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Placement Support · Practical Projects · One-to-One Mentorship

Data Analytics Course in HyderabadExcel, SQL, Power BI and AI

Excel, SQL, Power BI and AI for data-driven decision making. A structured, hands-on program from CareerBridge Consultancy, Hyderabad.

DurationApprox. 12 Weeks
LevelBeginner to Advanced
Projects4 Practical Projects
FocusExcel + SQL + Power BI + AI
Course Overview

About the Data Analytics course

The Data Analytics programme teaches you to collect, clean, analyse and present data so that businesses can make better decisions. You will master Excel, SQL and Power BI, learn the statistics every analyst needs, and use AI tools to write queries, build formulas and generate insights faster.

What you will learn

  • Introduction to Data Analytics
  • Excel for Data Analysis
  • SQL for Data Analysis
  • Statistics for Analysts
  • Power BI: Data Preparation and Modelling
  • Power BI: DAX and Visualisation
  • Power BI Service and Collaboration
  • Data Storytelling and Visualisation
  • AI for Data Analytics
  • Capstone and Career Preparation

Who is this course for?

  • Graduates and freshers who want to start a career in data analytics
  • Working professionals who want to use data in finance, HR, sales, operations or marketing
  • Career switchers and professionals returning after a break
  • Business analysts and reporting professionals who want to upskill

Prerequisites

  • No prior experience required
  • Basic computer knowledge and comfort with numbers
  • A laptop or PC that can run Excel and Power BI Desktop (Windows recommended for Power BI Desktop)
Outcomes

What you will achieve

  • Understand the data analytics lifecycle and key business metrics
  • Clean, transform and analyse data in Excel with formulas, pivots and Power Query
  • Write SQL queries from basic to advanced, including joins and window functions
  • Apply core statistics to business problems
  • Build interactive dashboards and data models in Power BI with DAX
  • Tell clear stories with data and present insights to stakeholders
  • Use AI to speed up SQL, Excel, DAX and reporting while checking accuracy
  • Prepare a project portfolio and face analyst interviews confidently

Tools and technologies covered

  • Microsoft Excel
  • Power Query
  • SQL (MySQL / SQL Server / PostgreSQL)
  • Power BI Desktop and Service
  • DAX
  • Excel and Power BI Copilot features
  • AI assistants (Claude, ChatGPT, Copilot)

Career opportunities

  • Data Analyst
  • Business Intelligence Analyst
  • Reporting Analyst
  • Power BI Developer
  • MIS Analyst
  • Junior Business Analyst
  • Operations / Finance Analyst
  • Insights Analyst

Career outcomes depend on many factors and are not guaranteed.

Syllabus

Data Analytics course syllabus

A structured, hands-on curriculum from fundamentals to advanced topics. Every module includes practical exercises, assignments and mentor support.

Module 1Introduction to Data Analytics
  • Data analytics lifecycle
  • Descriptive, diagnostic, predictive and prescriptive analytics
  • Roles: Data Analyst, BI Developer, Business Analyst
  • Types of data: structured and unstructured
  • KPIs and business metrics
  • Turning business questions into analysis
  • Data quality and data governance basics
  • Industry use cases
Module 2Excel for Data Analysis
  • Formulas and functions: logical, text, date, math
  • Lookups: VLOOKUP, XLOOKUP, INDEX-MATCH
  • Data cleaning and validation
  • Sorting, filtering and conditional formatting
  • Pivot tables, pivot charts and slicers
  • Charts and visual best practices
  • Power Query for data transformation
  • Building interactive Excel dashboards
  • What-if analysis, Goal Seek and Solver
  • Introduction to macros and automation
Module 3SQL for Data Analysis
  • Database and relational model concepts
  • SELECT, WHERE, ORDER BY, LIMIT
  • Aggregations: COUNT, SUM, AVG, GROUP BY, HAVING
  • Joins: inner, left, right, full, self
  • Subqueries and Common Table Expressions (CTEs)
  • Window functions: ROW_NUMBER, RANK, LAG, LEAD, running totals
  • Data cleaning and date/string functions
  • CASE statements and conditional logic
  • Views, indexes and query performance basics
  • Real-world business query practice
Module 4Statistics for Analysts
  • Mean, median, mode, variance, standard deviation
  • Distributions and outliers
  • Correlation and regression basics
  • Sampling and confidence intervals
  • Hypothesis testing basics
  • A/B testing concepts
  • Interpreting results for business
Module 5Power BI: Data Preparation and Modelling
  • Power BI Desktop and Service overview
  • Connecting to Excel, SQL, CSV and web sources
  • Power Query transformations
  • Data modelling and star schema
  • Relationships, cardinality and filter direction
  • Calculated columns vs measures
  • Date tables and hierarchies
  • Data refresh and optimisation basics
Module 6Power BI: DAX and Visualisation
  • DAX fundamentals and syntax
  • CALCULATE, FILTER, ALL, VALUES
  • Time intelligence: YTD, MTD, previous period, growth %
  • Iterators: SUMX, AVERAGEX
  • Charts, maps, matrices, cards and KPIs
  • Slicers, drill-through, drill-down and tooltips
  • Bookmarks, buttons and navigation
  • Theme, layout and mobile view design
Module 7Power BI Service and Collaboration
  • Publishing reports to Power BI Service
  • Workspaces, apps and sharing
  • Row-Level Security (RLS)
  • Scheduled refresh and gateways overview
  • Dashboards, alerts and subscriptions
  • Governance and best practices
Module 8Data Storytelling and Visualisation
  • Choosing the right chart
  • Design principles: colour, layout, clutter reduction
  • Dashboard planning and wireframing
  • Writing insights and recommendations
  • Presenting to business stakeholders
  • Common visualisation mistakes
Module 9AI for Data Analytics
  • Prompt engineering for analysts
  • Generating and explaining SQL queries with AI
  • AI for Excel formulas, Power Query steps and cleaning ideas
  • Writing and debugging DAX measures with AI
  • Copilot features in Excel and Power BI (where available)
  • Summarising data and generating insight narratives
  • Verifying AI output: testing queries and reconciling numbers
  • Data privacy and responsible AI use
Module 10Capstone and Career Preparation
  • End-to-end capstone project
  • Portfolio and GitHub / Power BI publish tips
  • Data analyst resume and LinkedIn profile
  • SQL, Excel and Power BI interview questions
  • Case studies and scenario practice
  • Mock interviews, job-search strategy and referrals
Practical Projects

