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GATE 2026 Data Analytics Syllabus: Your Complete Guide

Ritik Kumar Ritik Kumar · October 4, 2025
A laptop is shown on a desk displaying a data analytics dashboard. The screen features various charts, including bar graphs, line charts, and pie charts, all representing statistical data. The left sidebar of the dashboard lists audience segmentation options such as country, city, status, sex, age, interests, collaboration, behavior, technology, mobile, and custom inputs, among others. In the top left corner of the screen, the logo for "Career Plan Analytics" is visible, featuring a green and blue circular design with a stylized arrow. On the lower right side of the image, bold white text reads: "GATE 2026 Data Analytics Syllabus: Your Complete Guide.” The background and lighting suggest a professional and modern workspace, with a blue hue illuminating the scene.

Introduction

Data Analytics is emerging as a highly sought-after discipline in engineering and technology. GATE 2026 Data Analytics exam evaluates your understanding of statistical methods, machine learning, and data mining along with core programming and maths knowledge. This guide breaks down the exam pattern, syllabus topics, and preparation strategies to help you excel in this rapidly evolving field.

Exam Pattern at a Glance

The GATE Data Analytics paper is a 3-hour computer-based test with 100 marks and 65 questions:

  • General Aptitude (15 Marks): 10 questions testing verbal and numerical ability
  • Engineering Mathematics (13 Marks): Approx. 9 questions covering calculus, linear algebra, etc.
  • Data Analytics Core (72 Marks): Around 46 questions from key subject areas

Download the official GATE Data Analytics 2026 syllabus PDF here: https://gate2026.iitg.ac.in/doc/GATE2026_Syllabus/DA_2026_Syllabus.pdf

1: General Aptitude (15 Marks)

  • Verbal ability including vocabulary and grammar
  • Numerical ability such as arithmetic, percentages, ratios

2: Engineering Mathematics (13 Marks)

  • Linear algebra: vectors, matrices, eigenvalues
  • Calculus: differentiation, integration, optimization
  • Probability & Statistics: basic probability, distributions, hypothesis testing

3: Data Analytics Core (72 Marks)

Data Management and Processing (15–18%)

  • Data cleaning, transformation, and normalization
  • Data warehouses, data lakes, and big data concepts

Statistical Methods (15–18%)

  • Descriptive statistics, correlation, regression
  • Bayesian inference, sampling, confidence intervals

Machine Learning and Data Mining (20–25%)

  • Supervised and unsupervised learning algorithms
  • Clustering, classification, dimensionality reduction
  • Evaluation metrics and model validation

Data Visualization (7–10%)

  • Visualization principles, tools, and techniques
  • Dashboard design and visual analytics

Data Analytics Applications (7–10%)

  • Applications in business, healthcare, finance
  • Case studies and real-world problem-solving

Topic-Wise Weightage Distribution

Section Weightage (%) Approx. Questions
General Aptitude 15 10
Engineering Mathematics 13 9
Data Management & Processing 15–18 10–12
Statistical Methods 15–18 10–12
Machine Learning & Data Mining 20–25 13–16
Data Visualization 7–10 5–7
Data Analytics Applications 7–10 5–7

Preparation Strategy

  • Prioritize Machine Learning and Statistical Methods due to their larger weightage.
  • Strengthen Engineering Mathematics and General Aptitude with daily practice.
  • Use previous years’ question papers to familiarize yourself with question patterns.
  • Take full-length mock tests under timed conditions.
  • Maintain an error log and revisit weak areas regularly.

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 With over 16 years of expertise, we provide:

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  • Backup Strategies – Alternative options to ensure you never miss opportunities

Book your free counselling session today to take your GATE Data Analytics preparation to the next level!

Frequently Asked Questions (FAQs)

Q1: Where can I download the official GATE 2026 Data Analytics syllabus?
 A1: Download the official PDF here: https://gate2026.iitg.ac.in/doc/GATE2026_Syllabus/DA_2026_Syllabus.pdf

Q2: Which topics carry the highest weightage in GATE Data Analytics?
 A2: Machine Learning & Data Mining (20–25%), Statistical Methods (15–18%), and Data Management & Processing (15–18%) are key sections.

Q3: How many questions are there from Engineering Mathematics?
 A3: Approximately 9 questions (13 marks) cover foundational math topics.

Q4: Are there negative markings?
 A4: Yes, 1/3 mark deduction for wrong 1-mark MCQs and 2/3 mark for wrong 2-mark MCQs; no penalty for MSQ and NAT questions.

Q5: How many mock tests should I take?
 A5: Aim for 15–20 full-length mock tests along with practice quizzes to monitor progress.

Conclusion

A consistent, structured approach focusing on key data analytics topics, reinforced with math and aptitude practice and mock testing, will prepare you well for GATE 2026 Data Analytics. Download the official syllabus PDF and start your preparation today!

For expert career guidance, contact Career Plan B.

 

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