📊 Analyze Data
0.5.dev0+git.20260720.c8f33de - July 20, 2026 16:01 UTC

📊 Analyze Data

Section 5 of the Data Analytics hub — 30 of 30 lessons.

Organising, formatting, aggregating, and computing on data to surface patterns and answer the question.

↑ Back to the Data Analytics hub

🗂️ Organizing & Formatting Data

Sorting, filtering, formatting, validating, and string work in sheets and SQL.

• 001 · Understanding Data Analysis — what analysis actually is: the four phases that turn prepared data into insight

• 002 · Data Organization in Analysis — arranging data so analysis is possible — the organising step before any computation

• 003 · Sorting and Filtering in Data Analysis — the two foundational moves of analysis, and how they differ from cleaning uses

• 004 · Sorting Data in Spreadsheets — ordering rows by one or more columns to surface structure — done safely

• 005 · Sorting and Filtering Data in SQL Using ORDER BY and WHERE — the SQL twins of sort and filter: ORDER BY to order, WHERE to subset

• 006 · Data Formatting and Unit Conversion in Spreadsheets — consistent formats and units — making numbers comparable before analysing them

• 007 · Data Validation in Spreadsheets — rules that constrain what a cell may hold, catching and preventing bad data

• 008 · Combining Data Validation and Conditional Formatting in Spreadsheets — validation to enforce rules, formatting to reveal violations — used together

• 009 · Using CONCAT in SQL to Combine Text from Multiple Columns — joining text from several columns into one — CONCAT and the concatenation operator

• 010 · Working with Strings in Spreadsheets (LEN, LEFT, RIGHT, FIND) — the spreadsheet string toolkit for measuring, extracting, and locating text

🔗 Problem-Solving & Combining Data

Getting unstuck, choosing tools, and joining data with VLOOKUP, JOIN, and subqueries.

• 011 · Problem-Solving and Seeking Help in Data Analysis — the analyst’s debugging mindset, and how to ask for help effectively

• 012 · How to Effectively Search for Solutions Online as a Data Analyst — turning an error or a stuck point into a search that actually finds the answer

• 013 · Choosing the Right Tool in Data Analysis — matching the task to spreadsheet, SQL, or programming — and combining them

• 014 · Preparing Data for VLOOKUP in Spreadsheets — the setup VLOOKUP demands: a clean lookup key in the leftmost column

• 015 · Using VLOOKUP to Combine Data Across Spreadsheets — pulling matching values from another table by a shared key

• 016 · Troubleshooting VLOOKUP and Building a Problem-Solving Framework — why VLOOKUP fails, how to fix it, and a reusable debugging framework

• 017 · Using JOIN in SQL to Combine Tables — combining rows from multiple tables on a matching key — SQL’s core combine

• 018 · Subqueries in SQL — a query nested inside another — using one query’s result within a second

• 019 · Aggregating Data with Subqueries, HAVING, and CASE in SQL — combining aggregation, group filtering, and conditional logic for real analysis

🧮 Calculations & Aggregation

Formulas, conditional aggregation, pivot tables, and SQL GROUP BY calculations.

• 020 · Using Spreadsheet Formulas for Sales Trend Analysis — formulas for change over time — growth rates, running totals, period comparisons

• 021 · Using COUNTIF and SUMIF for Conditional Aggregation in Spreadsheets — counting and summing only the rows that meet a condition

• 022 · Using SUMPRODUCT for Advanced Spreadsheet Calculations — multiplying and summing across arrays in one formula — weighted and multi-condition sums

• 023 · Using Pivot Tables for Calculations and Trend Analysis — the spreadsheet’s most powerful summarising tool — grouping and aggregating with drags

• 024 · Using Pivot Table Filters and Calculated Fields for Deeper Analysis — filtering a pivot and adding computed fields — pushing pivots past basic summaries

• 025 · Comparing Calculations in Spreadsheets and SQL — the same aggregate two ways — when each tool suits the calculation

• 026 · Embedding Calculations in SQL Queries — computing derived values inside a query — arithmetic and expressions in SELECT

• 027 · Using GROUP BY and ORDER BY for Aggregated Calculations in SQL — the SQL pivot: grouping to aggregate, ordering the summary

🚀 Validation & Temporary Tables

Ongoing validation and temporary tables with WITH for cleaner SQL workflows.

• 028 · Data Validation as an Ongoing Analytical Process — validation not as a one-time gate but a continuous check throughout analysis

• 029 · Temporary Tables and the WITH Clause in SQL — holding intermediate results — CTEs and temp tables that structure complex queries

• 030 · Creating Temporary Tables in SQL — Methods, Trade-offs, and Best Practices — the ways to make a temp table, when each fits, and how to use them well

🔤 Every lesson, A–Z index

🔠 Open the full alphabetical index

Aggregating Data with Subqueries, HAVING, and CASE in SQL Choosing the Right Tool in Data Analysis Combining Data Validation and Conditional Formatting in Spreadsheets Comparing Calculations in Spreadsheets and SQL Creating Temporary Tables in SQL — Methods, Trade-offs, and Best Practices Data Formatting and Unit Conversion in Spreadsheets Data Organization in Analysis Data Validation as an Ongoing Analytical Process Data Validation in Spreadsheets Embedding Calculations in SQL Queries How to Effectively Search for Solutions Online as a Data Analyst Preparing Data for VLOOKUP in Spreadsheets Problem-Solving and Seeking Help in Data Analysis Sorting and Filtering Data in SQL Using ORDER BY and WHERE Sorting and Filtering in Data Analysis

Sorting Data in Spreadsheets Subqueries in SQL Temporary Tables and the WITH Clause in SQL Troubleshooting VLOOKUP and Building a Problem-Solving Framework Understanding Data Analysis Using CONCAT in SQL to Combine Text from Multiple Columns Using COUNTIF and SUMIF for Conditional Aggregation in Spreadsheets Using GROUP BY and ORDER BY for Aggregated Calculations in SQL Using JOIN in SQL to Combine Tables Using Pivot Table Filters and Calculated Fields for Deeper Analysis Using Pivot Tables for Calculations and Trend Analysis Using Spreadsheet Formulas for Sales Trend Analysis Using SUMPRODUCT for Advanced Spreadsheet Calculations Using VLOOKUP to Combine Data Across Spreadsheets Working with Strings in Spreadsheets (LEN, LEFT, RIGHT, FIND)

Tags: purpose: reference topic: data analytics