Curriculum
Data Analytics
Module 1: Foundation of Data & Spreadsheet
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Module 1 Intro: Foundations of Data & Spreadsheets
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Welcome to Week 1: The Data Analyst Mindset
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Week 1.1: Defining the Raw Material: What is Data?
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Week 1.2: The Analytical Blueprint: The Data Lifecycle
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Week 1.3: The Professional Landscape: Roles, Responsibilities, and Tools
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Week 1.4: The Analyst Mindset: Learning How to Learn
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Week 1 Assessment: Introduction to Data Analytics Fundamentals
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Week 1 Assignment: Introduction to Data Analytics Fundamentals
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Week 1 Module Completion and Next Steps
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Welcome to Week 2: Spreadsheet Basics
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Week 2.1: Getting Started with Excel: The Foundation
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Week 2.2: Understanding and Formatting Data Types
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Week 2.3: Data Quality: Filtering, Cleaning, and Validation
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Week 2 Assessment: Spreadsheet Basics
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Week 2 Assignment: Introduction to Data Analytics Fundamentals
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Week 2 Module Completion and Next Steps
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Welcome to Week 3: Calculations, Logic, and Lookups
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Week 3.1: The Formulas Tab: Your Calculation Command Center
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Week 3.2: Mathematics & Conditional Logic: Making Data Decisions
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Week 3.3: Data Transformation and Formatting of Time and Text
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Week 3.4: Data Transformation and Formatting of Time and Text
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Week 3 Assessment: Calculations, Logic, and Lookups
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Week 3 Assignment: Comprehensive Sales Analysis & Reporting
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Week 3 Module Completion and Next Steps
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Welcome to Week 4: Pivot Tables & Visual Storytelling
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Week 4.1: Pivot Tables: Summarization on Demand
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Week 4.2: Data Visualization with Charts
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Week 4.3: Building Interactive Dashboards
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Week 4.4: Excel is a powerful tool: you’ve only scratched the surface
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Week 4 Assessment: Pivot Tables & Visual Storytelling Fundamentals
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Week 4 Final Portfolio Project: Sales Performance Dashboard
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Week 4 Module Completion and Next Steps
Module 2: Data Management With SQL
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Module 3: Data Visualisation with Power BI
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Module 4: Business Problem Solving & Communications
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Module 5: Capstone Project
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Mock Exam
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Welcome to Week 2: Spreadsheet Basics
Our Focus this week: Taming the Data
We’ll cover the essential, practical skills needed to take any raw dataset and prepare it for deeper analysis:
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Environment Mastery: Navigating the Excel interface (ribbons, cells, formula bar) and properly importing data.
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Organization & Formatting: Applying correct data types (currency, dates, text) and efficiently managing the structure (rows and columns).
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Data Cleaning Essentials: Implementing filters, sorting, and crucial techniques like removing duplicates and using data validation to ensure data quality.
By the end of this week, you’ll have practical skills directly mapped to the Processing stage of the Data Analytics Lifecycle we discussed last week.
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Week 1 Concept |
Week 2 Practical Skill |
Why It Matters |
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The Processing Stage |
Data Cleaning, Validation, and Formatting |
Garbage In, Garbage Out (GIGO): Clean data leads to reliable insights. Poorly formatted or inconsistent data leads to incorrect conclusions and wasted effort. |
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Structured Data |
Using Tables, Filters, and Sorting |
Structured data is easy to query. We use Excel’s table features to enforce structure, making subsets and quick analysis simple and reliable. |
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Data Analyst Responsibility |
Efficiency in Navigation and Data Management |
An analyst must be fast. Mastering keyboard shortcuts and interface navigation allows you to process data in minutes, not hours. |
Expected Outcomes
Your work this week will be foundational, you will be well on your way to earning your stripes as a data preparation expert:
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You will develop foundational spreadsheet skills for data organization and preparation.
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You will be able to take a raw, messy dataset and transform it into a clean, structured format ready for analysis.
Set up Requirement: Get Ready to Work!
To follow along with this week’s labs, you must have access to Microsoft Excel.
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For students with a pre-installed version: Please open Excel and ensure the software is activated and up-to-date.
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For those who need to install it: Please use [this link to the official Microsoft 365 download page] and follow the instructions to install the desktop application.
Let’s dive in and get our hands on some data!