How To Build a Successful Data Analyst Career?

Clive Humby, a data scientist and mathematician, rightly coined the phrase ‘Data is the new oil’. An increasing number of companies are turning to data for insights and business decisions. However, they need skilled data scientists for this purpose. The demand for data analysts far exceeds the availability of professionals in the domain. There are opportunities for data analysts in almost all industries, So become a data analyst with the help of some of the free online certification courses and enhance your career. 

The Role of Data Analysts

Let’s take a closer look at this profession that may intrigue many amongst us. This may be a good starting point to clear some doubts about the profession and understand how it’s different from other data-related careers, like data scientist or data architect. To begin with, data analysts gather, organize and analyse data sets. They get insights and meaningful answers to business problems in almost every industry.

Whether a retail organization has questions regarding its customer behaviour, or a manufacturing firm needs some insight into its production data, they turn to data analysts for exploiting the full potential of the data. Even social and government organizations use data analysis for intelligence on several factors. Health organizations improve patient care with the help of analytics. It’s even used in agricultural practices. While evidence-based decision-making is not fool-proof, it’s several times more reliable than just instincts. Companies benefit from evidence-based decision-making and strive to optimize the process of data collection, storage, and mining.

The process of data analysis starts with raw data that’s collected through various appropriate channels. The raw data is usually chaotic so it must be first cleaned and organised. Post that, the data analysts use statistics, programming, visualization, and logical techniques to arrive at conclusions that help companies make data-driven decisions. Some of the functions that are part of a data analyst’s role are:

Data Infrastructure

Data analysts work with cross-functional teams to establish a robust infrastructure to streamline data collection and organization. They are also involved in setting the guidelines for data storage and collection. Considering the time required for cleaning data and understanding the missing data, this part of the process is extremely important.

Understanding Goals, Data Gathering and Cleaning

Data analysts must understand the goals and problems before starting the analysis process. Once they know what needs to be achieved, they decide the data to be used. The data is collected either directly by the company through surveys, websites/apps, or sourced from external agencies.

After collection, data is thoroughly checked for duplicates, missing quantities, errors, and outliers. The data goes through several stages of quality checks and the final version is ready for exploration. The process of cleaning uses programming methods to maintain a standard quality.

Data Modelling

Data analysts must design the structure of the database and the relationship between all the entities in the data sets. This is extremely critical and requires expert handling to get the desired answers.

Data Interpretation

Data interpretation is scientific in nature but has elements of creativity and inquisitiveness. That’s the reason it’s considered a combination of art and science. The interpretation depends on the questions asked by a data analyst. And that requires some out-of-the-box thinking and imagination in asking questions that will help them derive the most meaningful insights.       


The insight derived from data is useful only if it can be understood by all the stakeholders and utilized properly. Therefore, data analysts must be able to convey the insight to everyone involved. It should be visual and interesting as all the stakeholders will rarely be with a technical background in data analysis. Storytelling is the key to presentation.

Tools of The Trade

The various stages of data analysis require the usage of different types of tools. Some of the common ones are SQL, Tableau, and SAS. Programming languages like R and Python are also commonly used along with R Studio and Jupyter Notebooks respectively. In several projects, Microsoft Excel or Google sheets may find good use.

How to Become a Data Analyst?

A data analyst can find a job in almost any industry. However, there are certain steps that you must take to be ready with the skills and experience required for the job. Although there’s no single path that’ll set you up for a highly desirable career in data analysis, the following ways will certainly be helpful.


A sound foundation is always a good place to start. If you’ve made up your mind to pursue a career in the field, then you must learn the tools and fundamentals of data analysis. Having a thorough knowledge of a programming language like Python or R is essential. SQL is a simple query language used to work with databases. As a data analyst, you must create, read, update and delete data, and that requires a good level of knowledge of SQL. Even when you handle large data sets, SQL will come in handy.

Knowledge of statistics and math is also a primary requirement. All the requisite concepts must be grasped properly. Even though tools solve the problems, in-depth knowledge of the concepts is always beneficial.

Half of the work is done when you analyse data and get some meaningful insight from it but the other half remains pending if the insights can’t be communicated to the stakeholders. Communication is extremely important and you must learn all the data visualizations techniques including graphs and charts. After all, it’s a story that must be presented in an interesting manner.

Problem Solving Skills

Getting a good grasp of the problem and having creative skills to approach the data analysis process to solve the problem is a prerequisite. Before you start the process, you must be able to identify the right data and the method of analysis that would be best for the purpose.

Domain Knowledge

While data analysts may not be domain experts, it would be advantageous to know about the industry. This is required to understand the problem also.

Real Projects

There’s no substitute to experience. Before you start trying to get a data analyst job, you must test your learning by doing a real project. There are several sources of real data that can be used for data analysis projects. Do several of those and build your portfolio. This portfolio will help prove your technical skills.


If you have an impressive portfolio, there’s a good scope for getting your first job as a junior data analyst. However, if you don’t get a paid job, doing an internship is the next best thing. This way you will get an idea of the workplace and you may get absorbed by the company after the internship is over. Even if this company doesn’t offer you a full-time opportunity, other companies may find your candidature interesting.

Data Analyst – A Growing Field

Various reports show that data analysts’ skills are in high demand globally. So, if it’s a career that you wish to be in, then you must acquire the skills and get some experience. If you do the needful, you can be part of this growing field.

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