Data is everything nowadays. According to reports, every other person will generate more than 1.7 MB of data every second every day. To manage this enormous amount of data, businesses have already begun growing their search for Data Science experts to join their teams, so much so that more than 2,720,000 job posts for Data Sciences are open in 2020 alone. In this article, we’ll explore the Data Analytics syllabus and the subjects taught.

Table of Contents

  1. What is Data Analytics?
  2. What is Data Analytics Course Syllabus?
  3. Data and Analysis in the Real World
  4. Analytical Tools
  5. Data Extraction Using SQL
  6. Real World Analytical Organizations
  7. Big Data Analytics

1) What is Data Analytics?

Data Analytics refers to qualitative and quantitative processes and strategies for improving efficiency and business benefit. The data are collected and classified for the identification and analysis of behavioural data and trends. It is often known as Data Analysis.

2) What is Data Analytics Course Syllabus?

Regardless of whether you prefer an online course or a class or a full-time university course, the Data Analytics syllabus and curriculum tend to be almost the same worldwide. In each course, projects can vary. However, for every Data Analytics course syllabus, the basic principles of Data Science, and the basics of Data Analytics are compulsory.

Let’s take a look at them.

3) Data and Analysis in the Real World

In this Data Analytics syllabus segment, you will learn how to think about analytical problems and how data can be interpreted and made decisions. The knowledge value chain, which explains the way between worldwide events and business activities, is a concept that we will implement, and we will look at some of the sources used for data collection.

At the end of this course, you will be able to clarify the lifecycle of information from real-world events to business activities and think about analytical questions in this context. You will also learn how to recognize the kinds of events and techniques frequently employed in business analytics and explain how data is recorded by source systems and saved by conventional and emerging technologies.

4) Analytical Tools

This Data Analytics syllabus segment gives you insight into the technology for analytical work. You will gain knowledge about the storage of data and databases, along with the relational database. You will explore how large-scale data and cloud approaches and concepts such as federation, virtualization, and memory computing work. You’ll also go through a landscape of some of the most common tool classes and learn how they help everyday analytical tasks.

5) Data Extraction Using SQL

In this part of the Data Analytics syllabus, you learn how to extract data using Structured Query Language or SQL from a relational database. It covers all basic SQL commands and explains how data from different tables can be combined and stacked. You will also understand how to extend the strength of your requests with operators and to use sub-quests for additional complexity.

6) Real World Analytical Organizations

This Data Analytics syllabus segment focuses on people and organizations working with information and performing analytics. You will gain insights about who does what and how processes can affect effectiveness and performance. In this part of the Data Analytics syllabus, you’ll also learn about the supporting rules and techniques, such as data governance, data confidentiality, and data consistency that allow an analytical organization to work efficiently.

7) Big Data Analytics

Big Data Analytics is a vital component in a Data Analytics syllabus. Big Data Analytics helps learners analyze vast data collections and discover associations, trends, and more significant insights. This topic contains the following:

  • Relationship database management: It is a popular database that stores all data in tables. There are several tables or correlations in modern databases, categorized further into rows and columns.
  • Understanding of Big Data Ecosystem: This segment of the Data Analytics syllabus intends to introduce learners to the multivarious technologies for data use. From Big Data infrastructure to all of the valuable Big Data elements, this part covers everything.
  • PySpark for streaming and scalable machine learning: In this segment of the Data Analytics syllabus, you learn to create organized streams with Databricks in PySpark while learning side by side about powerful machine learning algorithms.
  • Cross-platform NoSQL system: Learners get to learn about the implementation of a NoSQL multi-platform database to transfer data without reaction between various operating systems, cloud infrastructures, and servers in this segment. 


These are some relevant topics that are primarily covered under the Data Analytics syllabus, be it an online course in Data Science or an on-campus degree course. If you wish to enhance your Data Analytics skills, our Data Analytics courses will surely help you. To explore our Data Analytics courses, check our Integrated Program In Business Analytics that consists of 10 months of online live classes. It also offers a ‘Bring Your Own Project (BYOP)’ feature for learners. Additionally, it offers joint certification by Indian Institute of Management, Indore and Jigsaw Academy.



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