Thinking About a Career in Data Analytics? Here’s What You Should Know

The LinkedIn Economic Graph reports that there are 1.3 million AI-related job opportunities available globally. So, if you are considering a career in data analytics, you’re looking at one of the most in-demand jobs available, where there’s a serious talent gap.

In fact, data analytics comes under the “new collar” roles, which are redefining the workforce.

Unlike the typical four-year college degrees, new-collar jobs are technical, high-demand positions. The priority is specialised knowledge, certifications, and practical experience.

Are you planning on taking a data analytics course but still have doubts? Let’s answer a few questions that most of you may have.

Is data analytics a good career choice?

If you are naturally a great problem solver, looking for a high-paying role, currently a career in data analysis is a fast-growing and future-proof option.

There is an industry-wide need for talented data analysts, so demand is quite high. In the interest of transparency, you should know that the market for entry-level positions tends to be saturated. But, if you’re willing to grow with the role, you can enjoy a stable, lucrative career.

Will AI replace data analysts?

Contrary to popular belief, AI is not going to replace data analysts. But, if you expect to thrive in this field, make sure you leverage AI tools to automate routine tasks and boost your efficiency.

The U.S. Bureau of Labor Statistics (BLS) estimates that data analyst/science positions may surge 34 percent between 2023 and 2033

All routine or repetitive tasks, such as cleaning data, creating reports, and carrying out preliminary analysis, can be handled by AI. On the other hand, human workers are always required for their unique insights, context awareness, subject matter expertise, and critical thinking.

But, yes, as a data analyst today, you would become redundant if you are not well-versed with tools like Microsoft Power BI, Tableau, Julius AI and other popular ones.

Very often, people get confused between the terms data analytics and data science. Let’s clear that up.

Data Analytics Vs Data Science

Even if you may have heard of both data analysis and data science being used interchangeably, they are not the same.

It’s true that both roles involve helping businesses leverage data to extract value, but they are not identical.

	Data Analytics	Data Science
Focus	Past data	Future predictions
Work	Find patterns	Build prediction models
Tools	Excel, SQL, BI tools	Python, R, ML tools
Maths	Basic statistics	Advanced statistics
Example	Analyse past sales	Predict future sales

Let’s get a more detailed idea of both data analysis and data science.

What is Data Analysis?

Data Analysis is the systematic practice of collecting, sorting, storing, and analysing raw data in an effort to glean patterns, insights, and trends that a business can use to make informed decisions and enhance profitability.

For a while now, data has been called the new oil. But the oil would remain unusable if it were not extracted and refined by professionals. That’s where data analysts come in.

So, in case a retail store maintains a monthly sales report, they to pinpoint peak purchase time/days. If the data reveals that Thursdays are the busiest day at the store, it allows them to schedule more staff, improve customer service, and increase revenue.

That’s the basic idea.

What is Data Science?

Data science uses scientific methods, algorithms, and AI to study data (both structured and unstructured) to gain valuable insights, patterns and predictions of various business goals and decisions.

Data Scientists need a blend of skills, including mathematics, AI, statistics, and computer engineering, to detect patterns and insights from vast amounts of data.

The success of ride-sharing services such as Uber hinges on data. They hire data scientists to create ML models. These models can calculate cab fares and suggest the best routes.

What happens is that the algorithms study live traffic data, driver availability, and rider demand. All these factors are simultaneously analysed, allowing the system to automatically balance prices and routes so that drivers move efficiently, and passengers get rides faster.

Now, in case you are wondering, Data Science or Data Analytics: What Should You Learn First? Check out this article.

Career Paths in Data Analytics

Doing a course in data analytics will open up several job possibilities for you. The good thing about this field is that you will not be restricted to only one role or career trajectory.

More often than not, companies do not advertise for ‘Data Analysts’. The names of the roles tend to be more specific, such as:

Junior Data Analyst

This role is typically where people begin their careers in data analysis.

Junior Analysts should have practical knowledge of SQL, Excel, and Python/R to clean data, check numbers, and prepare basic charts and reports.

In this role, much of your learning happens while you are already employed, since you are working with experienced, senior analysts and managers.

AI Data Analyst

In this role, you would analyse large datasets using Artificial Intelligence (AI), Machine Learning (ML), and natural language processing (NLP), to make informed predictions or recommendations.

Unlike the time-consuming traditional data analysis process, in this role you would be using AI tools to process large amounts of information quickly and find patterns.

AI data analyst jobs are in high demand as this is the natural progression from traditional data analyst positions.

Senior Data Analyst

While Junior Analysts may be assigned specific, small tasks, your advancement to Senior Analyst means that you will be accountable for entire projects.

If a company sees customer subscriptions steadily falling on their app, they will want to know why. In this case, a senior data analyst would study several datasets together, such as customer activity, pricing changes, support tickets, and usage patterns, to identify where users begin leaving or uninstalling.

