🌱 Foundations
0.5.dev0+git.20260720.c8f33de - July 20, 2026 16:01 UTC

🌱 Foundations

Section 1 of the Data Analytics hub — 27 of 27 lessons.

The case for data, the analysis process and data life cycle, analytical thinking, and the core tools of the trade.

↑ Back to the Data Analytics hub

🌟 Why Data Analytics

Why data matters today and how it reshapes work and decision-making.

• 001 · Why Data Analytics Matters Today — why organisations that decide with data outperform those that decide by instinct

• 002 · How Data Analytics Improves the Workplace — where analytics pays off day to day: operations, decisions, and shared facts

• 003 · Data-Driven Decision-Making — the loop from question to data to decision, and the evidence it works

• 004 · Detectives and Data Analysts — the investigator’s mindset: questions, evidence, and conclusions that hold up

🔄 The Analysis Process & Data Life Cycle

The six phases of analysis and the life cycle data moves through.

• 005 · The Six Phases of the Data Analysis Process — ask, prepare, process, analyze, share, act — the map for every project in this course

• 006 · The Origins of Data Analysis and the Many Ways to Structure It — from early statistics to EDA and CRISP-DM: one process, many framings

• 007 · Understanding the Data Ecosystem — the interlocking pieces — sources, storage, tools, people — data moves through

• 008 · Understanding the Data Analysis Process and the Data Life Cycle — two different journeys: what the analyst does vs. what happens to the data

• 009 · Understanding the Data Life Cycle — plan, capture, manage, analyze, archive, destroy — the data’s own biography

• 010 · A Review of the Six Stages of the Data Life Cycle — the six stages consolidated, with what can go wrong at each

• 011 · The Stages of the Data Analysis Process and Their Roles — what each analysis phase contributes, and what it hands to the next

• 012 · Practical Application of the Data Analysis Process — the six phases run end-to-end on a real-shaped business case

🧠 Analytical Skills & Thinking

Analytical skills, structured questioning, and root-cause methods.

• 013 · Analytical Skills and Their Core Components — the five skills — curiosity, context, technical mindset, data design, data strategy

• 014 · Applying Analytical Skills in a Business Context — the five skills at work on a real business problem, phase by phase

• 015 · Analytical Thinking and Its Core Components — the five aspects — visualization, strategy, problem-orientation, correlation, big picture + detail

• 016 · Analytical Thinking and Questions for Problem Solving — turning the aspects into questions: root causes, gaps, and the unconsidered

• 017 · Root Cause Analysis and Business Applications of the Five Whys — Toyota’s why-times-five: digging past symptoms to causes worth fixing

• 018 · Data-Driven Decision-Making and the Role of Analytical Skills — how the five skills power each step of the decision loop

• 019 · Case Studies in Data Analysis and the Practical Impact of Data-Driven Decision-Making — the evidence in action: research findings and worked cases where data changed the outcome

🧰 Tools, Applications & Ethics

Spreadsheets, SQL, visualization, industry uses, and fairness.

• 020 · Overview of Core Tools Used by Data Analysts — the working toolkit — spreadsheets, SQL, visualization tools, and code — and when each fits

• 021 · The Role of Spreadsheets in Data Analysis and Basic Concepts — the analyst’s first instrument: cells, formulas, and functions in a visible grid

• 022 · The Concept and Basic Use of SQL (Query Language) — asking databases questions: SELECT, FROM, WHERE and why they scale

• 023 · The Role and Importance of Data Visualization — why pictures beat tables: seeing structure that summary numbers hide

• 024 · Industries Where Data Analysts Work and How Data Is Used — the same craft in many rooms: retail to healthcare to public service

• 025 · The Role of Business Tasks in Data Analysis — the question behind the work: how business tasks anchor every analysis

• 026 · Fairness in Data Analysis — analysis that does not create or reinforce bias — and a famous failure to learn from

• 027 · Key Factors to Consider When Choosing a Data Analytics Role — industry, company size, specialisation, growth: weighing where to start

🔤 Every lesson, A–Z index

🔠 Open the full alphabetical index

A Review of the Six Stages of the Data Life Cycle Analytical Skills and Their Core Components Analytical Thinking and Its Core Components Analytical Thinking and Questions for Problem Solving Applying Analytical Skills in a Business Context Case Studies in Data Analysis and the Practical Impact of Data-Driven Decision-Making Data-Driven Decision-Making Data-Driven Decision-Making and the Role of Analytical Skills Detectives and Data Analysts Fairness in Data Analysis How Data Analytics Improves the Workplace Industries Where Data Analysts Work and How Data Is Used Key Factors to Consider When Choosing a Data Analytics Role Overview of Core Tools Used by Data Analysts

Practical Application of the Data Analysis Process Root Cause Analysis and Business Applications of the Five Whys The Concept and Basic Use of SQL (Query Language) The Origins of Data Analysis and the Many Ways to Structure It The Role and Importance of Data Visualization The Role of Business Tasks in Data Analysis The Role of Spreadsheets in Data Analysis and Basic Concepts The Six Phases of the Data Analysis Process The Stages of the Data Analysis Process and Their Roles Understanding the Data Analysis Process and the Data Life Cycle Understanding the Data Ecosystem Understanding the Data Life Cycle Why Data Analytics Matters Today

Tags: purpose: reference topic: data analytics