Examius
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Data Analytics Syllabus
Analyze and visualize data to support decision-making using analytical tools and techniques across the full analytics lifecycle.. The complete Data Analytics outline — 7 subjects, 37 chapters and 163 topics — laid out so you can see exactly what has to be covered and tick each item off as you go.
Data Analytics subjects
Each subject below has its own page with the full chapter → topic → sub-topic tree and a set of real exam-style flashcards.
5 chapters · 24 topics
Statistics and Probability for Analytics6 chapters · 26 topics
Data Wrangling and SQL6 chapters · 27 topics
Programming for Analytics with Python5 chapters · 22 topics
Exploratory Data Analysis and Visualization6 chapters · 27 topics
Predictive Analytics and Modeling5 chapters · 20 topics
Big Data and Modern Data Infrastructure4 chapters · 17 topics
Data Analytics flashcard decks
357 question-and-answer cards across 7 decks, written against this syllabus. Preview any deck free.
- Foundations of Data Analytics — 50 cards
- Statistics and Probability for Analytics — 51 cards
- Data Wrangling and SQL — 51 cards
- Programming for Analytics with Python — 50 cards
- Exploratory Data Analysis and Visualization — 53 cards
- Predictive Analytics and Modeling — 51 cards
- Big Data and Modern Data Infrastructure — 51 cards
How to work through the Data Analytics syllabus
The outline on this page is arranged the way the syllabus itself is: subject, then chapter, then topic, then sub-topic. That last level is what most study plans skip, and it is where coverage actually goes wrong — a chapter marked "done" often has three sub-topics inside it that were never touched.
Weight your plan accordingly: Data Wrangling and SQL carries 27 topics while Big Data and Modern Data Infrastructure carries 17. Giving both the same number of weeks is the most common planning mistake for Data Analytics.
The ~120 hour estimate above is a first pass only: roughly 45 minutes per topic plus 12 minutes per sub-topic. Revision cycles, past papers and mocks sit on top of that number.
Data Analytics syllabus FAQ
What subjects are in the Data Analytics syllabus?
Data Analytics covers 7 subjects: Foundations of Data Analytics, Statistics and Probability for Analytics, Data Wrangling and SQL, Programming for Analytics with Python, Exploratory Data Analysis and Visualization, Predictive Analytics and Modeling and Big Data and Modern Data Infrastructure. Together they contain 37 chapters and 163 named topics.
How much do you have to study for Data Analytics?
The full Data Analytics outline breaks down into 37 chapters, 163 topics and 0 sub-topics. Data Wrangling and SQL is the largest single subject with 27 topics across 6 chapters.
How long does it take to cover the whole Data Analytics syllabus?
Roughly 120 hours for one full pass. That estimate allows about 45 minutes per topic plus 12 minutes per sub-topic, so it is first-pass coverage — revision, past papers and mock tests sit on top of it. At 3 hours a day that is about 6 weeks.
Are there Data Analytics flashcards?
Yes — 357 question-and-answer flashcards across 7 decks, one per subject, written against this syllabus. A sample of every deck is readable on this site for free, and the complete decks are in the Examius app.
Is this Data Analytics syllabus free to use?
Yes. Every page here is free to read, and importing the Data Analytics syllabus into the Examius app to tick off topics as you finish them is free too. No account is needed to start.
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