How Much Should You Know as a Data Analyst?

20.1: Transition from Power BI to Fabric

26.1: Final Quiz

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Hemanand Vadivel

Ex- Data Analytics Manager, 8+ Years in Europe, Microsoft Certified, Certified Supply Chain Professional

I’m a mechanical engineer who transitioned to a full time Data & Analytics manager in the UK & Germany by teaching myself Power BI, excel & anything else that was required to solve the problem. I have worked with complex data across Supply Chain, Sales, Marketing, Revenue Management, Finance and HR functions over the last 8 years to deliver effective solutions. To me, Analytics is an extra sensory organ that anyone can develop to become a superhuman at work. I have conducted several workshops and internal training to help non-technical people to become superhuman at work and now, really excited for this opportunity to share all that knowledge with you in this course.

How Much Should You Know as a Data Analyst?

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Contents

1: Welcome to The Power BI Experience

1.1: Welcome to Power BI 2.0

1.2: How Learning Power BI Can Help You in Your Career?

1.3: How This Course is Different From Other Courses Online

1.4: How to Get Support if I Have a Question?

1.5: Who Can Take this Course?

1.6: System Requirements

2: Enhance your Learning Experience

2.1: Join Discord

2.2: Setting Video Resolution and Video Speed Globally

3: Power BI Basics: Getting Started NEW

3.1: Install Power BI

3.2: Power BI: Tool Introduction

3.3: Power Query: Intro & Column Transformations

3.4: Power Query: Merging and Appending

3.5: Power Query: Best Practices

3.6: Introduction to DAX

3.7: Introduction to DAX - II

3.8: Introduction to Data Modeling

3.9: Introduction to Creating Visuals

3.10: Tony asks Peter to Fix Data Holes

3.11: Practice Exercise

3.12: Chapter Summary

3.13: Quiz

4: Project Planning and Scoping

4.1: Problem Statement

4.2: The Email that Started this Project

4.3: Project Kick-off Meeting

4.4: Learn how a ‘Project Charter’ is Used in Companies

4.5: Project Kick-off: Session Debrief

4.6: Senior Data Analyst Sets Up the Next Steps with Junior Data Analyst NEW

4.7: Simplified: Profit and Loss Statement

4.8: Chapter Summary

4.9: Quiz

5: Power BI Basics: Data collection, Exploration & Validation

5.1: Simplified: Data Warehouse, OLTP vs OLAP, Data Catalog

5.2: Install MySQL and Import Data

5.3: Simplified: Data Exploration Using SQL, Star Schema, Fact vs Dimension Tables

5.4: Load and connect data with MySQL

5.5: Create a Date Dimension Table

5.6: Validate Data against Benchmark Numbers

5.7: Tony’s Valuable Advise to Peter NEW

5.8: Practice Exercise

5.9: Chapter Summary

5.10: Quiz

6: Power BI Basics: Data Transformation in Power Query

6.1: Review Finance View Mockups

6.2: How to Enhance your Mockups

6.3: Transform Data in Power Query Editor

6.4: Create Calculated Columns in Power Query Editor

6.5: Power Query Best Practices

6.6: Peter Gets His Hands Dirty NEW

6.7: Practice Exercise NEW

6.8: Chapter Summary

6.9: Quiz

7: Get Your DAX Fear Removed NEW

7.1: Peter's Fear for DAX

7.2: DAX Behaviour: Filter Context

7.3: DAX: Using Calculate to Change Filter Context

7.4: All and ALLEXCEPT

7.5: Direct Filters and FILTER Function

7.6: DAX Calculated Column

7.7: Practice Exercise

7.8: Chapter Summary

7.9: Quiz

8: Power BI Advanced: Data Modeling & Calculated Columns

8.1: Power Query or DAX for Generating Calculated Columns?

8.2: Data Modelling: Star and Snowflake Schema

8.3: Data Modeling: Connect Dimensions with Fact Tables

8.4: Simplified: Why Do We Need Dimension Tables?

8.5: Mentor Talk: Congratulations! You are Levelling Up!

8.6: Create Calculated Columns Using DAX

8.7: Easy Way to Verify Your Numbers in Power BI

8.8: Assignment: Optimize Report and Reduce File Size by 25 %

8.9: I Need a Favour

8.10: Chapter Summary

8.11: Quiz

9: Power BI Advanced: Build Finance View

9.1: Finance View: Prepare a List of Metrics