Is Data Analytics Hard? Beginner’s Guide to Start Data Career

- March 22, 2024
Time - 7:22 PM

Entering the world of data analytics can be thrilling and scary at the same time, especially for newcomers hoping to launch a career in this quickly developing industry.

One frequently posed question is, “Is data analytics hard?” With the help of our in-depth beginner’s guide, we demystify the complexities of data analytics and provide insights, helpful guidance, and a clear road map for understanding the field’s nuances and successfully starting a rewarding career in data.

What is Data Analytics?

Every industry today is collecting and using massive amounts of data. However, they collect it in raw form, which is baseless. That is where they need data analytics. It is the process through which raw data is analyzed to create meaningful insights.

You can also use data analytics to drive business decisions. All this is done by specialists known as data analysts.

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They transform these numbers into intelligent and helpful information. Once they have prepared, they share these insights with the right stakeholders. They are generally in the form of suggestions or recommendations for process improvements. This is their primary job responsibility.

Because of this data, companies can make solid and effective business decisions. For this, the analysts clean, manage, manipulate, and analyze the data using different processes.

Why is Data Analytics Hard and Challenging?

When people think about data analytics as a career option, the first thing that instantly comes is – is it hard to learn data analytics. It may be and may not be, all depending on how well you are prepared for it.

However, below are a few challenges often faced by people who start this career.

1. Learning Mathematical and Technical Skills

Although data analytics involves data, you still have to learn a few technical skills. If you are someone who is not great at mathematics, it can be tricky for you. But that doesn’t mean you cannot start your career in this field. Different tools and software do most of the math; you need to know the basics to understand everything.

In addition, you should also learn and understand some advanced technical skills for comprehending complex datasets and systems. Otherwise, it may be difficult for you to prepare valuable insights for your company. Moreover, you must also have vital research and analysis capabilities to determine which data to pick from where.

2. Understanding Which Data to Use

The most crucial part of data analytics is finding the data that will be used. You can’t use just any data. You need data that can offer valuable insight to an organization. Because data comes from different sources, it becomes a difficult job for analysts to decide which source is correct.

You should also understand about the different data warehouses that store the data in a central location. It will help you keep an organized inventory of the data that could be used in the future.

3. Continuous Learning

It’s imperative to stay up to date with the latest industry practices, trends, and data analytics tools in this ever-evolving profession if you want to maintain your competitive edge. Keeping up with the most recent developments in the market helps you stay competitive by expanding your knowledge and enhancing your capacity to adapt.

Tips for a Successful Data Analytics Career

We have curated a list of some fantastic tips that can help you excel in this bright and prosperous career.

1. Learn Data Skills as a Future Investment

According to BLS, or the U.S. Bureau of Labor Statistics, jobs related to data are expected to grow 5% higher than other jobs between 2021 and 2031. The exact number may change depending on the job designation within the data world, which includes data analysts as well.

Because everything today revolves around data, hiring a data analyst is becoming a top priority for companies.

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As a data analyst, one can work in the financial sector, technology, energy, healthcare, and information technology sectors. Moreover, the average salary of a data analyst in the U.S. is $76657 per annum, making it exciting for people to opt for this career. It means if you invest in the skills today, you can reap the benefits in the future.

However, you must remember that learning new technology or skill will take its due course of time. If you think of them as an investment, you will never question is data analytics hard. Just focus on learning and exploring new concepts; you will never find it challenging.

2. Enroll in an Online Course for Strong Foundation

It can be an excellent idea for everyone new to data analysis to enroll in an online course and clear the concepts. It will help them to build a strong base that will help significantly during their careers.

You can take the Data Analytics and Engineering bootcamp training program from CCSLA, which can help you with all the essential topics.

Some topics that are covered in these courses are:

Data structures and data types
Solving queries using data
Data processing and preparation
Data visualization and narratives
Data analysis methods

Even if you are not a fresher, it is still a great option to go for such courses as you can determine your strengths and weaknesses and draw your plan accordingly.

3. Meet Educational Requirements

Businesses look for candidates with at least a bachelor’s degree in Statistics, Mathematics, or Computer Science. However, it is not a mandate that you must have this degree. Today, companies are open to hiring people if they have the proper skill set as the demand is growing.

If you are yet to begin your education, it is a good idea to get a degree in one of these fields, as it can definitely increase your chances.

4. Review Your Math Skills

Data analytics needs a firm hold on mathematical skills. Therefore, if you are planning to start this career, you should learn or review your skills. You will need these skills to study numbers, understand their connection with each other, and use them to make and present valuable insights to the stakeholders.

5. Brush Your Statistical Knowledge

You must be familiar with the basic ideas and methods of statistics in order to analyze data. This covers sampling, probability, regression analysis, and hypothesis testing, among other things. Statistical techniques must be used in order to evaluate data and derive insightful conclusions. Proficiency in statistics is a prerequisite for proficient data analysis.

6. Gain Practical Experience

To understand the complexity of any career or course, you must gain hands-on experience. You can gain this practical experience by working on different projects. These can be taken up during your course or degree years, or you can even work on personal projects. Similarly, you can participate in data analytics competitions or look for open-source projects to gain this experience.

7. Networking

Another essential step that people often neglect is the significance of networking. Look out for communities, groups, or circles with the same passion. If you are working and looking to shift careers, speak to people already working as data analysts to understand their challenges and journeys.

