Data Analytics Syllabus 2022: Subjects, Course-wise, Books, Skills (2022)

Data Analytics course syllabus includes topics and practical exercises that can teach students how to extract, analyze, and manipulate data to draw conclusions or insights. It also teaches about various Data Analytics tools and software that help in the analysis of data. Hence, the essential Data Analytics subjects include Probability and Statistics, Data Structures and Algorithms, Data Simulation, Data Collection, and similar.

As Data Analytics courses are available at different levels (diploma, certificate, undergraduate, and postgraduate), the combination of different data analytics subjects and the Data Analytics course curriculum may vary. The important subjects in Data Analytics included in almost every kind of Data Analytics program aretypes of Data Analytics, Statistical Analysis, Excel, SQL, Tableau, Power BI, etc. Expertise in Data AnalyticsTools and languages such as Python, Machine Learning, Big Data, and SQL is beneficial, as these are the top listed skills for the Data Analytics job profiles as per the top job listing websites.

Data Science Course SyllabusBusiness Analytics Course Syllabus
Python Course SyllabusJava Course Syllabus

The Elements of Data Mining, Statistical Learning, Inference, and Prediction,Data Analysis Software: Programming with R (Statistics and Computing), and Probability & Statistics for Engineers & Scientists are the top data analytics books recommended by experts and professionals in the field of data analytics.

Table of Contents

  1. Data Analytics CourseSyllabus 2022

1.1Big Data Analytics Syllabus

1.2BSc Computer Science with Data Analytics Syllabus

1.3MBA in Data Analytics Syllabus

1.4BSc Data Analytics Syllabus

  1. Data Analytics Subjects

2.1Data Structure and Algorithms

2.2Probability and Statistics

2.3Business Fundamentals

2.4Text Analytics

2.5Data Collection

2.6Data Visualization

  1. Top Data Analytics Skills in 2022

3.1Python

3.2Microsoft Excel

3.3R Programming

3.4SQL

3.5 Machine Learning

  1. Top Data Analytics Books
  2. Top Data Analytics Tools and Software
  3. Data Analytics Syllabus: FAQs

Data Analytics Course Syllabus 2022

The Data Analytics course syllabus may differ from course to course or curriculum to curriculum but there are a few common data analytics subjects that are mentioned below:

Data Structures and AlgorithmsSupply Chain Analytics
Probability and StatisticsCustomer Analytics
Relational Database Management SystemsRetail Analytics
Business FundamentalsSocial Network Analysis
Text AnalyticsPricing Analytics
Data CollectionMarketing Analytics
Data VisualizationOptimization
Statistical AnalysisMachine Learning
Forecasting AnalyticsSimulation

Big Data Analytics Syllabus

Big Data Analytics is the process of extracting useful information from huge volumes of data. This includes finding hidden patterns, market trends, future predictions, and correlations. The following table mentions the MSc Big Data Analytics syllabus from St. Xavier’s University, Mumbai. A similar Big Data Analytics curriculum is usually followed in all of the colleges. Check: Top 10 Big Data Analytics Courses Online in 2022

Semester ISemester II
Statistical MethodsFoundations of Data Science
Probability & Stochastic ProcessAdvanced Statistical Methods
Linear Algebra & Linear ProgrammingMachine Learning I
Computing for Data Sciences using R, Python, and JavaEnabling Technologies for Data Science I (Theory & Lab)
Database Management – Relational and Non-RelationalValue Thinking
Python Programming (Theory & Lab)Elective Course
Semester IIISemester IV
Enabling Technologies for Data Science 2 (Theory & Lab)Internship based Project work
Machine Learning 2 including Deep Learning-
Data Visualization with Tableau-
Modeling in Operations Management-
Elective Courses-

BSc Computer Science with Data Analytics Syllabus

The following table mentions the BSc Computer Science with Data Analytics syllabus followed by Bharathiar University, Tamil Nadu. The other colleges also follow the same curriculum. The electives offered might be different.

