A report from McKinsey Digital on big data states that by 2023, the big data industry will be worth an estimated US$77 billion. That is a lot of money! The report also states that 90 percent of the data available right now was produced over the last two to three years. That is how quickly the data is produced. What I am trying to say is that the increase in the production of data leads to an increase in the need for someone to analyze the data. That is where data analysts come in the picture.
So, it is safe to say that data analysts have a bright future. In this blog, we will learn
What is data analytics? Watch this YouTube video created especially for beginners:
What is Data Analytics?
The simplest explanation of what is data analytics is that it is the science of analyzing the given data in its raw form and making clear insights and reports on it so that it can be understandable to everyone. The main purpose of data analytics is to optimize the performance of the company.
By using the data-driven approach or strategy, a company can cut back on expenditures. A company using a data-driven approach is more likely to make better decisions; this will help the company to make better-suited products for the customers.
Data Analyst’s Roles and Responsibilities:
Data analysts are professionals who translate numbers, statistics, and figures into plain language for everyone to understand. Considering the past and present trends, we can say that the scope for data analysts at the workplace is increasing.
If subjects such as mathematics, statistics, and computer science excite you and you are willing to work in a field that has a combination of these, then the job of a data analyst will be a perfect fit for you. Data mining, Python, and Structured Query Language (SQL) will play a major technological role in the post of a data analyst as they are required to extract insights from data sets and to make reports and visuals.
Check out Data Analytics Training to learn more about Data Analysis & techniques used for meaning insights.
Data Analyst Skills
Skills are an important factor when it comes to success in any field. Every field out there requires some specific skills for success. Likewise, the data analytics field requires some specific skills. This section will briefly discuss the skills required by a data analyst.
- Data cleaning and preparation: When it comes to data analytics, the first step is to clean the data and prepare it for the next stage of analysis. The data you will work on may come from various sources, so it is your job to clean the data. Cleaning data, in a sense, is dealing with null and inconsistent data and removing unwanted data.
It is also a kind of critical thinking skill of knowing what data to collect and what data to delete. As said earlier, it is the first step of the data analysis process, so data cleaning and preparation is one of the key data analyst skills.
- Mathematics and statistics: Numbers and statistics are the two things that a data analyst primarily works with. A deep understanding of statistics is crucial since it will make the exploratory process much easier and you will have an understanding of what data you are dealing with. So, having a strong foundation in probability and statistics is one of the must-have data analyst skills.
Oftentimes, data analysts use statistics to provide meaning to bigger data, which helps other people to understand and know about those bigger data sets. Based on the demands of the role and data you are going to work with, the level of statistical knowledge required will differ. If you are working in a company with probability analysis, you will need a thorough knowledge of statistics since you will be working with complex data sets.
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- Technical or programming knowledge: The primary role of a data analyst is to extract data from given data sets. So, to extract data, you will need to know some programming languages. Python, R, and SQL are the most commonly used programming languages that are used in the field.
SQL is used when large sets of data and processing information are being handled. It is a spreadsheet and computing tool that is much quicker and efficient than traditional spreadsheets. Since it is one of the valuable tools, knowing its functionality is one of the key data analyst skills.
Even though a spreadsheet is a very common tool in data analytics, having knowledge of statistical programming languages, such as Python and R, is better since statistical languages do work more quickly and efficiently, and they can handle what the traditional spreadsheets cannot. Python and R are industry-standard languages that are used to perform predictive and advanced analysis on bigger data sets. Hence, knowledge of these languages is also an important data analyst skill.
Knowing only SQL might be a problem for long-term career growth, hence we suggest learning either Python or R.
But, which is better?
Since R is built specifically for analysis, it is preferred by some data analysts over Python. But, both languages are open source and free for everyone to learn and use.
In some instances, you may probably need to extract data from complex data sets, so knowing these languages will help you by making the complex extracting process a bit easier.
- Data visualization: Data visualization is an important data analyst skill because the end product of data analysis might be a data-driven business strategy. Everyone in a meeting needs to know what was in the data. As a data analyst, you need to know how to present data in a way so that everyone can understand it. You cannot expect a developer to understand a giant spreadsheet of data.
Humans are visual learners; you can use graphs and other illustrative methods to convey the information in a way that is understandable for everyone.
You, as a data analyst, will make data visualizations for the trends and patterns in data. This means that you have to make clean and visually appealing charts and graphs. Data represented in the form of charts and graphs tend to make much more impact on humans than data based on numbers.
- Writing and communication: After conducting data analysis processes, you will have to present the data research to the employers. You should be able to explain your findings in a way that is understandable for everyone. So, public speaking is also one of the key data analyst skills. You must be able to present data as effectively as possible so that everyone is able to follow along with you.
You may be asked to submit a written report on the data that is analyzed by you, so good writing is also a desired data analyst skill.
To be a successful data analyst, you should be able to analyze data and explain it clearly without any confusion. Technically strong data analysts will have fewer chances of success if they are not able to communicate well.
To crack interviews, go through these Data Analyst Interview Questions and Answers.
Salary of a Data Analyst
The ultimate focus of working hard every month is to gain some economical value, i.e., money. The average salary of a data analyst in India is around ₹440,769. This salary is decided by multiple factors including the analyst’s experience, the city they work in, etc.
You can get full information about the Data Analyst Salary in India through our blog..
Data analyst salary by experience: Experience is one of the most important factors when it comes to salary. Your pay for the job increases as you get more experience in the field. Now, let us take a look at the salaries of data analysts according to their experience.
|Early career||1–4 years||₹425,661|
Data analyst salary by city: Salary by city sounds confusing, right? Let me explain. The salary given to you will be based on the living expenses in a particular city. It may also depend on multiple other factors. So, basically, if you work in a city where the living expenses are high, then you can expect a high salary. Now, let us take a look at how data analysts are paid across cities in India.
- A data analyst in Bengaluru earns 17.4 percent more than the national average salary.
- The same data analyst in Gurugram would earn 5.2 percent more than the national average salary.
- In Pune, the data analyst would earn 4.8 percent more than the national average salary.
- The data analyst in Mumbai and Delhi would earn 7.5 percent less than the national average salary.
- In Chennai, the data analyst would earn 6.8 percent less than the national average salary.
I hope this blog gives you some insights into the skills required by a data analyst to have a long, successful career. Skills are the deciding factor on whether you get high-paid jobs or not. The numbers that are provided above are just to give you some context. But, if you have the right skills, you can get a job with a high salary even early in your career.
To pursue a career in this domain and become a successful Data Analyst with a high-paying salary, you can sign up for Intellipaat’s online course for Data Analysts today! This course will help you in the early stages of your career as a data analyst by helping you to develop various skills.
Also, if you have any more doubts, you can post them on our Community!