Data is all around us! Businesses need data to run their operations. No matter the size of the company, they need data to be successful. The type of the data companies gather could vary on their business domain. Businesses rely on data driven decision making (DDDM) to drive growth and revenue.

The number of open data analytics jobs have exploded in recent years! So, what is this role all about, what in-demand skills and tools are needed for you to get started. In this blog we explore the topic on how to kickstart your Data Analytics career.

Who Is a Data Analyst?

A data analyst is a professional who uses data to develop insights that help make business decisions. They work with all kinds of data, from customer data to financial data to social media information. This role is often confused with Data Scientist. Data analysts are not entirely responsible for things like predictive analytics, machine learning which falls in the Data Scientist role. Check out this blog essential skills needed to become a top rated data scientist.

Why Would I Want to Be a Data Analyst?

According to, the average starting salary of a data analyst in the USA is around $71,591. The salaries go as high as $110,000.

Besides a decent salary, there are other reasons why someone might want to become a data analyst. Maybe you have an interest in statistics or analytics, or you’re just curious about the way companies use data.

Data analysts are responsible for acquiring, analyzing and in some cases managing data. Data Analyst job role focuses on answering the questions using data. Data Analysts are often responsible for writing reports and building dashboards so that organizations can turn data into actionable insights.

What Do I Need To Start Out as a Data Analyst?

In order to be successful as a data analyst, you need some skills and tools. Here are five things that will help get you started:

1) Analytics Skills

If you have curious mind and like solving problems being a data analyst will come easy to you. As the title of the role suggests, you need strong analytical skills if you want to be a successful data analyst.

You should be able analyze data quickly and efficiently, without any bias, to identify trends and patterns. You should also be able to interpret complex statistical models. As an analyst they also need to be able to think critically and come up with alternative solutions when faced with problems.

Data analysts are sometimes called upon to come up with new ways of analyzing data sets. This means that they must be creative thinkers who can think outside the box and come up with solutions to problems. It’s also important for them to be good problem-solvers and be able to work independently.

2) Technical Skills

If you want to use your analysis skills in interesting ways, you’ll need some key tech skills. Below are some of the skills needed to succeed in your data analytics career path:

  • Statistical Knowledge – To understand how different factors affect decisions, you’ll need statistical analysis knowledge. This includes understanding concepts like regression analysis, random forest and P-values to name a few.
  • Database Knowledge – Database knowledge is essential for working with big datasets. You’ll need the skills necessary for managing tables and queries (SQL) in databases like MySQL or Oracle. It is important to note that database could be relational or noSQL.
  • Microsoft Excel – Excel is by far the most powerful and used tool by analysts. Working with spreadsheets, knowing and using the in-built formulas, creating regression models are just some examples of excel.
  • Programming Language – While there are many programming languages you can use to work with data like Java, C#, C but the most powerful of them all is Python and R. The open sourced libraries that Python offers like MatPlotLib, Pandas you can easily analyze and visualize the data.
  • Visualization Tools – While most of the job of a data analyst is the analysis, it is important to visualize the data as well. There are a wide variety of visualization tools available, but  working knowledge of popular tools like PowerBI and Tableau is important to be successful in this role.

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3) Communication skills

It is very important that data analysts have the right soft skills. Being able to effectively communicate with others is essential for any position in business, but especially for a data analyst. You need to be able to explain complex ideas in a way that everyone can understand.

Data analysts often need to communicate their findings not only with their colleagues within the company they work for, but also with clients or other stakeholders outside the company as well. They should have strong writing and communication skills so that they can effectively communicate their findings and ideas. 

Do I need a college degree to start as a Data Analyst?

While college degrees are important, it is not a must to succeed in this role. Start small with learning the right tech skills, apply for an internship or do a freelancing job with popular platforms like Fiverr, Upwork, Freelancer. This will give you the right experience and you can apply for that dream job of yours.

That being said, computer science or statistics degree program would definitely give you an edge when compared to other candidates in terms of finding that dream job.

If you are a business analyst or a technical analyst in domains (like healthcare, insurance, media etc), and looking for a career switch in technology, this could be a very good option for you. There is often an overlap as far as the skills are needed in the analyst roles.

Your career trajectory as a skilled data analyst is dependent on your leadership skills and your technical skills.



Data analyst career path can be extremely rewarding. You can work on projects that impact businesses large and small, and you’ll be in charge of your own career growth. Like with any other job, be prepared to change your outlook on what’s possible and be willing to take on new challenges in order to succeed in your professional career.

Further Reading:

How to start your career in Data Science and Machine Learning

How to become a Full Stack Developer