Semester ISemester II
Language - ILanguage - II
English - IEnglish - II
Programming in CProgramming in C++
Programming Lab - CInternet Basics Lab
Data StructuresDiscrete Mathematics
Introduction to Linear AlgebraValue Education – Human Rights
Environmental Studies-
Semester IIISemester IV
Java ProgrammingPython Programming
Java Programming - LabData Warehousing & Data Mining
Database Management SystemsPython Programming Lab
Data Communication & NetworksDeep Learning
Data VisualizationCapstone Project Work Phase I
Elective CourseElective Course
Semester VSemester VI
R ProgrammingLinux & Shell Programming
R Programming LabLinux & Shell Programming Lab
Big Data AnalyticsProject Work Lab
Elective CourseElective Course I
Capstone Project Work Phase IIElective Course II
-Elective Course III
-Machine Learning
-Extension Activities

MBA in Data Analytics Syllabus

The following table mentions the MBA in Data Analytics syllabus followed by Sharda University, Greater Noida. The other colleges also follow the same curriculum. The electives offered might be different. Also Check: Top MBA in Data Analytics Colleges 2022

Semester ISemester II
Accounting for ManagersApplied Operations Research
Applied Statistics for Decision MakingData Cleaning, Normalization and Data Mining
Financial Analysis and ReportingEconometrics
Macroeconomics in the Global EconomyFoundation course in Business Analytics
Organizational BehaviorProject Management
Research MethodologySpreadsheet Modeling
Semester IIISemester IV
Applied Business AnalyticsEthical and Legal Aspects of Analytics
Foundation Course in Descriptive AnalysisHealthcare Analytics
Foundation Course on Predictive AnalysisHR Analytics
SAP FICOProject Work
SAP HCMR Programming
Stochastic ModelingSocial and Web Analytics

BSc Data Analytics Syllabus

Semester ISemester II
Foundation Course in MathematicsLinear Algebra
Discrete MathematicsStatistics II
Statistics IStatistics III
Environmental ScienceDifferential Equations & Complex Variable
Communicative English IIntroduction to Computer Organization
Fundamentals of Computer & Problem Solving using CData Structure & Algorithms
R ProgrammingIntroduction to MATLAB in Data Analysis
Semester IIISemester IV
Numerical AnalysisText Analytics
Data Preparation & Data CleaningRegression, Time Series, Forecasting and Index Numbers
Database Management SystemsMultivariate Analysis
Data Warehousing & Data MiningStatistical Inference
Operating SystemsRecommender Systems
OOPS using PythonData Visualization
Community Connect-
Semester VSemester VI
Statistical AnalysisDeep Learning
Data Scientist ToolboxBig Data Analytics
Machine LearningElective - II
Statistical SimulationElective - III
Operational ResearchCapstone Project
Elective - IResearch Report Writing & Presentation

Data Analytics Subjects

The following are the details of some of the important subjects of the data analytics course syllabus.

Also Check:

Top 10 Data Analytics Certification CoursesTop 10 Business Analytics Certification CoursesTop 30 Data Science Certification Courses

Data Structure and Algorithms

Array, Iteration, and InvariantsList, recursion, stacks, and queues
Efficiency and complexitiesTrees
Hash TablesBinary search trees
SearchingSorting

Probability and Statistics

Probability modelsRandom Variable and distribution
Model CheckingRelationship among variable
Sampling distributions and LimitsStatistical inferences
ExpectationsOptimal Inferences
Bayesian Inferences-

Business Fundamentals

Teamwork in BusinessThe foundations of Business
Ethics and Social responsibilityStructuring organizations
Motivating EmployeesManaging Human resources
Economics of BusinessOperations Management

Text Analytics

Natural language basicsProcessing and understanding text
Text SummarizationText similarity and Clustering
Text classificationSemantic and Sentiment analysis

Data Collection

Survey SamplingObservational result
Statistical TechniquesAnalysis of Unstructured Data
Extracting and Presenting Statistics-

Data Visualization

JavaCSS
Customized geographic mapCreation of Bar Chart, Scatter Plot

Top Data Analytics Skills in 2022

According to the report of the World Economic Forum, most companies will be hiring Data Analysts from next year onwards. So on that note, candidates must be aware of the skills that will help them get a good position as Data Analysts.

And to be good at data analytics, they need to have strong numerical and analytical skills and must have a proper understanding of computer software like Scripting Language (Python), Querying Language (SQL), Statistical Language (R), Machine Learning, and Microsoft Excel.

