Introduction to Data Analytics
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Introduction to Data Analytics
This course is part of multiple programs.
Instructor: Rav Ahuja
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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
Tools you'll learn
Details to know
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- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
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.
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 videos5 readings4 assignments1 discussion prompt
9 videos•Total 40 minutes
- Course Introduction•3 minutes
- Modern Data Ecosystem •5 minutes
- Key Players in the Data Ecosystem•6 minutes
- Defining Data Analysis •6 minutes
- Viewpoints: What is Data Analytics?•3 minutes
- Responsibilities of a Data Analyst •5 minutes
- Viewpoints: Qualities and Skills to be a Data Analyst•5 minutes
- A Day in the Life of a Data Analyst •5 minutes
- Viewpoints: Applications of Data Analytics•3 minutes
5 readings•Total 34 minutes
- A Quick Note for the Best Learning Experience•2 minutes
- Summary and Highlights•10 minutes
- Copy of Data Analytics vs. Data Analysis•2 minutes
- Generative AI: An essential Skill for today's Data Analysts•10 minutes
- Summary and Highlights•10 minutes
4 assignments•Total 45 minutes
- Graded Quiz: Modern Data Ecosystem and the Role of Data Analytics•15 minutes
- Graded Quiz: The Data Analyst Role•15 minutes
- Practice Quiz: Modern Data Ecosystem and the Role of Data Analytics•9 minutes
- Practice Quiz: The Data Analyst Role•6 minutes
1 discussion prompt•Total 5 minutes
- Introduce yourself•5 minutes
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.
What's included
11 videos2 readings4 assignments1 plugin
11 videos•Total 67 minutes
- Overview of the Data Analyst Ecosystem •4 minutes
- Types of Data •4 minutes
- Understanding Different Types of File Formats•5 minutes
- Sources of Data•8 minutes
- Languages for Data Professionals •8 minutes
- Overview of Data Repositories•5 minutes
- RDBMS•8 minutes
- NoSQL•8 minutes
- Data Marts, Data Lakes, ETL, and Data Pipelines•7 minutes
- Foundations of Big Data•5 minutes
- Big Data Processing Tools•6 minutes
2 readings•Total 20 minutes
- Summary and Highlights•10 minutes
- Summary and Highlights •10 minutes
4 assignments•Total 66 minutes
- Graded Quiz: The Data Ecosystem and Languages for Data Professionals•15 minutes
- Graded Quiz: Understanding Data Repositories and Big Data Platforms•18 minutes
- Practice Quiz: The Data Ecosystem and Languages for Data Professionals •15 minutes
- Practice Quiz: Understanding Data Repositories and Big Data Platforms•18 minutes
1 plugin•Total 5 minutes
- Real-World Applications of Data Warehouses, Data Marts, and Data Lakes•5 minutes
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.
What's included
7 videos2 readings4 assignments
7 videos•Total 40 minutes
- Identifying Data for Analysis•6 minutes
- Data Sources•5 minutes
- How to Gather and Import Data •7 minutes
- What is Data Wrangling?•7 minutes
- Tools for Data Wrangling•6 minutes
- Data Cleaning •6 minutes
- Viewpoints: Data Preparation and Reliability•4 minutes
2 readings•Total 20 minutes
- Summary and Highlights•10 minutes
- Summary and Highlights•10 minutes
4 assignments•Total 48 minutes
- Graded Quiz: Gathering Data •15 minutes
- Graded Quiz: Wrangling Data •15 minutes
- Practice Quiz: Gathering Data•9 minutes
- Practice Quiz: Wrangling Data•9 minutes
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.
What's included
8 videos2 readings4 assignments
8 videos•Total 44 minutes
- Overview of Statistical Analysis•8 minutes
- 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•6 minutes
- Introduction to Visualization and Dashboarding Software•8 minutes
- Viewpoints: Visualization Tools•3 minutes
2 readings•Total 20 minutes
- Summary and Highlights•10 minutes
- Summary and Highlights•10 minutes
4 assignments•Total 48 minutes
- Graded Quiz: Analyzing and Mining Data •15 minutes
- Graded Quiz: Communicating Data Analysis Findings•15 minutes
- Practice Quiz: Analyzing and Mining Data •9 minutes
- Practice Quiz: Communicating Data Analysis Findings•9 minutes
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.
What's included
8 videos4 readings2 assignments1 peer review1 app item1 plugin
8 videos•Total 33 minutes
- Career Opportunities in Data Analysis•6 minutes
- 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•4 minutes
- Viewpoints: Women in Data Professions•3 minutes
- Generative AI for Data Analytics •4 minutes
4 readings•Total 32 minutes
- Summary and Highlights•10 minutes
- Using Data Analysis for Detecting Credit Card Fraud•10 minutes
- Congratulations and Next Steps•2 minutes
- Course Credits and Acknowledgements•10 minutes
2 assignments•Total 21 minutes
- Graded Quiz: Opportunities and Learning Paths•15 minutes
- Practice Quiz: Opportunities and Learning Paths•6 minutes
1 peer review•Total 60 minutes
- Option 2: Peer Graded - Final Project Submission and Evaluation•60 minutes
1 app item•Total 20 minutes
- Option 1: AI Graded - Final Project: Submission and Evaluation•20 minutes
1 plugin•Total 5 minutes
- Final Project Submission Guidelines and Deliverables•5 minutes
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Reviewed on Oct 16, 2021
Pretty good course. In my opinion the reading material was a bit brief and did not really cover the quiz questions. Other than that though it was pretty clear and relatively easy to understand.
Reviewed on Sep 17, 2024
Thank you for creating this course. As a beginner trying to become mor analytically sound using data analytics, it was a great start to see the extent of tools that we can in subsequent courses.
Reviewed on Oct 27, 2025
ONE OF THE BEST COURSES TO START AS BEGINNER AND EXCEL IN THIS FIELD WITH EASY AND VISUALY INFORMATING LECTURES TO LEARN , ADAPT AND MAKE PROGRESS QUICKLY. THANKS TO THIS COURSE FOR MY BASICS CLEAR.
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