Skills That Will Determine Your Capabilities as Data Analyst

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The number of IoT devices is increasing, and the IT industry is looking for increasing numbers of highly skilled data handlers. India is now second only to the USA in terms of demand for highly skilled data analysts, says a recent research study. The same study also predicts that over 50 percent of current IT experts need to upskill their data handling and analyzing skills in order to retain their jobs

The demand for skilled data analysts is increasing by the day. Specialists in data interpretation and advanced programming with Python are particularly sought after. If you are planning a career in IT or any other data field, python training would be a good start.

In addition to programming, a good data analyst must have skills in math, data mining and statistical and business intelligence. In this article, we will walk you through the skills which will make you stand out from your peers.

 Data Analyst: The Essential Skills


An excellent knowledge of coding is vital. A data analyst uses advanced coding to conduct various statistical and numerical analysis of massive data sets. The data analyst should be highly skilled in at least one of the programming, scripting and statistical languages utilized to manipulate data.

 Good Quantitative and Analytical Skills

Whilst an understanding of programming can help you do the job of a data analyst, the harder question is what you are supposed to do with this understanding in your daily job? Having good quantitative skills enables the analyst to figure this out. They should understand probability, statistics and calculus, matrix and linear algebra.  Advanced analytical skills are also vital. Analysts require the ability to view and analyze information from the data they collect and use it to benefit the company

 Understanding Technology

An understanding of multiple technologies will enable you to grow as a data analyst. This understanding is not limited to programming alone and includes various platforms, hardware, tools, and software. Analysts should have a firm knowledge of basic tools such as SQL and Excel as well as more advanced ones like SAS, MATLAB and SPSS.  However, it is important to remember that the skills required will depend on the company, project and working environment.

Interpretation and Attention to Small Details

Data interpretation requires both creativity and technical knowledge. You need a combination of good mathematical skills and knowledge of data science. Nowadays, in most companies, employees rely on preconfigured dashboards and reports for delivering insights. However, this is not a holistic approach in tackling the organizational data procurement and analyzation and creates challenges. Fragmented data systems increase the problems in undertaking detailed analyses. They make it difficult to spot redundant information which can be crucial for results resulting in wastage of money and time. Data analysts will need to have the ability to overcome these problems


Having the ability to accurately describe complex information in layman’s terms to the decision-makers is an important role of data analysts. They should be able to understand the requirements of end-users and convey this back to the executives. Analysts require excellent communication skills to enable them to explain issues to managers, clients, employees and IT specialists.

Understanding Business

Even the best data analyst will struggle if they cannot be aligned with day-to-day business settings. Therefore, a strong understanding of the business domain in which they work is essential. It will enable them to identify relevant opportunities and threats based on their expertise. They can then communicate these efficiently back to stakeholders and executives.

The field of data analytics is growing and so are the number of jobs. The industry provides freshers with great career opportunities. To fully make use of these opportunities, we would suggest you begin by taking python training classes. This training will enable you to gain an idea of the industrial requirements needed to become a data analyst.