Introduction to Data Analytics from Coursera

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's inside

Syllabus

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.

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.

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.

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.

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces potential data science career, roles, and responsibilities. Serves as a survey for the field for those unsure of what roles are available

Exposes beginners to foundational vocabulary, platforms, and tools for data analysis

Strong overview of essential concepts in data analysis, including gathering data, data cleaning and preparation, exploratory data analysis, data visualization, and storytelling

Well-structured and comprehensive, with a logical progression of topics and modules

Reviews summary

Data analytics for beginners

The “Introduction to Data Analytics” course on Coursera provides an excellent foundation for individuals seeking to explore the field of data analytics. Led by experts in the field, this course introduces the ecosystem of data analytics, covering key concepts, processes, and tools used in the industry. Learners will gain insights into the different types of data analysis, data repositories, and the diverse range of software and programming languages employed in the field. Throughout the course, learners are exposed to real-world case studies and perspectives from experienced data analysts, offering practical insights into the application of data analytics in various domains. The course emphasizes the importance of storytelling and effective communication in presenting data-driven findings to stakeholders. By understanding how to translate complex data into clear and concise narratives, learners can enhance their impact as data analysts. The hands-on nature of the course, with practical exercises and a final project, allows learners to apply their newly acquired knowledge and skills to real-world scenarios. This reinforces their understanding of data analysis techniques and provides them with a tangible demonstration of their progress. Furthermore, the peer-reviewed assignments encourage learners to engage with their fellow classmates, exchange feedback, and enhance their critical thinking abilities. Overall, the “Introduction to Data Analytics” course is highly recommended for individuals with little to no prior experience in the field who are keen on exploring data analytics as a potential career path. It provides a comprehensive overview of the industry, introduces essential concepts and tools, and equips learners with the necessary skills to embark on their journey in data analytics.

Learners appreciate the inclusion of interviews with data professionals, as they offer valuable insights and perspectives from the field.

"The course did a great job of giving a basic overview of data analytics, the data ecosystem, data gathering, and wrangling, visualizing data, and career opportunities. It was a beginner course, and the information presented was clear."

The course provides opportunities for hands-on practice through exercises and a final project, which helps reinforce learning.

"By understanding how to translate complex data into clear and concise narratives, learners can enhance their impact as data analysts."

learners say this course is a largely positive introductory experience to the field of data analytics.

"This course gives a very good intro to data analytics."

The content is considered engaging, informative, and well-structured, providing a solid foundation for beginners.

"I learned a lot through this course."

"Content is provided in small chunks which are digestible."

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 Introduction to Data Analytics with these activities:

Attend data analysis workshops

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Participate in workshops led by industry experts to acquire hands-on experience and expand your knowledge in specific areas of data analysis.

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Research and identify relevant workshops offered by universities, professional organizations, or online platforms.
Register for and attend the workshops to actively engage with instructors and peers.

Connect with data analysts

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Seek out experienced data analysts for guidance and support to supplement your learning and gain real-world insights.

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Attend industry events or online forums to network with professionals.
Reach out to data analysts via LinkedIn or email to request mentorship.

Review statistics fundamentals

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Reinforce your foundational skills in statistics to better comprehend some of the more advanced concepts taught in this data analysis course.

Browse courses on Statistics

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Review your notes or textbooks on probability concepts like mean, median, mode, and standard deviation.
Brush up on hypothesis testing: null and alternative hypotheses, p-values, and significance levels.

Four other activities

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Build a data analysis dashboard

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Design and develop interactive dashboards to effectively present data insights and facilitate decision-making.

Browse courses on Data Visualization

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Identify the key data metrics and visualizations you want to include.
Select a dashboarding tool and learn its interface.
Build the dashboard and connect it to the data source.
Test and iterate on the dashboard design for usability and functionality.

Contribute to open-source data analysis projects

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Engage with the open-source community to enhance your coding skills, learn from others, and contribute to the field of data analysis.

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Identify relevant projects on platforms like GitHub.
Review the project's documentation and codebase.
Start contributing by submitting bug reports or code changes.

Develop a data analysis case study

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Apply your data analysis skills to a real-world scenario to enhance your understanding and demonstrate your proficiency.

Browse courses on Data Storytelling

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Identify a business problem or question that can be addressed through data analysis.
Collect and clean the necessary data.
Analyze the data and draw meaningful insights.
Visualize your findings effectively.
Write a report or create a presentation to present your case study.

