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Data Analyst: Courses, Training, and Other Resources

How to Learn Data Analysis

The world around you is run by numbers. From the latest political poll to the national census, numbers paint a valuable picture of social realities. With data analytics, we learn how people think, act, and function.
If data analytics piques your interest, this article is for you. Here, we'll explain how to become a data analyst, discussing educational paths, job outlook, salary expectations, necessary skills, and much more.

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.

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With help from a bootcamp, you could be a data analyst in 12 months.

What Is Data Analysis Used For?

A data analyst is a person who solves the questions that a business, government, or other organization is seeking to answer. These may include problems like identifying which product should go on sale in an online store. A data analyst uses their knowledge of professional data analysis techniques to find an answer.

The problems a data analyst solves depends on the industry in which they work. Governments use data analysis for a myriad of purposes, 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 features users enjoy most in a given app.

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 Does a Data Analyst Do?

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:
  • Interpreting data from small or large datasets
  • Identifying data patterns
  • Working with management to figure out ways to improve business operations
  • Obtaining data from sources where it is being collected
  • Developing databases and data reports
  • Implementing strategies to increase efficiency

Data Analyst Job Outlook

The US Bureau of Labour Statistics (BLS) expects market research analyst positions to grow by 18% from 2019 to 2029, which the Bureau categorizes as "much faster than average." This optimistic projection is the result of the growing demand for efficient systems and predictive analytics in our tech and business-driven world.

The services of data analysts are increasingly sought by business and government leaders to make decisions. As a data set increases in size, so does the reliability of the analysis that someone has conducted. This is why companies gather data. Taking all this into consideration, the employability of these professionals seems guaranteed, at least for the next decade.

Data Analyst Salary

The average salary for a data analyst is $61,592, according to PayScale. Glassdoor, on the other hand, estimates it closer to $68,000. Neither figure includes bonuses or commissions, which can significantly increase the income of these professionals. In fact, PayScale estimates that the total pay for a data analyst (including bonuses, profit sharing, tips, commissions, overtime pay, and other forms of income) ranges from $44,000 to $86,000.

Naturally, experience impacts these professionals' income. According to Glassdoor, a senior data analyst earns $94,797 a year.

Essential Data Analyst Skills

Learning data analytics means familiarizing yourself with the various tools involved in the process. Below are the essential data analyst skills:

Math.

Data analysis deals with numbers. You do not need to have an in-depth understanding of trigonometry or calculus. However, you will need a firm grasp of mathematics and its concepts.

Statistics.

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 the deeper meaning behind it.

Programming.

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.

Communication.

The importance of this soft skill should not be underestimated. Communication, both written and verbal, is key for your success. You need superb listening skills to understand your assignments as well as the ability to clearly explain complex topics to a colleague. Good communication skills can mean the difference between a harmonious working environment and a toxic one.

What Tools Do Data Analysts Use?

Another common question regarding data analysts is which tools they use on the job. The list is long, but some of the most common ones include GitHub, Amazon S3, and Jupyter Notebooks.
A staple in the data analysis industry is Google Analytics, which data analysts use to gain insights into valuable customer information that can boost business performance. In plain language, Google Analytics tracks and reports web traffic and is the most widely used web analysts service out there.
Tableau, used for aggregating and analyzing data, is another essential tool for data analysts. These professionals use Tableau to create and share dashboards with colleagues and to create visualizations.

A Day in the Life of a Data Analyst

You may be asking yourself what a day in the life of a data analyst looks like. To answer your question, the day-to-day tasks for data analysts vary depending on where they work and what tools they work with. However, a typical day in the life of your average data analyst could be as follows.
Because they lead a busy life, your average data analyst probably wakes up early and spends the morning on one of the many tasks that fall under his purview, such as building custom solutions, working with Hadoop and NoSQL databases, performing regression analysis, or creating data visualizations. After lunch, perhaps they find the time to write queries or address standard requests.

Types of Data Analysis

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

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. Based on this, they decide what data they need to collect. Their answers will tell engineers what data points they need.

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.

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 to colleagues who may lack a 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.

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's goals and how data can help to achieve them.

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.

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 data set and make sure it is structured in the way they want.

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

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.

How Long Does it Take to Become a Data Analyst?

Breaking into the field of data analysis usually takes four years. Most people that secure a job in the industry have obtained, at least, a bachelor's degree. However, some may choose to pursue a master's degree before applying for jobs, which means they are looking at six years of study.
That being said, it is possible to learn data analytics by joining a bootcamp or taking part in a course. These courses are accessible even if you have no prior data science experience. If you follow this path, it can take anywhere from three to six months to build a strong foundation.
The truth is that there's no saying how long it takes to learn data analytics. However, if you have a strong aptitude for mathematics, statistics, and critical thinking, you'll find success in this field soon enough.

How to Become a Data Analyst: Step-by-Step Guide

Learning data analytics is by no means a simple process. The first step in your journey to becoming a data analyst will probably be to pursue an undergraduate degree, where you will gain theoretical knowledge and develop some key technical skills. If you want to know more, we have compiled a step-by-step guide to get you on your way to becoming a data analyst.

Step 1: Get a Bachelor's Degree

As with so many other professions, the journey to becoming a data analyst starts with an undergraduate degree program. You can pursue a degree in data analytics, data science, database management, or machine learning, among other programs. It will take you around four years to complete your degree.

Step 2: Obtain an Internship

Nowadays, internships are an important part of professional development, particularly for students and recent graduates. Through an internship, you can obtain critical practical experience and multiply your chances of landing your dream job. Internships can be a great opportunity to develop some of those abilities that are not covered in academic programs, such as soft skills.

Step 3: Take Online Classes

Your degree and internship may not have addressed every subject relevant to the field. Don't worry; you can turn to online courses or bootcamps to fill those gaps in your learning. Online learning platforms offering data analytics courses abound, with courses taking anywhere from a few weeks to a few months.

Step 4: Apply for a Job

If you've followed the steps above, you should be ready to face the dreaded job hunt. The job outlook for data analysts is very positive, which means there are plenty of open positions to go around. Using job boards such as Indeed, LinkedIn, or Jobvite, you are sure to achieve your goal of landing a high-paying job in the sector.

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 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 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.

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 and programming languages. It gives you the tools you need to become a successful data analyst.

This course is available on Coursera, 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.

Fluency in a programming language is an impressive skill on any resume, and this course on learning Python is 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.

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.

This course teaches you the basics of the R programming language 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 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.

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 Become a Data Analyst in 2021?

Yes, you should. As we have shown you, data analytics is a growing field with an excellent job outlook and high salaries.
Data analytics is crucial to our modern economy. Today, data analytics is used by, among other groups, the insurance industry to predict claims, and 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 and problem-solving, and a dislike for uncertainty, then data analytics might be for you.

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