The analyst then hands over these findings to the product or management teams so they can decide what to improve.

Senior analysts are also charged with reviewing the work of junior analysts and helping them approach problems more carefully.

Business Intelligence (BI) Analyst

Analysts in this role take raw data and turn it into actionable insights, which help to achieve strategic business goals.

What does this mean exactly?

Suppose a transportation company hires a Business Analyst to study delivery delays. The analyst examines real-time GPS data from vehicles to identify slow routes and helps the team choose faster alternative routes.

A BI Analyst would need to be familiar with tools like SQL, Tableau, Power BI, and Excel.

Analytics Manager

An Analytics Manager is usually a step above senior analysts. Instead of doing most of the analysis themselves, they lead a small team of analysts and decide what problems the team should study.

Your client may be a bank that wants to understand why many customers close their accounts. Several data analysts start studying customer data. The Analytics Manager guides their work, checks their reports, and explains the final findings to senior leaders so the bank can decide what changes to make.

An Analytics Manager usually understands tools like SQL, dashboards, and reporting systems, but their main job is leading analysts and turning their work into clear business decisions.

Chief Data Officer (CDO)

This C-suite executive position is responsible for ensuring the organisation’s data assets serve to maximise its business goals and benchmarks. Very often, this means using advanced technologies to monetise business data.

Everything from data strategy to data governance and data security comes under the purview of the Chief Data Officer.

This is a strategic role where you manage and oversee the lifecycle of data.

You would work closely with the chief marketing officer (CMO) as well as

Of course, the main question that most graduates and job changers have before doing a course is whether there’s demand for that role or not. It’s understandable since a career needs to be future-proof.

Demand For Data Analyst Job Roles

A report from the World Economic Forum shows that AI and big data are at the top of the list of fastest-growing skills. So, it’s clear that there is an urgent demand for professional Data Analysts. But, to give you a more transparent idea of the demand for this role, here’s a breakdown.

Global Demand for Data Analysts

Data analytics jobs are in high demand worldwide, particularly in the United States, where top platforms have tens of thousands of job listings.

They are followed by Canada, where there is consistent hiring in the tech industry. In Germany, there are high vacancy rates for these data roles because of the high number of AI projects.

Australian job platforms like Seek indicate a large number of openings for data analysts.

Here’s the salary range for roles within data analysis in top countries across the globe.

Country	Expected Salary Range (USD)
United States	$70,491 – $118,881
Canada	$45,900 – $68,350
Germany	$44,000 – $99,000
Australia	$43,991 – $93,265

source

Demand for Data Analysts in India

India has the biggest demand for data analysts in the entire world. Bengaluru is number one because big IT companies like Infosys and TCS, plus several of new startups, are hiring them non-stop.

Hyderabad outsources work from global firms that set up data teams there. Delhi-NCR has strong demand from corporate offices and government projects needing key data insights.

Mumbai needs a large number of data analysts for banks and finance companies that handle huge amounts of transaction data.

Let’s see the average salary of data analysts in India.

City	Average Salary
Bengaluru	₹680,000
Hyderabad	₹780,000
Delhi-NCR (Gurugram)	₹663,000
Mumbai	₹650,000

Wrapping Up

It’s clear that most organisations want to see the numbers behind a problem before they decide what to do next. This is why people who can read and explain data have become increasingly valuable.

If you are thinking about learning these skills, you could explore a Data Analytics course at Webskitters Academy. Not only will you get training from top industry professionals, but you will also get placement assistance on completion of the course.

If this sounds like something you want to pursue, take a few minutes to look through the course details and begin your enrollment process.

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Frequently Asked Questions

1. What is the salary of data analysts?

The average salary for a Data Analyst is $92989 per year in United States. The average salary for a Data Analyst is $92989 per year in United States. In India the average salary for a data analyst is ₹6,54,514 per year.

2. Is a career in data analytics relevant in 2026?

Yes. Data-related jobs remain highly relevant. The U.S. Bureau of Labor Statistics expects data scientist roles to grow about 34% between 2024 and 2034, much faster than average.

3. Why choose a career in data analytics?

Many organisations rely on data to guide decisions. Analysts collect, organise, and study information, then explain findings to leaders so businesses in fields like finance or healthcare can make informed decisions.

4. What job can I get with data analytics?

Junior Data Analyst, AI Data Analyst, Senior Data Analyst, Business Intelligence (BI) Analyst, Analytics Manager, Operations Analyst, Marketing Analyst, Systems Analyst, Healthcare Analyst, Financial Analyst, HR Analyst are some of the roles.

5. What are the top 3 skills for a data analyst?

Most analyst jobs require three core abilities: working with databases, analysing data, and communicating results clearly so decision-makers make smart business decisions based on the numbers and insights.