How To Become A Data Analyst: Toolkit 101

Master Excel, Power BI, Tableau & Python by solving the same real-world problems across all four tools.

What you'll learn

Learn about basic data analysis tools such as Excel, PowerBI, Tableau, and Python

Understand how the various tools differ in their specialties

Be able to derive actional business insights from a given dataset

Understand how to do effective data visualisation

Experience a Pre-Employment Sample Technical Test for Data Analysts

Requirements

Interest to become a Data Analyst

Description

Want to stand out as a data analyst? This course gives you hands-on experience with Excel, Power BI, Tableau, and Python — showing you exactly how to answer real business questions in each tool.Instead of learning them in isolation, you’ll tackle the same set of real-world problems in all four platforms, so you can compare methods, understand strengths and limitations, and decide which tool is best for the task at hand.You’ll learn how to:Identify top-performing and underperforming tenants from raw sales dataCreate insightful charts to visualize customer trendsCalculate key metrics like total daily footfall, total revenue, and total profitsPresent findings in clear, compelling dashboards and reports that stand out to employersTo make your preparation even more practical, you’ll also get a sample technical test — just like the ones used in real analyst job interviews — so you can put your skills to the test before the big day.By the end of this course, you’ll have a multi-tool data analytics skillset you can confidently showcase in portfolios, interviews, and on the job. Whether you’re aiming for your first analyst role or leveling up your current career, this course will give you the skills, practice, and confidence to impress employers and land that next opportunity. You’ll be able to handle complex datasets, communicate insights clearly, and make data-driven decisions with measurable impact.Course Image Photo by Nick Morrison on Unsplash — many thanks to you!

Overview

Section 1: General Course Information

Lecture 1 Course Introduction

Section 2: Excel

Lecture 2 Setting up Excel

Lecture 3 COUNTA()

Lecture 4 Sorting in Excel

Lecture 5 Ploting Graph in Excel

Lecture 6 SUM()

Lecture 7 Pivot Tables in Excel

Lecture 8 Pivot Charts in Excel

Section 3: PowerBI

Lecture 9 Basic Introduction to PowerBI - Downloading, Setup, and Loading the Dataset

Lecture 10 Quick Power BI Insight: Counting Tenants in Seconds

Lecture 11 Finding Top/Worst Performing Tenants with Power BI

Lecture 12 Visualizing Footfall Data for Smart Retail Insights

Lecture 13 SUMMING in PowerBI

Lecture 14 Data aggregation: Category Analysis

Lecture 15 Comparing Categories: Average Cost per Item in Power BI

Section 4: Tableau

Lecture 16 Setting up Tableau

Lecture 17 Counting Tenants in Tableau

Lecture 18 Sorting (Tree Map, Highlight Table) in Tableau

Lecture 19 Bar Chart in Tableau

Lecture 20 Summing Aross Column in Tableau

Lecture 21 Data Aggregation (Sum) in Tableau

Lecture 22 Data Aggregation (Average) in Tableau

Lecture 23 Dashboarding in Tableau

Section 5: Python

Lecture 24 Python Set Up

Lecture 25 COUNT()

Lecture 26 Sorting in Pandas

Lecture 27 Bar Charts with matplotlib

Lecture 28 SUM() in pandas

Lecture 29 GROUPBY() in pandas

Lecture 30 Data Aggregation in Python

Section 6: Technical Test for Data Analysts

Section 7: Course Wrap Up

Lecture 31 Course Wrap Up: Next Steps

Beginners hoping to become a Data Analyst