Data Analytics Basics for Everyone from edX

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In this course, you will learn about the various components of a modern data ecosystem and the role Data Analysts, Data Scientists, and Data Engineers play in this ecosystem. You will gain an understanding of data structures, file formats, sources of data, and data repositories. You will understand what Big Data is and the features and uses of some of the Big Data processing tools.

This course will introduce you to the key tasks a Data Analyst performs in a typical day. This includes how they identify, gather, wrangle, mine and analyze data, and finally communicate their findings to different stakeholders impactfully. You will be introduced to some of the tools Data Analysts use for each of these tasks.

You will learn about the features and use of relational and non-relational databases, data warehouses, data marts, and data lakes. You will understand how ETL, or Extract-Transform-Load, process converts raw data into analysis-ready data. And what are some of the specific languages used by data analytics to extract, prepare, and analyze data.

By the end of this course you will know about the various career opportunities available in the field of Data Analytics, and the different learning paths you can consider to gain entry into this field.

The course ends with some exercises and a hands-on lab to test your understanding of some of the basic data gathering, wrangling, mining, analysis, and visualization tasks.

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
Explain the use for different types of data repositories, the ETL process, and Big Data platforms
Describe the process and tools for gathering data, wrangling data, mining and analyzing data, and visualizing data
List the different career opportunities in Data Analysis and resources for getting skilled in this domain
Demonstrate your understanding of gathering, wrangling, mining, analyzing, and visualizing data

What's inside

Learning objectives

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
Explain the use for different types of data repositories, the etl process, and big data platforms

Describe the process and tools for gathering data, wrangling data, mining and analyzing data, and visualizing data
List the different career opportunities in data analysis and resources for getting skilled in this domain
Demonstrate your understanding of gathering, wrangling, mining, analyzing, and visualizing data

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
Explain the use for different types of data repositories, the etl process, and big data platforms
Describe the process and tools for gathering data, wrangling data, mining and analyzing data, and visualizing data
List the different career opportunities in data analysis and resources for getting skilled in this domain
Demonstrate your understanding of gathering, wrangling, mining, analyzing, and visualizing data

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a thorough survey of data analytics, from basic concepts to specific skills used throughout the field

Structured to provide learners with a foundation in data analytics for career development or personal growth

Well-structured with clear learning objectives and a logical progression of topics

Provides a good introduction to the field of data analytics and its various career opportunities

Prepares learners for further study or entry-level roles in data analytics through practical hands-on labs

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Analytics Basics for Everyone with these activities:

Create a collection of course notes and resources

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Organizing and reviewing your course materials regularly will help strengthen your understanding of the key concepts and techniques covered in Data Analytics.

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Organize lecture notes, slides, and assignments in a logical manner.
Include helpful online resources, such as articles, videos, and tutorials.
Review your materials regularly to reinforce your learning.

Learn from experienced Data Analysts

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Watching videos and tutorials by experienced Data Analysts will accelerate your learning process.

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Identify reputable sources and content creators in the Data Analytics domain
Watch videos and tutorials on topics aligned with the course curriculum
Take notes and document key insights and concepts

Join a study group or participate in online forums

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Engaging with peers through study groups or online forums can provide valuable insights, different perspectives, and support in your Data Analytics journey.

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Join study groups with classmates or connect with fellow learners online.
Discuss course materials, share experiences, and ask questions.
Collaborate on assignments and projects to enhance your understanding.

Three other activities

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Follow tutorials on data visualization techniques

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Data visualization is crucial for communicating insights effectively. Following tutorials on different techniques will enhance your ability to present data in an engaging and meaningful way.

Browse courses on Data Visualization

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Explore tutorials on libraries like Matplotlib, Seaborn, and D3.js.
Practice creating various types of visualizations (e.g., bar charts, scatter plots, histograms).
Analyze real-world data sets and create visualizations to uncover trends and patterns.

Solve practice problems and case studies

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Solving practice problems and case studies will help you develop your analytical thinking and problem-solving skills, which are essential for Data Analytics.

Browse courses on Case Study Analysis

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Find online platforms or textbooks that provide practice problems.
Work through the problems and analyze the solutions.
Apply your learnings to real-world data analysis scenarios.

Participate in a Kaggle competition

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Kaggle competitions provide real-world data sets and challenges, allowing you to apply your Data Analytics skills in a practical setting and gain valuable feedback.

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Choose a competition that aligns with your interests and skill level.
Develop a data analysis and modeling strategy.
Implement your approach using the provided data.
Submit your results and analyze your performance.

Career center

Learners who complete Data Analytics Basics for Everyone will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts work closely with business stakeholders to identify and solve problems. This course provides a solid foundation for those who wish to become Data Analysts. It explains the key steps in the Data Analytics process and introduces the tools and techniques used by Data Analysts. The course also covers the different career opportunities available in Data Analysis, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of mathematics, statistics, and computer science to extract insights from data. This course provides a foundation for those who wish to become Data Scientists. It introduces the different types of data, the different techniques used to analyze data, and the different tools used by Data Scientists. The course also covers the different career opportunities available in Data Science, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Data Scientist

Data Engineer

Data Engineers design, build, and maintain the systems that store and process data. This course provides a foundation for those who wish to become Data Engineers. It introduces the different types of data repositories, the different techniques used to process data, and the different tools used by Data Engineers. The course also covers the different career opportunities available in Data Engineering, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Data Engineer

Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses make better decisions. This course provides a foundation for those who wish to become Business Intelligence Analysts. It introduces the different types of data, the different techniques used to analyze data, and the different tools used by Business Intelligence Analysts. The course also covers the different career opportunities available in Business Intelligence Analysis, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Business Intelligence Analyst

Business Analyst

Business Analysts use data to help businesses make better decisions. This course provides a foundation for those who wish to become Business Analysts. It introduces the different types of data, the different techniques used to analyze data, and the different tools used by Business Analysts. The course also covers the different career opportunities available in Business Analysis, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Business Analyst

Database Administrator

Database Administrators design, build, and maintain databases. This course provides a foundation for those who wish to become Database Administrators. It introduces the different types of databases, the different techniques used to manage databases, and the different tools used by Database Administrators. The course also covers the different career opportunities available in Database Administration, as well as the different learning paths one can consider to gain entry into this field.

See salaries and explore the career path for Database Administrator

Data Architect

Data Architects design and implement data management solutions. This course provides a foundation for those who wish to become Data Architects. It introduces the different types of data management solutions, the different techniques used to design and implement data management solutions, and the different tools used by Data Architects.

See salaries and explore the career path for Data Architect

Data Governance Specialist

Data Governance Specialists ensure that data is used in a consistent and ethical manner. This course provides a foundation for those who wish to become Data Governance Specialists. It introduces the different types of data governance policies, the different techniques used to implement data governance policies, and the different tools used by Data Governance Specialists.

See salaries and explore the career path for Data Governance Specialist

Big Data Engineer

Big Data Engineers design and implement big data solutions. This course may be useful for those who wish to become Big Data Engineers.

See salaries and explore the career path for Big Data Engineer

Machine Learning Engineer

Machine Learning Engineers design and implement machine learning models. This course may be useful for those who wish to become Machine Learning Engineers.

See salaries and explore the career path for Machine Learning Engineer

Project Manager

Project Managers lead and manage projects.

See salaries and explore the career path for Project Manager