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Data Analytics: Courses, Training, and Resources on Data Analysis

How to Learn Data Analytics

The world around you is run by numbers. From the latest political poll to the national census, numbers paint a valuable picture about social realities. With data analytics, we learn how people think, act, and function. You may have seen terms like data analysis, business analytics, and data science before. Now, you can learn what they mean through data analytics courses.
But how can you begin to analyze data on such a large scale? Lucky for you, there is a surplus of options to help you. These include free online data analytics courses.

What is Data Analysis?

Data analysis involves the processing, cleaning, and understanding of data to figure out the solution to a problem. Data analysis is used by business and government leaders to make decisions. Whereas they used to rely on intuition to make decisions, data analysis has made it possible to hold faith in the numbers. As a data set increases in size, so does the reliability of the analysis that someone has conducted. This is why companies gather data.

What Is Data Analysis Used For?

A data analyst interprets data by looking at trends and patterns. They turn the data into information that can be used to improve a business. Their day-to-day duties include:
  1. Interpreting data from small or large datasets
  2. Identifying data patterns
  3. Working with management to figure out ways to improve business operations
  4. Obtaining data from sources where it is being collected
  5. Developing databases and data reports
  6. Implementing strategies to increase efficiency

Types of Data Analysis

Data analysis requires a combination of mathematical, programming, and business information analysis skills. As a career field, data analytics varies wildly. Below are a few common types of data analysis career options for you.
Developer types

Data Requirements Analysis

It’s easy to collect data. What’s difficult is collecting the right data. Before data analysts begin their work, they must ask what problem they need to solve. Then, they choose what data they need to solve that problem. Their answers will inform engineers what data points they need.

Developer types

Statistical Analysis

Data analysts apply statistical analysis solutions to data sets. This involves several processes. It means figuring out the limitations of a data set, using statistical principles, and calculating final results with those same principles.

Developer types

Data Visualization

Data analysts are in charge of creating visuals that present their findings. As a result, data analysts need to be good at communicating their findings with others who have a non-technical background. An excellent way to do this is through graphics, which are easier to interpret than lists of numbers. Data analysis tools , such as Matplotlib and Tableau, allow data analysts to create graphics and visuals for their work.

Developer types

Business Analysts

While it’s easy to think that data analysts just sit and analyze data, they do so in the context of a much larger issue. Data analytics experts need to have a keen awareness of a business’ goals and how data can help the company achieve its goals.

Data analysts work with people from different departments to solve problems. This means they need to know how to talk in terms that engineers, directors, salespeople, and other employees will understand.

Ultimately, problems are framed as “how can this help advance our organization’s goals?” Some data analysts even specialize in applying business intelligence to data analytics. These people are called business analysts. They use diagnostic analysis to solve business-specific problems.

Developer types

Data Cleaning

Data does not come in a neatly-packaged file with instructions. It comes as raw data. Data analysts need to figure out what to do with that data. Using a technique called cleaning, data analysts look through a dataset and make sure it is structured in the way they want

This involves removing and ensuring the validity of values. Only once a dataset has been cleaned can analysis begin.

Developer types

Data Interpretation

Data analysts need to be good at interpreting data. It’s no use just knowing what data exists. You need to know what story that data tells.

Once an analysis is conducted, data analysts read through the data to identify trends. These trends are compiled into a final report, alongside any visualizations and graphics that the analysts have prepared.

What is a Data Analyst?

A data analyst is a person who solves the questions that a business, a government, or another organization wants to answer. These may be problems, like identifying which product should go on sale on an online store. A data analyst will then use his/her knowledge of professional data analysis techniques to solve the problem.

The problems a data analyst solves depends on the industry in which they work. Governments use data analysis for applications such as public health protection and predicting how the economy will change. Businesses, on the other hand, use data analysis to analyze user engagement or find out what application features users enjoy most.

Learning Data Analytics

Learning data analytics means familiarizing yourself with the various tools involved in the process. Below are the essential skills you'll need to find success in the world of data analysis.


Data analysis deals with numbers. You do not need to have a detailed understanding of trigonometry or calculus. But, you will need a firm grasp of mathematics and its concepts.


Having a deep knowledge of statistics is one of the most useful skills to have if you wish to pursue data analytics. Knowing how different pieces of data are collected is the backbone of the data analysis process. This means you should be comfortable with graphs, charts, regressions, sample sizes, and other data analysis concepts.

Critical Thinking.

To analyze real-world data, you need critical thinking skills. This means having the ability to look at one aspect of a study and extrapolating deeper meaning behind it.


Programming literacy is a huge bonus in the world of data analytics. There are plenty of coding languages you may choose to learn, such as Python , C++, and Java.

How Long Does It Take to Learn Data Analytics?

The amount of time it takes to learn data analytics varies by the learning path you take. If you take a bootcamp or take part in a course, you could learn data analytics anywhere from three to six months. These courses are accessible even if you have no prior data science experience.
Becoming proficient as a data analyst is a different story. It may take several years for you to become proficient as a data analyst and find success as a data scientist. There's no number on how long it takes to learn data analysis. However, if you have a strong aptitude for mathematics, statistics, and critical thinking, you'll find success in this field soon enough.

How to Learn Data Analytics: Step-by-Step

Learning data analysis is an involved process. You must get familiar with several programs and understand how to compile, clean, and use data for accurate analysis. Below is our data analytics step-by-step guide.
  • Learn math and statistics. The first step in becoming a data analyst is to have a strong familiarity and understanding of math and statistics. This is the foundation of any analyst's profession.
  • Learn programming. Analyzing big data means learning programming languages such as R, SQL, and Python.
  • Get familiar with data analytics tools. Once you've gotten familiar with math and programming, the next step is learning the tools. This includes programs like Microsoft Excel, Talend, Datapine, and more.
  • Take courses. The next step is to take courses. Whether you take a standalone course or participate in a bootcamp or data science program, courses prepare you for a career in data analysis.