Data storytelling practice

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Enhance your ability to derive meaningful insights from data and present them effectively through storytelling.

Browse courses on Data Visualization

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Choose a dataset and identify the key narrative you want to convey.
Craft a compelling narrative that highlights the insights and implications of the data.
Practice presenting your story to an audience, using visual aids and clear language.

Career center

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

Data Analyst

A Data Analyst gathers, cleans, and analyzes data to help businesses make informed decisions. This course provides a comprehensive introduction to the field of data analysis, including the skills and responsibilities of a Data Analyst. By completing this course, you'll be well-prepared to launch a successful career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist uses advanced statistical and machine learning techniques to extract insights from data. This course provides a foundation in the skills and tools used by Data Scientists, including data gathering, cleaning, analysis, and visualization. By completing this course, you'll be well-positioned to pursue a career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Business Analyst

A Business Analyst helps businesses understand their data and make better decisions. This course provides a solid foundation in the skills and knowledge needed to succeed as a Business Analyst, including data analysis, visualization, and communication. By completing this course, you'll be well-prepared to launch a successful career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Data Engineer

A Data Engineer designs, builds, and maintains the infrastructure that supports data analysis. This course provides an introduction to the skills and tools used by Data Engineers, including data storage, processing, and management. By completing this course, you'll be well-prepared to pursue a career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models to solve business problems. This course provides a foundation in the skills and tools used by Machine Learning Engineers, including data analysis, machine learning, and software engineering. By completing this course, you'll be well-positioned to pursue a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Visualization Analyst

A Data Visualization Analyst creates visual representations of data to help businesses communicate insights and make informed decisions. This course provides a comprehensive introduction to the skills and tools used by Data Visualization Analysts, including data visualization, storytelling, and communication. By completing this course, you'll be well-prepared to launch a successful career as a Data Visualization Analyst.

See salaries and explore the career path for Data Visualization Analyst

Statistician

A Statistician uses statistical methods to collect, analyze, and interpret data. This course provides a strong foundation in the skills and knowledge needed to succeed as a Statistician, including data analysis, probability, and inference. By completing this course, you'll be well-prepared to launch a successful career as a Statistician.

See salaries and explore the career path for Statistician

Data Architect

A Data Architect designs and manages the data architecture of an organization. This course provides an introduction to the skills and tools used by Data Architects, including data modeling, data integration, and data governance. By completing this course, you'll be well-prepared to pursue a career as a Data Architect.

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Database Administrator

A Database Administrator manages and maintains databases. This course provides an introduction to the skills and tools used by Database Administrators, including database design, database management, and database security. By completing this course, you'll be well-prepared to pursue a career as a Database Administrator.

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Information Security Analyst

An Information Security Analyst protects an organization's data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course provides an introduction to the skills and tools used by Information Security Analysts, including data security, network security, and risk management. By completing this course, you'll be well-prepared to pursue a career as an Information Security Analyst.

See salaries and explore the career path for Information Security Analyst

Data Governance Officer

A Data Governance Officer develops and implements policies and procedures to ensure that an organization's data is used in a consistent and ethical manner. This course provides an introduction to the skills and tools used by Data Governance Officers, including data governance, data quality, and data privacy. By completing this course, you'll be well-prepared to pursue a career as a Data Governance Officer.

See salaries and explore the career path for Data Governance Officer

Data Librarian

A Data Librarian manages and organizes an organization's data assets. This course provides an introduction to the skills and tools used by Data Librarians, including data management, data organization, and metadata management. By completing this course, you'll be well-prepared to pursue a career as a Data Librarian.

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Data Steward

A Data Steward is responsible for the quality, accuracy, and completeness of an organization's data. This course provides an introduction to the skills and tools used by Data Stewards, including data quality management, data governance, and data lineage. By completing this course, you'll be well-prepared to pursue a career as a Data Steward.

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Data Privacy Officer

A Data Privacy Officer is responsible for protecting an organization's data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course provides an introduction to the skills and tools used by Data Privacy Officers, including data privacy law, data security, and risk management. By completing this course, you'll be well-prepared to pursue a career as a Data Privacy Officer.

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Data Warehouse Architect

A Data Warehouse Architect designs and builds data warehouses. This course provides an introduction to the skills and tools used by Data Warehouse Architects, including data modeling, data integration, and data management. By completing this course, you'll be well-prepared to pursue a career as a Data Warehouse Architect.

See salaries and explore the career path for Data Warehouse Architect