Python

File operations using PythonLooping in Python
Python SyntaxFunctions, Function Arguments, and Control Flow
Working with ListsPython Modules
Decorators and generatorsUsing Dictionaries
Errors and Exception HandlingComparisons and Operators

Check:Top 10 Python Certification Courses Online

Microsoft Excel

Creating WorkbooksFormatting Data
Using FormulasUsing Slicers
Creating Pivot tablesCreating graphs
Using Cell ReferencingFunctions and Formulas
Edit ChartsVBA

Check: Top 10 Excel Courses Online

R Programming

Background and Nuts & BoltsProgramming
Loop Functions and DebuggingSimulation and Profiling

SQL

Basic conceptsCreating Database
Entity-relationship modelingAdding Records to a table
Relational modelSQL Subqueries
Data ManipulationSQL Injections

Check:Top 10 SQL Certification Courses Online

Machine Learning

Introduction to different Learning methods (Supervised, Unsupervised, and Reinforcement Learning)Decision Tree
Database and SQLData Preprocessing and Data Mining
Linear RegressionExploratory Data Analysis
SVMLogistic Regression
CNNNaive Bayes

Top Data Analytics Books

BooksAuthors
The Elements of Data Mining, Statistical Learning, Inference, and PredictionRobert Tibshirani, Trevor Hastie, Jerome Friedman
Data Analysis Software: Programming with R (Statistics and Computing) John M. Chambers
Probability & Statistics for Engineers & Scientists Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, and Keying Ye
Data Mining and AnalysisMohammed J. Zaki, Wagner Meira

Top Data Analytics Tools andSoftware

Many tools have risen with several functionalities for this purpose with the increasing demand for Data Analytics in the market. Whether it is user-friendly or open-source, the following are some of the top tools in data analytics.

  • Tableau:This software enables connection to any data source for free such as Corporate Data Warehouse, Excel, etc. then it creates maps, visualizations, and dashboards with real-time updates on the web.
  • QlikView:It offers in-memory data processing quickly with the results delivered to the end-users. It comes with data association and data visualization with data being compressed.
  • Python:It is an open-source object-oriented programming language that is easy to read, write, and maintain. It offers several visualization and machine learning libraries like TensorFlow, Matplotlib, Scikit-learn, Pandas, Keras, etc. This tool can be fabricated on any platform like a MongoDB database, SQL server, or JSON.
  • RapidMiner:This tool is a powerful integrated space that can combine with any data source type such as Microsoft SQL, Excel, Access, Tera data, Oracle, Sybase, etc. It is used for predictive analytics mostly like text analytics, data mining, and machine learning.
  • OpenRefine:This tool is a data cleaning software that will help you clean up data for analysis which is also known as GoogleRefine. It is used to clean messy data for the transformation and parsing of data from websites.
  • SAS: This tool is a programming language and environment for data manipulation and analytics that can be easily accessible and can analyze data from various sources.

Data Analytics Syllabus: FAQs

Ques. Can I pursue Data Analytics courses online after Class 10th?

Ans. No, you can pursue Data Analytics courses only after class 12th.

Ques. Can I pursue Data Analytics courses online?

Ques. Which type of Data Analytics tools are there?

Ans. The tools of Data Analytics Microsoft Excel, Tableau, Python, SQL, R, and so on.

Ques. Does Data Analytics have a good career?

Ans. According to the report of the World Economic Forum, most of the companies will be hiring Data Analysts from next year onwards. So on that note, candidates must be aware of the skills that will help them get a good position as a Data Analyst.

Ques: What is the syllabus of data analytics?

Ans: Students have to learn a wide range of subjects in the data analytics course. The course includes subjects like Data Collection, Data Visualization, Probability and Statistics, Data Structures and Algorithms, and many more.

Ques: Is learning data analysis difficult?

Ans: The best answer would be it depends. The data analysis courses require the learner to have a good understanding of the different programming languages and analytical software.

Ques: Is being a data analyst a stressful job?

Ans: Data analysts and scientists need to scour the internet and the whole database so that they can form an idea about the trends. It can be termed as a challenging job that requires dedication and patience.

Ques: What is the data analytics salary?

Ans: In India, data analysts can expect a salary of INR 420,000.

Ques: How long does it take to become a data analyst?

Ans: The UG course in Data analytics takes about 4 years to complete. Certificate and diploma courses in Data Analytics can range from a few weeks to 12 months

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