Why this guide
- Built from the CompTIA Data+ DA0-001 exam objectives — 5 weighted domains, no filler
- SQL and statistics cheat sheet — the query patterns and formulas the exam tests most often
- Visualization do's and don'ts — chart selection and dashboard design for the scenario questions
- Designed for printing — full guide, two 1-page cheat sheets, and a 1-page pocket card
Who this is for
- Data analysts building reports and dashboards for business stakeholders
- Business intelligence analysts moving from ad-hoc reporting to certified analytics practice
- Marketing analysts who need a structured approach to data mining and visualization
- Junior data scientists who want a vendor-neutral analytics credential
- Career-changers entering data analytics roles without a four-year statistics degree
What you'll learn
- Domain 1 — Data Concepts and Environments (15%): Relational and non-relational databases, schemas, ETL/ELT, data warehousing, data lakes, big data basics
- Domain 2 — Data Mining (25%): Data collection, cleaning, profiling, transformation, feature selection, descriptive and diagnostic analytics
- Domain 3 — Data Analysis (23%): Statistical methods, hypothesis testing, correlation, regression, SQL queries, Python/R basics, analysis techniques
- Domain 4 — Visualization (19%): Chart types, dashboard design, storytelling, color/accessibility, tools, best practices and pitfalls
- Domain 5 — Data Governance, Quality and Controls (18%): Data stewardship, quality dimensions, master data management, privacy, compliance, ethics
- Core concepts: data lifecycle, structured vs unstructured, quantitative vs qualitative, dimensions vs measures
- SQL and statistics essentials: SELECT, JOIN, GROUP BY, aggregation, mean/median/mode, standard deviation, outliers
What you're getting
- 6 printable PDFs: cover, course notice, full study guide, two condensed cheat sheets, and an exam-day pocket card.
- Content built from the public syllabus and real test-taker accounts.
- No fake "actual exam" content — honest, source-cited study aids.
"Data Mining is the biggest domain. Expect cleaning, profiling, and transformation scenarios."
— paraphrased from public test-taker accounts