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Brijesh Kohli
The data analytics job scenario has high potential. Opportunities encompass numerous industries and the nature of the jobs today often allows flexibility of remote work and self-employment. The demand is quite high; however, experts who can perform this job are limited. So, a data analytics career has certainly become one of the most sought-after options in the contemporary job market.
Data is now a crucial metric that defines an organisation’s performance. It can help weigh investment decisions, target customers, assess risks and decide on capital allocations. This market has grown by leaps and bounds and data analysts command huge salaries and excellent perks — even at the entry-level.
Role of a data analyst
Data analysts probe Alps of data to spot trends, make forecasts, and dig out information to help their employers make better-informed business decisions. Data analysts dominate the job market — from private equity firms, marketing, retail, healthcare industry, insurance companies, credit bureaus and technology firms.
Students must master certain skills to be able to make a mark in the data analytics market.
Must-have skills
Some are elaborated here for a better understanding of the courses available in the market today:
1. SQL
SQL is database coding language that extracts, organises and manages large datasets stored in relational databases. Expertise in SQL can help you add, delete, update and extract information from any database. Without having proper understanding of SQL, you cannot perform any substantial analysis. This skill is in demand as it helps employers carry out analytical functions and transform data structures.
As a data analyst specialist, it is important for you to have knowledge on how to create joins, retrieve data, develop stored procedures and create aggregations so that you can analyse data and provide meaningful business insights to clients.
2. Microsoft Excel
Microsoft Excel offers an easy way to store data, apart from providing quick analytics. For instance, you may use ‘Pivot Tables’ to summarise, reorganise, group, count and sort — or calculate — the average of your data or you may also use Visual Basic for Application (VBA) to create macros that facilitate speedy data analysis in an Excel.
As a result, many organisations prefer storing and analysing data in Excel. Employers prefer analysts with advanced Excel knowledge because it helps manipulate and visualise data to draw profitable insights from it.
3. Mathematical skills
You may have to use a probability distribution to analyse and visualise data to discover meaningful insights or the concept of dimensionality reduction to process a dataset with far too many variables. Data analysts need to quantify and process loads of data. So, they should possess strong mathematical skills. Expertise in advanced mathematics can also help understand numbers and how to operate and combine them to support the analysis. This makes mathematics the most in-demand skill when employers hire a data analyst.
4. Statistical programming language
A data analyst uses R specifically for statistical data analysis and Python for a more general approach to analyse data. Statistical programming languages, like Python and R can help you perform analysis in a manner no spreadsheet can. The ability to write codes in these languages ensures you can analyse and visualise large data sets more efficiently. Mastery over even one language is sufficient to excel at your workplace. These statistical programming languages can help you accomplish your day-to-day duties. Both languages are open source, so learning any of them can increase your employability and land you a job fast.
5. Machine learning
Organisations that use highly specialised machines to carry out data analysis want to hire professionals who understand how machine learning works. Proficiency in machine learning ensures that a data analyst can use machine learning to automatically create analytical models. It primarily focuses on building algorithms specifically designed to find trends and patterns in a data set. Over time, the algorithm improves the accuracy of finding patterns.
Machine learning is a branch of Artificial Intelligence (AI) that is important in data analytics. Since AI is the upcoming and in-demand certification, data analysts with machine learning skills are incredibly valuable and are often preferred over candidates who do not understand the subject.
6. Data visualisation
Data visualisation is the ability to communicate and present your insights and findings via graphs, charts or other illustrations. With data visualisation, you can provide simplified business solutions that maximise understanding and cognition. It is an essential skill as it facilitates information in a manner that is easily understandable by someone with no training in data analysis. Using this skill, you can help organisational leaders understand complex ideas and identify patterns.
Also, the ability to use the right chart to answer a common business question can make you a desirable candidate for a data analyst’s role.
These certifications help you land one of the jobs mentioned below in any company and can fetch you anywhere between Rs 50,000 and Rs 1 lakh, depending upon your skills, knowledge, experience and the company you are working in.
Data analytics is a very fast growing field with compelling opportunities for professionals across a wide range of industries. In the current day scenario, there is a spiralling demand for skilled big data professionals and there can be no better time to enter the big data job. At present, the demand for skilled data analysts largely exceeds supply. In a 2018 report, the World Economic Forum (WEF) predicted that 85% of the companies would be using big data analytics by 2022. Considering trends; it is surely going to be in demand for some time now.
The writer is Director, Xebia Academy
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