Analytics Made Simple

Learn

Step-by-step guides for SQL, tools, and practical AI — skills you can use at work. Learn by doing, not by jargon.

Series

Step-by-step paths grouped by topic. Start at part 1 and work through at your pace.

Foundations

How analytics works and how everyday data becomes structured.

Series From spreadsheets to real data Excel and Sheets habits that scale: when a file becomes a liability, real tables, keys, cleaning, clean exports, and a one-page table contract. 6 parts · View series → Series Analytics foundations Questions before data — learn to define the problem so every chart and query actually helps someone decide. 5 parts · View series →

Core skills

SQL, Python, data quality, charts, and metrics — skills you reuse everywhere.

Series Charts that make sense Make charts that answer decisions: purpose, chart choice, honest axes, accessible color, dashboards vs slides, annotation, and chart crime fixes. 7 parts · View series → Series Data quality for people who ship numbers Hands-on data quality for analysts who ship numbers: dimensions, profiling, dedupe, standards, time, checks, and a light scorecard. 7 parts · View series → Series Metrics that matter From goals to metric specs, leading signals, North Star design, incentive traps, and review meetings that actually decide something. 6 parts · View series → Series SQL series Step-by-step SQL — from playground setup through joins, subqueries, and optimization. 14 parts · View series → Series Python for analytics Clean data, explore with pandas, and turn notebooks into reusable analysis you can trust at work. 12 parts · View series →

Data at work

Pipelines, stewardship, and how data moves through real teams.

Series Data stewardship at work A six-part series on weekly data habits: roles, catalogs, access, incidents, retention, and working with Legal and Security without panic. 6 parts · View series → Series How data actually moves A seven-part series for analysts who inherit pipelines: path, latency, storage homes, orchestration, dbt concepts, environments, and observability. 7 parts · View series →

AI fundamentals

Practical AI for everyday work — product-agnostic judgment and workflows.

Series AI setup from zero Accounts, payments, apps, and where your files go. Start on Free. Pay on the website. One vendor at a time. 5 parts · View series → Series Open-source AI explained What open means for models: weights, licenses, and the homework of running things yourself. Not a free lunch. 10 parts · View series → Series Practical AI for analytics people A nine-part series for analysts: what AI can and cannot do, tokens, prompts, evals, RAG, agents, privacy, documentation, and a personal ops checklist. 9 parts · View series → Series Run open models from scratch Hosted open-model chat, desktop runners, one local stack, offline tasks, hardware, updates, and sharing a machine with family. 7 parts · View series → Series Which AI product should I use? Pick a chat box, a coding agent, an office helper, or a local model by the job, not the brand name. 6 parts · View series →

AI products

One complete path per brand: first login through deep tools. Official product logos.

Anthropic Claude Anthropic Claude from first login through product map, Claude Code, and Cowork — one continuous path. 31 parts · View series → OpenAI ChatGPT OpenAI ChatGPT from everyday chat through product map, Work mode, Codex, and Custom GPTs — one continuous path. 30 parts · View series → Google Gemini Google Gemini from first login through product map, Workspace, and coding surfaces — one continuous path. 26 parts · View series → xAI Grok A 24-part path into xAI Grok: getting started, product map (chat vs Build vs Imagine vs API), everyday writing and verification, Grok Build in the terminal, and Imagine for images and short video. 24 parts · View series → Meta Meta Llama from scratch Llama is a family of open-weight models from Meta, not a chatbot app. Map the family, the license, and when a $20 closed chat is easier. 1 part · View series → DeepSeek DeepSeek from scratch DeepSeek is a Hangzhou lab with a free chat app and open weights. Separate the product from the files you can download. 1 part · View series → Alibaba Qwen from scratch Qwen is Alibaba's model family: chat surfaces, open weights, and a huge multilingual line. Start with the map, not the zoo. 1 part · View series → Moonshot Kimi from scratch Kimi is Moonshot's assistant, famous for long context. The app, the K2/K3 weights, and what long context actually buys you. 1 part · View series → Z.ai GLM from scratch GLM is Zhipu's (Z.ai) family, including the GLM-5.x era. ChatGLM heritage, chat.z.ai, open weights, coding plans. 1 part · View series →

Analytics practice

Stats, experiments, customer and finance analytics, and career paths.

Series Analyst career path IC ladder, portfolio, and storytelling toward senior trust. 3 parts · View series → Series Customer analytics basics Funnels, conversion math, and cohorts for product analysts. 3 parts · View series → Series Experimentation culture Design, guardrails, and decision reviews beyond pure stats. 3 parts · View series → Series Finance analytics for non-finance ARR, churn, and cohort retention with careful definitions. 3 parts · View series → Series Geospatial for beginners When maps help and how to avoid misleading them. 2 parts · View series → Series Inclusive data products Accessibility and whose story your metrics miss. 2 parts · View series → Series Statistics for analysts Bias, sampling, uncertainty, and A/B intuition without the math degree. 4 parts · View series →

BI & workflow tools

Hands-on starters for Power BI, dbt, Airflow, and similar tools.

Microsoft Power BI starter Model, measures, and trustworthy publish for beginners. 3 parts · View series → Apache Airflow hello DAG First DAG, retries, sensors, and when not to use Airflow. 2 parts · View series → dbt Labs dbt project lab Hands-on layout, models, tests, and PR review. 3 parts · View series →

More series

Additional paths that do not fit a section yet.

Series AI agents for everyone An agent is a chat that can take steps. Watch, approve, or walk away on purpose. Check the work without being an engineer. 5 parts · View series → Series AI safety for everyday life Scams, deepfakes, school honesty, health and money limits, kids on shared devices, and the job skills that still matter. 5 parts · View series → Series Memory, projects, and files across AI tools Chat history is not memory. Projects are not a folder. Learn where uploads go and how to turn a messy directory into a working project. 4 parts · View series → Series Prompting for everyone Talk to AI like a clear human. Context, constraints, examples, iteration, and when to stop prompting and do the work yourself. 5 parts · View series →