The Best Data Analytics Courses and Training

There are many options for pursuing an education in data analysis. Below are some of the best data analytics courses to enroll in right now. These are paid and free data analytics courses.

In-Person Data Analytics Courses

Data Science Dojo

Data Science Dojo offers courses in NYC, Seattle, Barcelona, Austin, and more. This is a five-day data science bootcamp for individuals who want to learn data science for any number of careers.

Coding Template

Coding Template is a coding bootcamp that offers courses for students in Boston, Chicago, and Dallas. This is a full-time 10-week program that teaches students data science. Upon completion, students are ready to work in any data-related field.


Metis is a coding bootcamp with courses in Seattle, San Francisco, New York City, and Chicago. Students in the program take part in intensive data science workshops that last 12 weeks. These include job placement support, career coaching, and more.

Online Data Analytics Courses

It can be incredibly convenient to learn data analysis online. Below is a list of some of the best data analytics courses for those who want to learn from home.

The Data Science Course 2020: Complete Data Science Bootcamp from Udemy

This is one of the top-rated data analytics courses from online course provider Udemy. It will teach you everything you need to know about data analytics and computer science. You will start small and work your way up to study machine learning and advanced programming.

In this comprehensive course, students learn the basics of machine learning, business analytics, programming languages. It gives you the tools you need to become a successful data analyst.

Business Analytics Specialization

Coursera is a fantastic resource for anyone looking to further their learning in fields such as data analytics. This class shows those new to the world of data analytics the power of raw numbers.

Business analytics specialization is a beginner course taught by Eric Bradlow. He is a professor of marketing, statistics, and education at the illustrious Wharton School of Business at the University of Pennsylvania. Professor Bradlow puts particular emphasis on how data analysis helps businesses. Those who want to get into data science would be hard-pressed to find a better course than this.

Learning Python for Data Analysis and Visualization

Fluency in a programming language is an impressive skill on any resume, and this course on learning Python s specifically designed for data analysts. Students of this course will learn the fundamentals of data visualization and computer science through hours of video instruction.

By the end of the course, you will have a solid intermediate knowledge of Python. Additionally, you’ll have a more impressive resume and a knack for creating data sets and data visualizations.

Introduction to Data Analytics for Business

Offered by the University of Colorado Boulder, this introductory data analytics course will throw students straight into the world of data analytics. The program focuses on business analytics and will give you a strong foundation to build future skills. By the end of this course, you will have a better understanding of how critical business decisions are made.

Data Science: R Basics

This course teaches you the basics of R programming and how it is used in data analytics. It's a course offered by Harvard, which ensures you'll get a quality education. Students can audit the course for free or pay to receive a verified certificate.

IBM Data Analyst Professional Certificate

IBM is one of the largest and most successful tech companies in the world. Through this course, you learn the principles of data analysis and gain hands-on experience. Upon completing the program, you'll receive certification.

Data Analytics Books

Supplement your learning with data analytics books. There are several books out there for those interested in data analysis. These aren't just books for beginners but also for those who already work in the field. Below are some of the best out there.

The Hundred-Page Machine Learning Book, Andriy Burkov

Machine learning is a significant aspect of data science. This book compiles decades of knowledge and research for those interested in the topic. It only takes a few hours to read, but the information it provides is vital.

The Quick Python Book, Naomi Ceder

Python is an important programming language in data science. If you're interested in the language, then this book is best for you. It is a comprehensive course on Python and teaches you all you need to know about the language.

An Introduction to Probability Theory and Its Applications, William Feller

Probability theory is a significant aspect of data analysis. When it comes to predicting, analyzing, and understanding data, you must work with the probability theory in mind. This book teaches you all about it.

Developing Analytic Talent: Becoming a Data Scientist, Vincent Granville

If you're new to data analysis, this book is for you. Upon completing it, you'll be able to conduct end-to-end data analysis. This may help you find a career in analytics.

Online Data Analytics Resources

As you learn data analytics, there'll be times when you have questions or want to delve into a topic further. Luckily, there are online resources out there to help you. From forums to websites dedicated to the subject, these are the best online data analytics resources out there.

Data Science Masters is a resource that helps you understand data science as a concept. There are several resources on the site, such as tutorials, books, and even study groups. You can learn anything from data design to math and computing.

If you want to learn data science, then this website is for you. Those interested in data analytics can find a wealth of materials to help with learning. The site covers topics such as linear regression, data explorations, and random forests.

This is an interactive website that offers data analysis of various types. You can find data on health, sports, political issues, and culture. The site was launched by American statistician Nate Silver. You can also enjoy insights into the data through the site's podcast.

If you need advice or to see the works of professors in data science, then this is a great resource. Not only does the site provide advice to aspiring data scientists, but it also shows you how some entered the field.

Data Science Weekly is a database of data science resources, news updates, and more. If you cannot find the resources needed in the above pages, you may be able to here. You can also sign up for data science newsletters, which have articles, news, and even features jobs.

Should You Study Data Analytics?

Data analysis is crucial to our modern economy. Today, data analysis is used by, among other groups, the insurance industry to predict claims. It is also used by the financial industry to predict the direction of the stock market. Even technology companies use it to analyze user engagement.
What’s more, even government bodies rely on data to solve societal problems. This is because data can help organizations make more informed, data-driven decisions. When you have data to back up a decision, it is easier to feel confident that you are pursuing the right path.
On an average day, data analysts apply their knowledge of mathematics, statistical dataset analysis methods, and programming to solve business problems. If you’re someone who has a knack for numbers, problem-solving, and a dislike for uncertainty, then data analytics might be for you.

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