How to Become a Data Analyst in 2023

In today’s world, data is an asset for any organization. There has been a sudden increase in the use of apps and websites in the past couple of years. As the number of users, they are increasing, there is an increase in data coming to these apps and websites. This data could be of great use to the companies if they come up with meaningful insights from this unstructured data. If you love to work with data, then it could be a great career choice. The job openings for Data Analysts are increasing every year. Data Analysts with the right skill sets are in high demand. It is a great time to start your career as a Data Analyst. The need for Data Analysts is more than the supply.

In this article, I will try to give you a brief about Data Analysts, their roles and responsibilities, complete roadmap, salary, etc.

Let’s dive in.

What is Data Analyst?

Data analysis is a subdomain of big data. We can define it as “finding useful information from a bunch of unstructured data.”

The person doing all this analysis and trying to find meaningful insights that could be helpful for his organization is known as a “data analyst.”

Roles and Responsibilities

The Data Analyst acts as a bridge between the transformed data (given by the data scientists and the engineering team) and the clients & customers.

The clients can vary from company to company. If you are in a service-based company, you can have some external clients (various other companies and brands). In the case of a product-based company, it can be an internal team. It could also be a freelance project for you.

Let’s take an example of a food ordering company. All the raw data (customer, orders, search data, etc.) that comes into the company goes to the engineering team. The data scientist converts the raw data into transformed data. But, CXOs or the product team can’t understand this data (sometimes in millions). It is where the work of Data Analysts starts.

The data Analyst takes this transformed data and pulls out the required information. He does this as per the requirements of the internal team or clients. The main work of a Data Analyst is to represent this meaningful information in a manner that his internal team or CXOs can understand. It can be pie charts, graphs, heat maps, line charts, etc.

They act as a bridge between the engineering team as well. A data analyst takes all the requirements from their internal team and sends them to the engineering team. The engineering team transforms the raw data according to the need and sends this data to the Data Analyst. The data analyst then represents this data in a meaningful manner.

Roadmap to Data analyst

There are a lot of tools and technologies a Data Analyst use daily. A structured roadmap is suitable for a beginner to start as a Data Analyst. We will see all the tools and technologies in a structured way. The roadmap for a Data Analyst is as follows:-

Programming language

The programming language used in data analysis is Python. Python is also known as the language of data. You can start with basic concepts such as loops, functions, syntax, Python data structures, etc.

Many people argue why programming is even a requirement in data analysis. You can’t just rely on enterprise tools if you want to grow your career as a Data Analyst.

After learning these topics in python, you can move on to data exploration libraries in Python. Two of the most widely used libraries are Pandas and NumPy. Pandas is used for data analysis-related tasks in python.

Data Structure and Algorithms (DSA)

It is one of the most debatable topics in the data analysis field. Basic DSA is a must-have if you want to be good at data analysis. You don’t have to be a pro coder. Learn data structures such as strings, linked lists, arrays, queues, and stacks. Do some practice problems on them. Practice Problems up to medium level are sufficient for you.

Database

We all know that the primary use case of a database is to store data and information. It is a basic need for Data Analysts on what kind of databases they need. First, you should know the fundamentals of DBMS (database management system) before learning a database.

Transactional (MySQL, Postgre SQL) and NoSQL (Cassandra, MongoDB) databases are two database types you need daily as a Data Analyst.

Structured Query Language (SQL)

SQL is one of the most important things to learn as a Data Analyst. Start with the topics like the min & max operations, logic, tables, etc.

SQL is a must-have while preparing for Data Analyst interviews. It has a weightage of around 30 to 40% in Interviews.

Big Data fundamentals

Data analysis is a sub-domain of big data. You can start with basic terminologies like distributed computation, distributed storage, file formats (JSON, CSV, PARQUET, etc.), data (structured, unstructured, and semi-structured), etc.

After that, you can learn frameworks such as HIVE (data warehousing tool).

Dashboarding tool

As a Data Analyst, your primary focus is on the data representation part. The dashboarding tools are simple drag-and-drop tools used to make charts, graphs, etc.

Tableau and Power BI are two of the widely used dashboarding tools. They are used to analyze data, extract insights, and share it across various departments within your company.

Data warehousing

We store the transformed information in a properly structured form. It is also known as data warehousing. Some of the widely used tools are HIVE, Amazon REDSHIFT, etc.

It is also a must-have for Data Analyst interviews.

MS Excel

We all know Excel is a well-known office tool. Excel is still a popular choice by data analysts in case of a meeting or presentation with external clients. Most of the clients prefer Excel for this.

Excel is mainly used for data manipulation, applying functions on a list, and creating pivot tables, charts, graphs, etc.

ETL (extract, transform, and load) tools

The use of these tools is to make a connection to multiple data sources. For example, joining data sets, databases, tables, etc.

Widely used tools are Informatica and Tabular. They are used to enterprise extract, transform, and load the data from the sources.

Statistics

As a Data Analyst, you will use statistics regularly in your work. Some widely used topics are Mean, Median, Mode, Standard deviation, Permutation & Combination, Probability, etc.

Salary of a Data Analyst

According to AmbitionBox, the average salary in India is around ₹4.2 LPA.

Soft skills

Data Analyst is a job profile in which you deal with clients daily. So, soft skills play a vital role for you. Some of the soft skills you should learn are the following:

• Good communication skills
• Presentation skills
• You should be good on the Documentation part

Conclusion

With the increasing use of apps and websites, the demand for Data Analysts is increasing every year to deal with the humongous amounts of data coming to these applications and websites.

I hope this article will help you to understand Data Analyst, a roadmap to Data Analyst, Salary, etc.