Is Data Analytics Hard? A Guide To Getting Started in 2023

Sakshi GuptaSakshi Gupta | 9 minute read | January 19, 2022
Is Data Analytics Hard A Guide To Getting Started in 2022

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For the past decade, data analytics has been one of the most popular fields in information technology (IT)—and for good reason. However, data analytics is not without its challenges, making professionals in the field all the more sought-after. So in what ways is data analytics hard? 

While it’s not easy, it’s also not all that complicated to learn and master, especially if you do it the right way from the beginning. Jobs in data analytics are some of the best-paying in many parts of the world. In the U.S., the average salary of a data analyst is $64,756, according to Indeed. 

This means that all of the efforts you’ll put into learning data analytics will eventually pay off— and pay off well. 

What Is Data Analytics?

Data analytics is the process of collecting, analyzing, and interpreting data to help businesses optimize performance, solve problems and mitigate risks, and achieve their goals. Data analytics is quite broad and touches almost every industry, the technology is now part of every sector. As a result, data analytics deals with diverse types of information.

Typically, data analysis involves identifying trends or calculating metrics to help optimize performance, identify issues, or mitigate risks. 

For example, social media companies regularly use data analytics to adjust how they present content to their viewers. Similarly, manufacturers can use data collected from the factory floor to identify bottlenecks. 

What Makes Data Analytics Hard To Learn?

is data analytics hard: What Makes Data Analytics Hard To Learn?

Is data analytics hard? Many would agree it is because of the cross-disciplinary nature of the field, and, indeed, it may not be for everyone. 

Here are reasons why data analytics is generally considered difficult for beginners:

  • Mathematical skills. As a STEM field, data analytics is closely linked with mathematics, which means you are required to be good at math if you want to be good at data analytics. Even though software and algorithms do most of the math, as a data analyst, you should know the working and how the results were analyzed. 
     
  • Advanced technical skills. Unlike some other fields in the IT sector, data analytics requires advanced technical skills, as you often use complex systems and a lot of data. The processes and practices are more standardized because you need to be as accurate as possible with your findings. 
     
  • Research skills. Data analytics isn’t just about analyzing data; part of the process is also knowing where to look for data that can help identify problems or measure performance. Therefore, you also need a keen eye and good research skills to identify and determine data requirements. 
     
  • Continuous learning. This field is constantly evolving with new trends, industry practices, and new data analytics tools, meaning you must stay on top of these things to stay ahead. Keeping up with the latest industry trends not only increases your knowledge but also improves adaptability, helping you remain competitive in the field.

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How Long Does It Take To Learn Data Analytics?

As there are different paths to learning data analytics and becoming a data analyst, the duration of these paths also varies. It also depends on whether you’re a complete beginner or someone with some level of technical knowledge and expertise. 

For many data analysts, the beginning point is a four-year bachelor’s degree in Computer Science, followed by specializations like certification courses or a master’s degree focusing on data analytics. 

So, if you take this route, it may take up to 4-5years. This would include your four years of college and subsequent courses or certifications—specifically in data analytics—as well as some hands-on industry experience. 

That said, many data analysts these days are taking a different approach by completing short courses and certifications that accelerate the process. These courses can last from just a couple of weeks to a few months. 

As a beginner, it may take at least six months to learn data analytics through courses, bootcamps, and self-practice. Taking classes and completing bootcamps in data analytics can help you land a job, but the learning doesn’t stop there. It’s a good idea to keep learning emerging technologies in data analysis to stay competitive in the job market. 

For a professional with some knowledge of data analytics, it may take even less time, say, ten weeks. 

How To Get Started With Data Analytics

is data analytics hard: How To Get Started With Data Analytics

So how does someone learn data analytics? Should you go back to college or binge tutorial videos on YouTube? 

The truth of the matter is that you don’t necessarily need to go to college and earn a degree. A mix of different approaches to learning data sets and analytics can also set you on the right career path. 

Build Your Foundation

As with any other subject, you should start from the ground up and build your base first. As data analytics is heavily reliant on mathematics, databases, and other specific technical skills, you will first need to learn those before using data sets and tools. 

Here are some of the foundational skills and core concepts you should focus on:

  • Statistics 
  • Python/R
  • Data types and structures
  • SQL
  • Data cleaning and preparation
  • Data visualization

You can self-study by reading books and watching videos or taking courses in these particular areas. 

Utilize Free Resources

is data analytics hard: Utilize Free Resources

Luckily enough, there are many free resources online that you can utilize to build your foundation and learn more about data analytics—and even data science

If you’re more of a visual learner, YouTube has many video tutorials for people who are learning basic data analytics concepts, like what it is, how it’s used, and what kinds there are. 

Similarly, to learn coding languages like Python, you can use the basic subscription of Codecademy for free. 

You can also find several data analytics-related free courses on Kaggle, the community for data science and machine learning. 

Take a Course

is data analytics hard: Take a Course

While free resources are beneficial, the best way to prepare yourself is by taking dedicated data analytics courses. While you can try finding a course near you, your best bet is to go with an online course, as they offer greater flexibility and convenience. 

The advantage of taking a course is that you learn from professionals, this can help increase your chances of getting hired. With a course certification, you can show potential recruiters that you are indeed qualified to work in data analytics.

You can find career-oriented data analytics courses at Springboard that offers one-on-one mentoring from an industry expert along with project-based learning. 

Ask for Help

is data analytics hard: Ask for Help

As data analytics can be complicated to master from scratch, you won’t make it far without seeking help when you need it. You shouldn’t shy away from asking questions when confused, whether you’re asking an instructor, mentor, or friend who already works in the field. 

