Even before the big data revolution, ‘data analytics’ as a form existed across businesses. From calculations of profit and loss from hundreds of thousands of transactions to productivity measurements in large factories, data analysts have always studied data, gleaned insights and informed business decisions. In the digital age, data analytics jobs have become not only more common but also more complex. So, we find that young professionals are often confused by the various myths and misconceptions floating around.

Myth busting: Clearing Misconceptions Around Data Analytics Jobs

In this blog post, we’ll clear up common myths clouding your pursuit of a data analytics career. Whether you’re worried about qualification, skill sets, experience or salaries, we have you covered.

Data Analytics Jobs Myth #1: Data Analysts are Just Excel Wizards

This is the most commonly heard description of data analysts. People believe that if you know Excel, you can be a data analyst. While we all agree that Excel is an important part of a data analyst’s toolkit, it’s hardly the only one. More importantly, it’s definitely not the only skill. The fundamental role of a data analyst is to analyse data and glean insights which can be used to make business decisions. Take this job description from Amazon. It says that the key responsibility for the role is to “provide seller data and insights for better impact decisions and driving new/existing marketing initiatives”. For this, the job expects the candidate to know SQL, statistical analysis tools like R and techniques like regression, cluster analysis etc. in addition to Excel. Data analysts typically also have skills in Python, database management, PowerBI, visual basic and more.

Myth #2: Data Analysts Only Make Reports

To say data analysts only make reports is like saying a driver only presses the accelerator. A data analyst finds answers for business problems through data. Why is this marketing campaign expensive? Why are checkouts on the website failing? Why is production capacity reducing? Which group of customers contribute to top billing? An analyst collects, processes, analyses existing data using their in-depth understanding of the industry/business, to find answers to such questions and presents them in the form of reports. Building dashboard, presentation and clear communication is crucial to being a successful analyst, but the role itself is much beyond that.

Myth #3: Data Analysts are Nerds; They don’t need Communication Skills

This is patently false. An analyst is expected to convince business stakeholders to make decisions based on data. In addition to knowing the business like the back of their hand, they also need to engage meaningfully with sales, marketing, operations, finance, manufacturing and various other teams, including the C-suite. Without strong communication, negotiation and persuasion skills, they can’t do their job effectively. 

Myth #4: Data Analysts don’t Need to Understand the Business

People often assume that data is enough, and all they need is to understand the data. But this is far from the truth. All data exists within the context in which it’s collected, processed and used. To make sense of the data, an analyst needs to understand the business. For instance, if you’re a marketing data analyst, you need to know digital marketing concepts like clickthrough rates, conversions, drop-off, customer journey, etc. If you are a financial analyst, you need to understand revenue, cost of goods sold, sales, cash flow, EBITDA, etc. Not only do you have to understand these concepts, but you also have to know how they work within the business you are performing analytics for.

Myth #5: Only Mathematics Graduates can get Data Analytics Jobs

As a data analyst’s role typically involves numbers, people tend to assume this. It’s wrong. Most data analyst jobs today expect a bachelor’s degree in any related field. This is typically computer science, mathematics, statistics, economics or even computer science. You need quantitative skills, not specifically mathematical skills, to become a data analyst.

Myth #6: Data Analysts don’t need Coding Skills

While data analyst jobs don’t specifically ask for programming skills, it’s always a plus. In the least, data analysts are expected to be proficient in writing SQL queries to perform ETL (extract, transform, load) functions. But it would certainly be an advantage to know to use a programming language like Python or R. If you’re a programmer aspiring to make a career transition to data analytics jobs, your coding skills can set you apart.

Myth #7: Data Analysts are not paid Top Salaries

The average salary of a data analyst in India, as declared by the LinkedIn community, is about Rs. 420,000 per annum. In-house data analysts in industries like banks and financial institutions are paid much higher. For instance, the average data analyst salary in Citibank is Rs. 10,30,000, finds the LinkedIn survey. With experience, the average salary grows too. A senior data analyst earns an average of Rs. 725,000 per annum. Analytics managers earn about Rs. 17,00,000 per annum, senior managers Rs. 24,00,000 per annum, and director of analytics over Rs. 45,00,000.

In the flux of artificial intelligence and machine learning, good old data analytics might feel left behind. But, there is a huge gap between myths vs reality. For most businesses today, there is nothing to match the role of a competent data analyst in helping them make the right decisions at the right place at the right time. With thousands of data analyst jobs open right now, the market is poised to grow. If you’re looking to start a career in data analytics, consider Springboard’s mentor-led, project-driven online learning program. In addition to the up-to-date, industry-ready curriculum, you will also get 1:1 mentorship from leading professionals, and personal coaching for a seamless career transition.