All of these will help you gain a lot of knowledge and valuable insight into this booming field.

8. Learn Advanced Skills

Data analytics is a very bright career, and the future holds very strong. If you want to be on the list of selected candidates and emerge as a winner, go for advanced skills. DataOps and automation are two technologies that can improve data analytics by automating and streamlining the tasks involved in it.

Through the automation of procedures like version control and data quality checks, DataOps can decrease errors while simultaneously increasing the precision and effectiveness of data analytics. Similarly, automation tools will increase efficiency by reducing manual effort. For example, automating data transformation and cleaning can reduce errors and save time during data processing.

When used together, these technologies can transform businesses’ approaches, resulting in more efficient and accurate results.

9. Learn Programming

Programming is an essential part of data analytics. To begin your career, you must know a few programming languages. You can start with R and Python; they are the most commonly and widely used programming languages.

10. Learn SQL

SQL is the standard language for interacting with databases. Understanding SQL enables you to change data structures (schema) and organize, update, and query data kept in relational databases.

SQL is likely the most essential skill to master to get a job since practically all data analysts must use it to access data from a company’s database. In reality, a technical SQL screening is frequently included in data analyst interviews.

11. Build Your Work Portfolio

How will you tell the recruiters that you managed a project successfully? You need to showcase your portfolio to demonstrate your skills. A strong portfolio is the key to getting the right job. That portfolio should include things that are most relevant for a data analyst profile to increase your chances. Do not add generic or common projects, as it would not excite the other person.

Questions to Ask Yourself Before Going for Data Analytics

The fact is that every field is challenging; whether we are a good fit for it or not is the question one should ask. Here are a few questions you should ask yourself before starting this career.

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Are You Inquisitive and Curious?

As a data analyst, you will be required to study data and find out trends and patterns. It is not only about studying numbers; it is about how well you can build them to present valuable insights.

Therefore, you must be a curious person by nature who likes to figure out the reasons behind everything and offer insight solutions to their companies.

If Experienced – Are You Ready to Make that Career Shift?

It is the most crucial point to consider. If you are not into the technical world and want to make this shift, you should ask yourself if you are ready for it. Since a non-technical profile is very different from a technical job role and requires a different level of commitment and dedication.

Moreover, if you are not a good fit, shifting careers too often may not look good on your resume in the long run.

Bottom Line

Despite its size, the field of data analytics is manageable with the correct skills, resources, and willpower. The difficulties of being a competent data analyst can be simply navigated if you pay attention to the advice provided in this article. Data analytics is a growing and evolving field, and since every industry uses data, this career is going to stay.

Everyone who is looking to kickstart this exciting journey can join this excellent Data Analytics and Engineering bootcamp training program by CCSLA. In less time, you can learn and understand every concept you must know to become a successful data analyst.

FAQs

Q1: Is data analytics a difficult field to enter for beginners?

Data analytics can be challenging for beginners, especially those without a background in statistics or programming. However, with the right resources, dedication, and a structured learning path, beginners can effectively acquire the necessary skills and knowledge to succeed in this field.

Q2: What basic skills are required to start a career in data analytics?

Basic skills required include a fundamental understanding of statistics, proficiency in programming languages like Python or R, knowledge of SQL for database management, and the ability to visualize data using tools such as Tableau or Power BI.

Q3: How long does it typically take to become proficient in data analytics?

The time it takes to become proficient in data analytics can vary widely depending on your starting point, learning pace, and the amount of time you can dedicate to learning. On average, it might take several months to a year of consistent study and practice to gain a solid foundation in data analytics.

Q4: Are there any recommended resources for beginners to learn data analytics?

Yes, there are numerous resources available for beginners, including online courses from platforms like Coursera, edX, and Udacity, as well as tutorials and guides from websites like Khan Academy and freeCodeCamp. Books on statistics, Python programming, and data visualization can also be valuable.

Q5: Can I learn data analytics on my own, or should I take formal classes?

Many individuals successfully learn data analytics on their own using online resources and self-study materials. However, formal classes or bootcamps can provide structured learning, personalized feedback, and accountability, which might be beneficial for some learners.

Q6: What are the first steps I should take to start learning data analytics?

The first steps include gaining a basic understanding of statistics and mathematical concepts, learning a programming language such as Python or R, and familiarizing yourself with SQL and data visualization principles. Starting with small projects can also help apply what you’ve learned in practice.

Q7: Is a background in mathematics or statistics necessary for data analytics?

While a background in mathematics or statistics is beneficial, it is not strictly necessary. A basic understanding of these subjects is essential, but many concepts can be learned as you delve into data analytics studies.

Q8: How important is programming in a data analytics career?

Programming is very important in data analytics for automating data processing, performing complex analyses, and creating data visualizations. Languages like Python and R are particularly valuable due to their extensive libraries and community support.

Q9: What challenges do beginners face when starting in data analytics?

Beginners often face challenges such as understanding complex statistical concepts, learning to code, navigating the vast amount of available tools and technologies, and applying theoretical knowledge to practical problems.

Q10: Can I start a career in data analytics without a degree in the field?

Yes, it is possible to start a career in data analytics without a degree in the field. Many employers value practical skills and experience as much as formal education. Building a portfolio of projects and gaining certifications can also help demonstrate your capabilities to potential employers.

Is Data Analytics Hard? Beginner’s Guide to Start Data Career

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