A Guide To Data Analytics Jobs, Types, Skills, And More

November 2, 2024 Mallika Basu

Data has become a decisive benchmark for any organization’s performance. The field of data analytics has a broad scope which includes different techniques and goals. Data analytics work simultaneously with information technology, statistics, and business. They synthesize these fields and provide productive strategies to help organizations grow further. In other words, data analytics jobs are the instrument for the highest decision-making of any organization. And so, the demand for data analytics is going to skyrocket high in the coming future.

What is Data Analytics and Its Importance?

Data Analytics is a scientific process of drawing conclusions from raw data after examining and analyzing it thoroughly. It is done with the help of specialized systems and software. Data analytics are widely used in e-commerce, retail, and the IT sector to allow organizations to perform better.

It is even used in science and research departments too for verify or disprove methods. The primary goal of a data analyst is to increase productivity and improve the performance of an organization’s business by discovering significant patterns and information in the derived data.

The implementations of data analytics are apparently endless. Every day millions of data are being generated, to handle those data efficiently data analytics is the only option — to deal with this situation applying data analytics to more aspects of business, science, technology, and our everyday life is rather undeniable.

and our everyday life. As a result, data analysis skills are quite in demand which also increased the demand for data analytics jobs in the industry.

Types of Data Analytics Jobs

Medical & Healthcare Analyst

Medical and healthcare analysts use data collected from different sources to help improve healthcare systems. They provide information to improve patient care facilities, streamline operations, and things like that.

Business Analyst

Business analysts use data to provide business insights and guide organizations to grow further. They can locate any issues inside an organization, like employee development, IT systems, organizational structure, and more. Business analytics is turning into a crucial part of how organizations work as organizations are constantly growing with all of their effectiveness and cutting costs.

Market Research Analyst

Market research analysts are likely to be weather forecasters of the market. They collect and analyze consumers’ and competitors’ data to predict market situations. They research market conditions to forecast future sales of a product or service and they also help businesses to determine on customers’ wishlist, like what, when, and how much.

Business Intelligence Analyst

Business intelligence (BI) analysts analyze data and other information to guide organizations to make wise decisions. They collect, clean, and analyze information about the company’s sales, revenue, and consumer engagement metrics to improve business. BI analysts sometimes develop tools and data models to aid in the monitoring of data.

Operations Research Analyst

Operation research analysts are known as high-level problem solvers. They use mathematical modeling, data mining, statistical analysis, and optimizations to provide solutions to organizations for working more effectively and efficiently.

Intelligence Analyst

Intelligent analysts analyze data and information like, internal and external statistics, databases, and field reports to identify and mitigate security issues. They must have deep research, comprehension, and analytical abilities to unify the information and make action plans.

Roles & Responsibilities of Data Analysts in the Industry:

Every day every second data is generated while using any device or technology. The estimation of the total amount of data generated all around the world every day is 2.5 quintillion bytes. With that amount of data, companies can grow their businesses worth billions.

Regarding this matter, companies hire data analysts to handle the data and give value to the businesses. Furthermore, the roles and responsibilities of data analysts can be determined by the companies they work for. Data Analysts’ roles and responsibilities in an organization are:

Data Mining: Data analysts extract data from multiple sources, both primary and secondary. Then, they processed that data and make it presentable to understand it easily.

Maintaining Databases: Data analysts help to design and maintain database systems. This includes reading, creating, updating, and deleting databases.

Data Preparation: Data is collected from multiple sources in raw form. Data analysts then have to convert the raw data into structured ones by resolving the errors, removing irrelevant data, and identifying the potential data. They apply different types of data-cleaning techniques to make them presentable to others.

Collaboration: Data analysts collaborate with other team members, like programmers, engineers, and organizational leaders to identify and analyze process improvement opportunities, give recommendation system changes, and develop data governance policies.

Preparing Reports: Data analysts prepare reports presented in graphs and charts are very crucial data relevant to effectively communicating trends, patterns, and predictions.

Quality Assurance: Most businesses rely on data for their day-to-day pursuit. Data analysts make sure that after extracting and cleaning the raw data whatever data they have in their hands is relevant to the business and will help in the growth of the business.

Data Security: Data and information are vital resources for any business. So, therefore, maintaining and securing data and information are the foremost responsibility of data analysts.

Troubleshooting: Sometimes there are troubleshooting issues occur related to information, reports, and databases. Data analytics can resolve that issue.

Benefits of Data Analytics:

Data is the new oil of our modern world and so government organizations and companies are focusing on it to make better products and provide high-quality services. There are a handful of benefits that needs to be mentioned :

Personalized Experience

Organizations collect information on customers from different sources. Data analytics use different techniques to make a comprehensive customer profile from those data to provide insights into customer behavior. It will allow businesses to promote better-personalized experiences.