How To Get Better at Data Analytics

If you already have some training and experience with data analytics and want to get better at it, there are many avenues where you can polish your skills and learn new things. 

Remember, data analytics and data science are continuously evolving fields, which means learning never really stops. 

Get a Mentor

is data analytics hard: Get a Mentor

The best thing you can do to improve your data analytics knowledge and skills is to have a mentor to guide you every step of the way. A mentor can readily answer your questions, allowing you to move quickly through the learning process rather than getting bogged down with a problem. 

Because your mentor will be experienced in the field, they should also be able to acquaint you with career prospects and challenges. That way, you will be better prepared for the job market. Having a mentor can also be immensely helpful even after you have already found a job in data analytics. 

Practice on New Data Sets

While learning online and taking courses, you’ll be given data sets to work on, but you can also look outside for newer data sets, especially those from real-life applications. You can follow your projects using free data sets available online on platforms like GitHub. 

This helps you because different data sets present different problems and findings, which prepares you to utilize data sets to the best of your abilities. 

Participate in Competitions

is data analytics hard: Participate in Competitions

Another fun and rewarding way to sharpen your analytical skills is by taking part in data analytics competitions. IT competitions are fairly common online, allowing amateur programmers and analysts to hone their skills and win certificates and monetary prizes along the way. 

Kaggle routinely hosts data science, data analytics, and machine learning competitions. One of the most popular data analysis competitions is the International Data Analysis Olympiad (IDAO). It’s open to everyone regardless of their education or experience. 

DataHack is an excellent platform for finding challenges to learn new skills for data hackathons. If you’re in it for the money, Codalab hosts some competitions with monetary prizes. 

Attend Events and Presentations

Similar to online competitions, data analysis conferences, seminars, and other events can also present a great opportunity to learn new things and interact with experts in the field. Many organizations hold such events, and you may even be able to find one near you. 

Nowadays, many seminars and events are being held virtually because of the pandemic restrictions, as well as the general trend of conducting seminars virtually. This means that even if you’re in another city or country, you can attend the event and gain valuable insights into the industry and where it’s headed. 

Pick a Specialty

Pick a Specialty

Rather than just focusing on data analytics as a field, pick a specialty and focus on that. Some of these specialties are:

  • Data warehousing
  • Data mining and visualization
  • Business analytics
  • Statistical analysis
  • Database management and architecture
  • Predictive analytics
  • Enterprise performance management

You can take courses or certifications in these specialized fields within data analytics. Working directly in the field can also be considered a form of training. 

About Data Analytics as a Career

Is being a data analyst hard? Is it a fulfilling career? You may have many questions about data analyst jobs. 

What Are the Requirements To Get Into Data Analytics?

What Are the Requirements To Get Into Data Analytics?

The requirements for a data analyst job can vary by the specific job in question. However, an entry-level data analytics job would normally require a bachelor’s degree in a related field (computer science, software engineering, IT, etc.) and skills directly linked to the job. 

Generally, you should be skilled in programming languages like Python or R that are frequently used in data analysis applications. You should also be good with databases, especially query languages like SQL. 

Taking statistics, mathematics, database, and general computer science courses can give you a headstart as you pursue your undergraduate degree. 

If you don’t have a bachelor’s degree or you have one in another field not relevant to data analytics, you should complete at least one data analytics course or undergo some other relevant form of training. 

Is Data Analytics a Good Career?

Data analytics is a great career field with high demand and an above-average salary. With big data and data science becoming such a crucial part of global technological advancements, there’s also a growing need for data analysts.

More importantly, data analysts aren’t just limited to the IT sector; data analysts are essential for any sector producing and relying on data, such as retail, entertainment, production, and consultancy. 

Data analytics-related jobs like statisticians and data scientists are among the  top 10 best jobs in the U.S. 

Does Data Analytics Pay Well?

Does Data Analytics Pay Well?

Data analytics jobs are considered well-paying, with median salaries consistently increasing year on year. According to Glassdoor, the average base pay of a data analyst is $69,517 a year. 

The U.S. Bureau of Labor Statistics put the median salary of data analysts in 2022 at $86,200 a year ($41.44 per hour). 

With specialties, the pay range can be even higher. So a career in data analytics can be quite lucrative, especially if you specialize in newer technologies and gain more valuable skills per the industry’s demand. 

Is There a Difference Between Data Analytics and Business Analytics?

Data analytics and business analytics are two different fields that are strongly interlinked. Data analytics refers to the analysis of data sets to detect trends, identify problems, and calculate metrics to gauge performance. 

On the other hand, business analytics involves reviewing data-driven information to make business decisions. You can say that business analytics is driven by data analytics. 

But is business analytics hard? It’s not as technical as data analytics, but it does require strong communicating, problem-solving, and critical thinking skills to choose the right strategies and make the best decisions to reach your business goals. 

Unlike data analytics, a career in business analytics may require a business-related degree. 

If you’re still wondering, “Is data analytics hard?” the answer lies in proper training, mentorship, and practicing. You don’t need a fancy degree in data analytics, and you can learn a great deal and land a job with a comprehensive course. 

Keep in mind that while it may be difficult, with a strong foundation and continuous drive to improve, you can become an expert in this field relatively quickly.

Since you’re here…
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Sakshi Gupta

About Sakshi Gupta

Sakshi is a Senior Associate Editor at Springboard. She is a technology enthusiast who loves to read and write about emerging tech. She is a content marketer and has experience working in the Indian and US markets.