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Introduction to Data Analytics

This course is part of multiple programs. Learn more

This course is part of multiple programs

Taught in English

Some content may not be translated

Instructor: Rav Ahuja

Financial aid available

482,571 already enrolled

(14,463 reviews)

Recommended experience

Beginner level

All you need to get started is basic computer literacy, high school level math, and access to a modern web browser such as Chrome or Firefox.

What you'll learn

Explain what Data Analytics is and the key steps in the Data Analytics process

Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst

Describe the different types of data structures, file formats, and sources of data

Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Skills you'll gain

Data Science
Spreadsheet
Data Analysis
Microsoft Excel
Data Visualization

Details to know

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There are 5 modules in this course

Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers.

You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pipelines. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you’ll be able to understand the fundamentals of the data analysis process including gathering, cleaning, analyzing and sharing data and communicating your insights with the use of visualizations and dashboard tools. This all comes together in the final project where it will test your knowledge of the course material, and provide a real-world scenario of data analysis tasks. This course does not require any prior data analysis, spreadsheet, or computer science experience.

What is Data Analytics

In this module, you will learn about the different types of data analysis and the key steps in a data analysis process. You will gain an understanding of the different components of a modern data ecosystem, and the role Data Engineers, Data Analysts, Data Scientists, Business Analysts, and Business Intelligence Analysts play in this ecosystem. You will also learn about the role, responsibilities, and skillsets required to be a Data Analyst, and what a typical day in the life of a Data Analyst looks like.

What's included

9 videos 3 readings 4 quizzes 1 discussion prompt

9 videos • Total 39 minutes

Course Introduction • 2 minutes • Preview module
Modern Data Ecosystem • 4 minutes
Key Players in the Data Ecosystem • 5 minutes
Defining Data Analysis • 5 minutes
Viewpoints: What is Data Analytics? • 3 minutes
Responsibilities of a Data Analyst • 4 minutes
Viewpoints: Qualities and Skills to be a Data Analyst • 4 minutes
A Day in the Life of a Data Analyst • 5 minutes
Viewpoints: Applications of Data Analytics • 2 minutes

3 readings • Total 22 minutes

Data Analytics vs. Data Analysis • 2 minutes
Summary and Highlights • 10 minutes

4 quizzes • Total 45 minutes

Practice Quiz • 9 minutes
Practice Quiz • 6 minutes
Graded Quiz • 15 minutes

1 discussion prompt • Total 5 minutes

Introduce yourself • 5 minutes

The Data Ecosystem

In this module, you will learn about the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will gain an understanding of various types of data repositories such as Databases, Data Warehouses, Data Marts, Data Lakes, and Data Pipelines. In addition, you will learn about the Extract, Transform, and Load (ETL) Process, which is used to extract, transform, and load data into data repositories. You will gain a basic understanding of Big Data and Big Data processing tools such as Hadoop, Hadoop Distributed File System (HDFS), Hive, and Spark.

11 videos 2 readings 4 quizzes

11 videos • Total 67 minutes

Overview of the Data Analyst Ecosystem • 3 minutes • Preview module
Types of Data • 4 minutes
Understanding Different Types of File Formats • 4 minutes
Sources of Data • 7 minutes
Languages for Data Professionals • 8 minutes
Overview of Data Repositories • 4 minutes
RDBMS • 7 minutes
NoSQL • 7 minutes
Data Marts, Data Lakes, ETL, and Data Pipelines • 6 minutes
Foundations of Big Data • 5 minutes
Big Data Processing Tools • 6 minutes

2 readings • Total 20 minutes

4 quizzes • total 66 minutes.

Practice Quiz • 15 minutes
Practice Quiz • 18 minutes
Graded Quiz • 18 minutes

Gathering and Wrangling Data

In this module, you will learn about the process and steps involved in identifying, gathering, and importing data from disparate sources. You will learn about the tasks involved in wrangling and cleaning data in order to make it ready for analysis. In addition, you will gain an understanding of the different tools that can be used for gathering, importing, wrangling, and cleaning data, along with some of their characteristics, strengths, limitations, and applications.

7 videos 2 readings 4 quizzes

7 videos • Total 39 minutes

Identifying Data for Analysis • 5 minutes • Preview module
Data Sources • 4 minutes
How to Gather and Import Data • 6 minutes
What is Data Wrangling? • 6 minutes
Tools for Data Wrangling • 5 minutes
Data Cleaning • 6 minutes
Viewpoints: Data Preparation and Reliability • 4 minutes

4 quizzes • Total 48 minutes

Mining & visualizing data and communicating results.

In this module, you will learn about the role of Statistical Analysis in mining and visualizing data. You will learn about the various statistical and analytical tools and techniques you can use in order to gain a deeper understanding of your data. These tools help you to understand the patterns, trends, and correlations that exist in data. In addition, you will learn about the various types of data visualizations that can help you communicate and tell a compelling story with your data. You will also gain an understanding of the different tools that can be used for mining and visualizing data, along with some of their characteristics, strengths, limitations, and applications.

8 videos 2 readings 4 quizzes

8 videos • Total 44 minutes

Overview of Statistical Analysis • 8 minutes • Preview module
What is Data Mining? • 5 minutes
Tools for Data Mining • 6 minutes
Overview of Communicating and Sharing Data Analysis Findings • 5 minutes
Viewpoints: Storytelling in Data Analysis • 3 minutes
Introduction to Data Visualization • 5 minutes
Introduction to Visualization and Dashboarding Software • 7 minutes
Viewpoints: Visualization Tools • 3 minutes

Career Opportunities and Data Analysis in Action

In this module, you will learn about the different career opportunities in the field of Data Analysis and the different paths that you can take for getting skilled as a Data Analyst. At the end of the module, you will demonstrate your understanding of some of the basic tasks involved in gathering, wrangling, mining, analyzing, and visualizing data.

7 videos 4 readings 2 quizzes 1 peer review

7 videos • Total 28 minutes

Career Opportunities in Data Analysis • 5 minutes • Preview module
Viewpoints: Get into Data Profession • 3 minutes
Viewpoints: What do Employers look for in a Data Analyst? • 5 minutes
The Many Paths to Data Analysis • 4 minutes
Viewpoints: Career Options for Data Professionals • 3 minutes
Viewpoints: Advice for aspiring Data Analysts • 3 minutes
Viewpoints: Women in Data Professions • 3 minutes

4 readings • Total 32 minutes

Using Data Analysis for Detecting Credit Card Fraud • 10 minutes
Congratulations and Next Steps • 2 minutes
Course Credits and Acknowledgements • 10 minutes

2 quizzes • Total 21 minutes

1 peer review • total 60 minutes.

Peer-Graded Final Assignment • 60 minutes

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

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Learner reviews

Showing 3 of 14463

14,463 reviews

Reviewed on Mar 13, 2021

Great general and broad information on data analytics. Gives good ideas and examples of career paths that can be followed. I especially liked how it ranked the various careers and specializations.

Reviewed on Apr 4, 2022

Great foundational course for begginers. It provides overview of data analytics, tools used in data analysis, skill requirements, and examples of typical career paths taken by data analysts.

Reviewed on Sep 10, 2021

A great job is done in providing professional background and knowledge on Data Analytics!! Learned more on tools, and gained new insights on analytics from IBM staff. Thank you for a great course!

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