Inform Business Decision-Making

Organizations can use data analytics to make better business decisions and minimize financial losses.

Streamline Operations

Organizations can improve their operational efficiency with the help of data analytics. Data analytics can identify the cause of past setbacks and can predict future issues. Moreover, regarding the prime supply of an organization’s products based on factors, like holidays, seasonality, and temporal trends, data analytics can create a statistical model to provide efficiency.

Optimize Risk Factors and Handle Setbacks

Data analytics can help an organization to understand the risk factors and take preventive measures. Businesses can also use data analytics to optimize losses after a huge setback. It can help with determining the optimal price for a clearance sale as well as can create a statistical model to make recommendations automatically to resolve this recurrent problem.

Enhance Security

Data security threat is a common problem for all businesses. Organizations can use data analytics to identify the cause of past breaches by processing and visualizing relevant data. IT departments can also use statistical models with the help of data analytics to prevent future attacks.

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Reasons Why You Should Choose Data Analytics Job as a Career:

Data analytics is a hot new trend that navigates businesses towards higher productivity. Organizations hire data analytics for better outcomes. It guides organizations to make effective business decisions for better performance with the help of derived data through different techniques and tools of data mining.

Pursuing a data analytics career would be the right move in this digital era where data is the most valuable object. Here are some reasons:

World Wide Record Level Data Generation

The most obvious reason to consider a career in data analytics is a huge supply of data is a crucial component of any organization for growth and a massive amount of data is generated every day.

Global IOT connections created a data volume in 2019 that reached 13.6 zettabytes, and it is expected that this number will go up to 79 zettabytes by 2025.

Digital Transformation & Innovation

We are moving towards digital transformation and innovation where data is the key component. In this digital era, artificial intelligence and big data technologies are the two key investment sectors where data analytics is a must. Therefore, this is another important reason to choose a career in data analytics.

Data Analytics is in High Demand

In the last few years, especially since the pandemic, there has been a considerable rise in how data is collected and converted for business intelligence and decision-making. With the new era of digitization, new technologies are being invented to enhance businesses, therefore, data analysts will become more and more valuable to society leading to an excellent career with job security.

Ample Range of Job Profiles to Choose from

In this digital era, from healthcare and technology to finance and retail, every organization is using larger data sets to accomplish their needs as well as goals. This presents an excellent opportunity for data analytics to choose a job from a vast sector. They even can get to choose a specialized field for themselves. In other words, regarding job profiles and domains, data analytics have plenty of options for choosing a job in the industry.

Attractive Wages

Attractive wages are another alluring aspect of a data analytics career. As the demand for data analytics is increasing rapidly, salary packages too getting a high rise. With the supply of experienced data analytics very low, salary packages will remain alluring for deserving candidates. Further, since data analytics professionals with the required skills are inconvenient at the moment, one can expect a satisfactory wage with the right knowledge and expertise.

A chance to grow

A career in data analytics will not only help you to flourish but also hone your skills. Having appropriate technical skills in data analytics will let you shift easily and grow more with the industries that are best aligned with your interests.

Skills Required for Data Analytics Jobs as a Career:

Data analysis is after all about retrieving and processing essential information from unprocessed data sets and making it presentable to all. On any regular day, data analysts will use different skills to do their job. That being said, to perform their work properly data analysts not only need hard or technical skills but also a handful of soft skills too. These soft skills are necessary for one to thrive in the field of data analytics.

#Technical Skills:

There are several technical skills needed to perform the data analyst job. The important ones are:

Data Visualization:

It is tough to find where data visualization is not required in a data science field. Without it, data analysts cannot present any findings understandably which makes data visualization the number one key technique in the data analyst job. As the term represents, data visualization is a technique data analysts need to present the findings via graphs, charts, or other illustrations.

The purpose of this technique is it makes data-driven insights more accessible to all, even to those who are not trained in data analytics. For example, with data visualization data analysts can help a business person to understand complex things easily which then helps in decision-making.

Data Cleaning and Preparation:

Research shows that most data analysts spend 80% of their time on data cleaning and preparation. It means data cleaning and preparation is another vital key for data analysts. Retrieving data from one or more unprocessed data sets and then preparing that data for numerical and categorical analysis are the most common jobs for data analysts.

Data cleaning also includes removing and fixing all inconsistent data to improve the data analysis. Properly cleaned data with a simple algorithm can produce unique insights, whereas, uncleaned data will bring out misleading patterns that will eventually lead a business toward wrong conclusions.

MATLAB:

MATLAB is a programming language for technical computing. It is a matrix-based language that enables computational mathematics in the utmost natural expression. In other words, it supports algorithm implementation, matrix manipulations, and data plotting, among other functions.