Build a portfolio with 4 practical projects

You will build these industry-style projects during the course and showcase them in your portfolio and interviews.

Project 1

Sales Performance Dashboard in Excel

Clean raw sales data with Power Query, analyse it with pivot tables and build an interactive dashboard with slicers and KPIs.

Skills and tools
Excel, Power Query, Pivot Tables, charts
Deliverables
Cleaned dataset and interactive Excel dashboard
Project 2

Retail Analysis with SQL

Answer real business questions on a retail database: top products, customer segments, monthly growth and repeat purchase behaviour.

Skills and tools
SQL joins, CTEs, window functions, aggregations
Deliverables
Query set with documented insights
Project 3

HR Analytics Dashboard in Power BI

Build a data model and DAX measures for attrition, hiring and workforce analysis, with drill-through, bookmarks and row-level security.

Skills and tools
Power BI, DAX, data modelling, RLS
Deliverables
Published report and presentation
Project 4

Capstone: End-to-End Analytics with AI

Take a business problem from raw data in SQL to a Power BI dashboard. Use AI to speed up queries, DAX and insight writing, then validate every result.

Skills and tools
SQL, Excel, Power BI, AI assistants
Deliverables
Portfolio-ready project, insight report and presentation
Mentorship

One-to-One Mentorship, Projects and Placement Support

Designed around career outcomes, not just theory. This support is part of the Data Analytics course.

One-to-One Mentorship

Guidance from experienced mentors throughout the programme.

  • Doubt clearing and learning guidance
  • Project reviews
  • Career planning
  • Interview preparation

Practical Projects

Hands-on, industry-style projects in every course, so you finish with a portfolio you can show to employers and discuss confidently in interviews.

  • Four practical projects per IT course
  • Built step by step with mentor support
  • Presented as part of your portfolio

Placement Support

  • Resume and LinkedIn profile review tailored to the role
  • Interview question banks, scenario practice and mock interviews with feedback
  • Portfolio and project presentation guidance
  • Guidance on job openings, application strategy and referrals
  • Ongoing mentor guidance until you are interview ready

Placement support is guidance and assistance. Job offers depend on the candidate's performance, market conditions and employer decisions and are not guaranteed. Contact us for the current mentorship schedule.

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FAQ

Data Analytics course FAQ

Common questions about the Data Analytics course in Hyderabad.

Do I need a technical background to learn data analytics?

No. The course starts from the basics and builds up. Comfort with numbers and logical thinking is enough.

Is programming (Python) required?

No. This course focuses on Excel, SQL, Power BI and AI. These tools are the foundation for most analyst roles.

Which version of SQL will I learn?

You will learn standard SQL concepts that apply across MySQL, SQL Server and PostgreSQL, so you can work with any of them.

Will I get Power BI hands-on practice?

Yes. You will build data models, write DAX, design dashboards and publish to Power BI Service.

How is AI used in this course?

AI helps you write and explain SQL, build Excel formulas and DAX, clean data and draft insights. You will also learn to validate AI output and protect sensitive data.

Will AI replace data analysts?

AI automates routine tasks, but analysts are still needed to ask the right questions, validate results and communicate insights. Analysts who use AI well are more productive.

Who can join this course?

Fresh graduates, working professionals, career switchers and anyone returning after a career break can join. No prior experience in this field is required unless stated in the prerequisites.

Is the AI content in the course useful for beginners?

Yes. AI is taught as a practical productivity tool, starting from simple prompting and building to real data analytics workflows. You will also learn how to verify AI output and protect confidential data.

What does placement support include?

We help with resume and LinkedIn preparation, mock interviews, interview question banks, portfolio guidance and job-search strategy. Placement support is assistance and guidance; we do not promise or guarantee a job offer.

How does the mentorship work?

You get access to experienced mentors who review your project work, clear doubts and help you plan your next career steps. Contact us for the current mentorship schedule.

Will I work on real projects?

Yes. Every course includes practical, industry-style projects. You will build them step by step and present them as part of your portfolio.

What are the batch timings, mode of training and fees?

These can vary by batch. Please message us on WhatsApp or email us and our team will share the latest schedule, mode of delivery and fee details.

Can I attend a demo session before enrolling?

Please contact our team to ask about upcoming demo or orientation sessions.

Will I receive a certificate?

Please contact our team for current certification details.

Contact Us

Enquire about the Data Analytics course

Have questions about our training programs, career counselling, mentorship, or placement services? Get in touch with our team in Hyderabad.

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