requirements.
- Use Matplotlib to cover insights by visualising data using charts and graphs.
Why should you learn Data Analysis?
In the fast-paced technology world where businesses rely heavily on data, your data analysis skills will be valued a lot. You do not need any coding or programming expertise, as you will be learning about tools such as Excel, SQL, and Power BI that are easy to use. Learning with real-time projects that will make you ready for industry challenges immediately after the course. Since there is a high demand for data analysts, the data analysis courses in Hyderabad with placements will make you ready to grab those opportunities.
What is Data Analysis?
Data Analysis involves bringing out sense from the data to solve real-world problems. It is all about transforming messy spreadsheets into clear insights that can be used by businesses to make informed decisions.
There is no coding knowledge necessary for getting enrolled in this data analysis training in Hyderabad, as we will guide you step by step to learn how to analyse and visualise data using different datasets. The demand for data analysts is increasing as companies are working on large datasets. It is a great opportunity for you to start your career by identifying trends and creating easy visuals.
What to do before you begin?
This online Data analysis coaching in Hyderabad is designed for beginners as well as seasoned professionals. You do not require any prior programming experience to enrol in this course. Having basic knowledge about computers, like browsing the internet and using Word and Excel tools, will be helpful. Learners with analytical skills, like solving puzzles and problems, will find this course very interesting. A basic understanding of mathematical concepts such as averages, statistics, and percentages is enough.
Do not worry if you are unsure about these prerequisites; we have still got you covered. We provide learning from scratch and gradually move towards advanced concepts to build a strong foundation. You just need to be curious to learn about data analysis; we will handle the rest and ensure a smooth learning experience for all learners.
Who should choose the Best Data Analyst course in Hyderabad?
The online data analyst course in Hyderabad is for all those willing to start a career with Data Analysis skills or experienced learners who want to update their skillset.
- Students and Fresh Graduates, to kickstart their journey with data analysis skills.
- Career Switchers planning to start a career in the data fields.
- Working Professionals upgrading their skillset.
- Entrepreneurs and Small Business Owners need to make themselves capable of working with datasets.
- Freelancers and Aspiring Consultants to boost their opportunities.
- Anyone curious about learning data.
Benefits you will get after enrolling in the Best Data Analyst coaching in Hyderabad:
- Gain understanding of various tools like Excel, SQL, and Power BI that can be used in different fields like healthcare, marketing, etc.
- Get hands-on with various datasets and become confident in making data-driven decisions.
- You can easily grasp the knowledge provided in this course as we provide learning with practical exercises and training projects.
- After course completion, you will be eligible for the certification that can be used to showcase your skills to potential employers.
Jobs after learning Data Analysis
Become eligible for various high-paying job roles that will secure your future and make you stable in your career path. Some of the potential job roles are mentioned below, from which you can choose based on your expertise and plans:
- 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 Analytics with Python Course
Data Analyst Online Training in Hyderabad FAQs
This Data Analysis training in Hyderabad is designed to teach you the fundamentals of data analysis, equipping you with the skills to collect, clean, analyze, and visualize data. Students, professionals, or beginners with an interest in data analysis can enrol in this course.
The live classes are led by industry expert instructors. These live sessions are conducted online, and you can attend them from anywhere.
Yes, all the enrolled learners will have access to recordings of the live sessions. In case you miss any live classes, you can go through the recorded lectures and keep up your learning pace.
The online Data Analysis classes in Hyderabad equip you with essential tools for data manipulation and visualization, specifically Excel (advanced formulas/Power Query), SQL, and Power BI.
You will be working on around 30 projects during the training. These projects will increase your practical knowledge and make you job-ready.
The projects included in this course are designed on the basis of real-world data analysis challenges. These projects will help you to create a strong portfolio.
After completing this best data analysis training in Hyderabad, you will be eligible to get the certification from the official website with the help of your credentials.
Yes, this Data Analyst course in Hyderabad includes various assignments and practical exercises for learners.
During this online Data Analyst course in Ameerpet, mentors will provide complete support and guidance to the students. We ensure a smooth learning experience by resolving your queries.
This Data Analysis course in Ammerpet is beginner-friendly, and learners from non-technical backgrounds can enrol in this course. We provide learning from scratch, gradually covering advanced topics.