Businesses working in big data have started to use MATLAB as it helps analysts to reduce the time drastically for pre-processing the data, like quick cleaning, organizing, and visualization.

Another vital feature of MATLAB is it can execute any machine learning models built in its environment across multiple platforms. Understanding MATLAB is not a requirement to get Data Analytics Jobs, although knowing how it works can be crucial while working in big data sectors and can boost one’s marketability as well.

R is one of the widely used languages in data analytics jobs. Its system and structure are built to support analytical work. It surrounded several built-in, easy-to-use data organization commands by default, and can operate on complex or more extensive data. Institute of Electrical and Electronics Engineers (IEEE) professional journal, Spectrum conducted a poll on the top 10 programming languages used in 2019.

It showed that R ranked 5th on that list. This means only one thing and that is due to R’s popularity and comprehensive functionality, getting skilled in R should be one’s top priority.

Python:

Python is another programming language one should get skilled in to enter data analytics jobs as it provides a variety number of specialized support systems, many of which are specifically artificial intelligence (AI). It landed the number 1 spot in IEEE’s Spectrum 2019 survey.

Understanding Python would be a huge help to one’s career as an AI-concerned system is in demand in our current professional environment and is still increasing. Aspirants who want to have a good grip on Python should look into its auxiliary programs such as Pandas or NumPy, a bundle of programming languages that assists Python users with scientific computing tasks.

SQL:

There are several database languages available among those the first and foremost is Structured Query Language, better known by its acronym, SQL. In modern analytics, SQL presents the standard means for querying and handling data in relational databases. SQL was created a long time ago but because of its functionality and continuing effectiveness keep its demand high everywhere.

So the fact is SQL has a niche everywhere and its popularity is not going to diminish soon. In simple words, one should master the skill of SQL to enter into data analytics jobs. Branded versions of SQL, such as MySQL, are good for a better understanding of relational database management systems.

Machine Learning:

Machine learning is not learning a skill like data cleaning or other programming languages. But having a good grip on this one will definitely help one to become competitive in the field of data analytics jobs. Having an overall understanding of related tools and concepts will give one a much better prospect regarding job search.

Linear Algebra and Calculus:

A good grip on advanced mathematical skills is non-negotiable for entering data analytics jobs. Linear algebra and calculus are the two foremost mathematical studies in the analytical field. Machine and deep learning are two applications of linear algebra, which support vector, matrix, and tensor operations.

Calculus is used to build the objective, cost, and loss functions that teach algorithms to achieve their objectives. Nonetheless, one may find that having a robust theoretical background is not that important for pursuing analytical jobs. In reality, there is no other way to become a data analyst without it.

Microsoft Excel:

Having a skill in Microsoft Excel, one shall find less important considering that data analysts have other significantly advanced programming languages at their disposal. Excel is inconvenient in comparison to other platforms yet, this platform is used by millions of people worldwide.

Excel presents certain features and commands for better data analysis. It has its own programming language, VBA, and utilized properly can save a lot of time for data analysts for repetitive projects, such as accounting, payroll, or project management. Microsoft also developed its Analysis ToolPak for statistical modeling and data analysis.

#Soft Skills:

There are a handful of soft skills required to achieve success in data analytics jobs. The important ones are:

Critical Thinking:

As data analysts, it is not enough to just look at the raw data. One has to think hard and do things differently to understand the data and extract specific insights from it. It is an undeniable fact while processing the data one has to go above and beyond with thinking despite the support system of programming languages.

Becoming a critical thinker can be hard to work but it can be possible with practice and in time. To become a data analyst one should give importance to honing critical thinking skills because without it analytical job would be hard.

Problem-Solving:

Problem-solving is another major soft skill for data analysts. Data analysts face divergent problems every day relating to analytical work and being able to solve the problems would be one’s way to accomplishing the key skill of problem-solving.

Despite of constrain of resources one has to find a way out of problems. Even sometimes, data analysts would provide remarkable problem-solving methods using the available resources that would make a difference in the job. Simply put, problem-solving skill is an undeniable asset for any data analyst.

Communication:

Communication skill is undeniably a significant skill required everywhere and being able to be a good communicator is itself a great achievement. To become a good data analyst one needs to be able to explain fluently and in a way so that others including non-technical persons could understand the insights as well as the patterns easily.

Check here the best data analytics courses:

Scope & Future of Data Analytics Jobs in India:

For the past decade, India has experienced exponential growth in the data analytics industry as a result of emerging internet users. During covid-19 Internet penetration got doubled from 20% in 2018 to 41% in 2019, and this number is expected over 900 million by 2025, according to World Bank.

This growth is supported hugely in the data analytics industry with a remarkable increase in data collection, which can be used potentially in various markets.

