Artificial Intelligence & Data Science
Power BI Data Analytics Course
3 Months
Advanced
Certified Course
Contact Us
+918160529351
info.nodetolearn@gmail.com
Surat, Gujarat
Course Overview
Raw data sitting in Excel files or databases means nothing until someone turns it into clear, visual reports that help businesses make decisions. That's exactly what Power BI does — and that's exactly what this course teaches you to do, hands-on, from day one.
At NodeToLearn, you learn in a 1-on-1 setup, not a crowded batch class. You work on a dedicated workstation at your own pace, with a mentor sitting next to you. You'll start by connecting Power BI to real data sources — messy Excel sheets, SQL databases, web data — then clean and shape that data using Power Query. From there, you'll build proper data models, write DAX formulas to calculate KPIs and time-based comparisons, and finally design dashboards that look professional and are easy for business teams to use.
The course also covers publishing reports to the cloud (Power BI Service), setting up automatic data refresh, controlling who sees what data using Row-Level Security, and using AI tools to speed up your DAX writing and analysis work. By the end, you'll have two complete, real-world dashboard projects in your portfolio — a Finance Dashboard and a Sales Performance Report — built entirely by you.
This program is built for people who want to actually do the job, not just watch someone else do it. No slideshows, no passive lectures. If you can use a laptop and understand basic Excel, you have enough to start here.
At NodeToLearn, you learn in a 1-on-1 setup, not a crowded batch class. You work on a dedicated workstation at your own pace, with a mentor sitting next to you. You'll start by connecting Power BI to real data sources — messy Excel sheets, SQL databases, web data — then clean and shape that data using Power Query. From there, you'll build proper data models, write DAX formulas to calculate KPIs and time-based comparisons, and finally design dashboards that look professional and are easy for business teams to use.
The course also covers publishing reports to the cloud (Power BI Service), setting up automatic data refresh, controlling who sees what data using Row-Level Security, and using AI tools to speed up your DAX writing and analysis work. By the end, you'll have two complete, real-world dashboard projects in your portfolio — a Finance Dashboard and a Sales Performance Report — built entirely by you.
This program is built for people who want to actually do the job, not just watch someone else do it. No slideshows, no passive lectures. If you can use a laptop and understand basic Excel, you have enough to start here.
Who is this for?
This course suits BCA, MCA, B.Com, and B.Tech graduates who want to move into a data analyst or BI developer role. It's also a good fit for working professionals — like operations managers, finance executives, or sales leads — who are already handling reports in Excel and want to move to something more powerful and visual. Commerce students curious about business intelligence can join too; you don't need a programming background. The only real requirement is that you're comfortable using a computer and understand basic spreadsheet concepts like rows, columns, and simple formulas.
Career Outcomes
- After completing this Power BI Data Analytics course
- students typically move into roles like Power BI Developer
- Business Intelligence Analyst
- Data Visualization Analyst
- MIS Reporting Executive
- or Corporate Data Analyst. Freelance consulting for small businesses that need dashboard setups is also a realistic path.
Course Curriculum
Data Importing & Cleaning with Power Query
- Setting up Power BI Desktop and understanding how the tool is organized — the Query Editor, Report view, Data view, and Model view.
- Connecting Power BI to different data sources: Excel files, CSV files, SQL databases, JSON files, and web URLs.
- Cleaning raw data in Power Query: fixing wrong data types, removing duplicate rows, splitting columns, replacing errors, and unpivoting tables.
- Using M Code (Power Query's scripting language) to write custom transformation steps and merge data from multiple sheets or files automatically.
Building a Data Model (Tables, Relationships & Schemas)
- Understanding the difference between fact tables (transaction data) and dimension/lookup tables (like product lists or customer names), and why this structure matters.
- Creating relationships between tables: one-to-many, many-to-many, active vs. inactive relationships, and setting the correct cross-filter direction.
- Designing a star schema layout to keep your model clean, fast, and easy to maintain — the standard used in professional BI work.
- Building a reusable Date Table from scratch so you can do time-based calculations like 'sales this month vs. last month' without errors.
Writing DAX (Data Analysis Expressions)
- Understanding how DAX works: the difference between a calculated column and a measure, and when to use each one.
- Using the CALCULATE function to override filters and build measures that respond to slicers and report context dynamically.
- Writing time intelligence functions: Year-to-Date (YTD), Quarter-to-Date (QTD), Month-to-Date (MTD), and Same Period Last Year comparisons.
- Building conditional logic with IF, SWITCH, and VAR statements to create custom KPIs, error handling, and business-specific calculation rules.
Dashboard Design & Publishing to the Cloud
- Designing clean, professional dashboard layouts: choosing the right chart types, using consistent colors and fonts, and making reports easy to read at a glance.
- Adding interactivity: bookmarks, page navigation buttons, drill-through pages, custom tooltips, slicers, and toggle views.
- Publishing your reports to Power BI Service (the cloud), setting up automatic data refresh schedules, and connecting on-premise data through a gateway.
- Setting up Row-Level Security (RLS) so different users (like regional managers vs. executives) only see the data they are allowed to see.
AI-Assisted Analysis & Portfolio Projects
- Using AI tools and large language models (like ChatGPT) to generate DAX code, debug formula errors, and speed up repetitive BI tasks — without replacing your understanding of the logic.
- Using Power BI's built-in AI features: Q&A visuals (ask questions in plain English and get a chart), anomaly detection, and smart narrative summaries.
- Building Project 1: a complete Operational Finance Dashboard — tracking revenue, expenses, and profitability across time periods with interactive filters.
- Building Project 2: a Sales Performance Management Report — tracking targets vs. actuals by region, product, and salesperson, ready to show in interviews or client meetings.