In India, widely used big data sources are the foremost reason for the bright future of data analytics with high levels of employment, assuring of better wages, and most of all high demand for data analytics in the coming future.

Major Sectors for Data Analytics Jobs:

According to industry analysts, India is the top market-leading country in data analytics. For the past decade, India has been transforming in different sectors, and as a result, there is significant growth in data gathering around us every day. So, now it is a necessity for every business, firm, and sector to have data analytics for handling the data to improve and grow. Major sectors for data analytics in India are:

IT Sector:

The IT sector holds the majority of the share (43%) of the data analytics industry in the market. Some of the IT giants in India are Accenture, Tata Consultancy Services, Cognizant, Infosys, Capgemini, and Wipro. IT industry is all about cyber security which is a very advanced one.

Regarding this matter data analysts are in high demand as they have the expertise to handle big data. Moreover, they are working together with cybersecurity experts to face the challenges regarding cybersecurity defense. Also, there have been significant innovations in several industries through the IT sector.

Banking, Financial Services, Insurance Sector (BFSI):

BFSI is the second largest sector in the data analytics industry with a market share of 13.9%. This sector has witnessed the rise of several companies with the help of data analytics. The third largest sector is India’s Fintech market. E-commerce such as Phone Pay, Paytm, MobiKwik, and Policy Bazar have used data analytics and AI to grow their business.

E-Commerce and Retail:

The e-commerce sector was at an estimated US$50 billion in 2020. E-commerce business operates 1.2 million transactions every day, according to NASSCOM. This sector is anticipated to pass the US and become the 2nd largest retail market by 2023.

These sectors own 5.9% market shares in the data analytics industry. Both the industry has been using data analytics for predicting trends, providing better customer services, and streamlining warehouse operations.

Since 2014, India has been investing considerably in big data to increase its effectiveness. To improve the lifestyles of citizens, nearly 75% of big data is helping government departments. The government has also taken initiatives to create big platforms for big data sets which will require the acquisition and manipulation of large amounts of data.

Healthcare:

Analytics can give the necessary assistance regarding the diagnosis or probable outcome of the treatments for people suffering from specific illnesses. The healthcare industry is one of the most promising sectors in the data analytics industry in the coming future time.

Expected Salary in Data Analytics Jobs:

A data analyst’s annual pay might range from Rs1.9 Lakhs to Rs11.2 Lakhs with an average annual salary of Rs4.3 Lakhs. Financial and technological companies pay more than the national average, according to the job listing on the websites.

The role of data analysts is likely the first step in the world of data science. So data analysts can step up to positions like data scientists, senior data analysts, analytics managers, and business analysts, according to PayScale. The wages for these positions have also increased significantly. The average wage for data scientists is Rs10.6 LPA, and the starting salary for analytics managers is around Rs20.1 LPA.

FAQs: Data Analytics Jobs

Q1. Is data analytics a high-paying job?

Data analytics is a highly satisfying job. It guarantees financial satisfaction at both entry-level and experience-level. According to Payscale, the average salary of data analysts in India is around Rs1.6 Lakhs per year, while senior data analysts can earn Rs3.0 Lakhs to Rs21.8 Lakhs with an average annual salary of Rs8.0 Lakhs. After getting a more advanced degree in PG Data Science one can have a much higher salary job.

Q2. What is a career in data analytics or is it a wise choice to pursue data analytics jobs?

There are numerous opportunities for jobs in data analytics career. Today’s world is all about data, and the rising demand for data-driven industries makes this job profile much more confident and demanding. Therefore, a career in data analytics is definitely a better choice for high wages job and a secure future.

Q3. How do I start a career in data analytics jobs?

After getting a bachelor’s degree one should have a fundamental knowledge of data analytics and upgrading practical skills through working on projects, building skills in analytical problem-solving, and developing skills in communication to start a data analytics career.

Q4. What is the purpose of data analytics jobs?

Data Analytics is a field of processing information. Data analysts process raw data to collect the required information which then can be used to improve decision-making and grow organizations in the future.

Q5. Is a math background necessary to pursue data analytics jobs?

Yes. It is necessary to have a certain level of mathematical knowledge to pursue data analytics as this field required data handling with effective problem-solving abilities.

Conclusion: Data Analytics Jobs

The data industry is a huge industry and it is predicted to keep growing. It is expected to touch US$11.87 billion by 2026 as it keeps flourishing at a steady pace. The data analytics industry is projected to create 11 million jobs by 2026. The data analytics industry of India is expected to play a significant role in the future of Industry 4.0 and with this create considerable job opportunities and provide better lifestyles for its citizens.

In India, following the path towards digitization, and the establishment of new data centers are the stepping stone for the data industry. This industry will just not only disrupt the market but also will cause a huge shift in it and will bring several job opportunities with it.

Vaibhav Kakkar