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Skills That Will Determine Your Capabilities as Data Analyst

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With the increasing number of IoT devices, the IT industry is looking for individuals with high-skill in handling data. India is second to the USAin terms of demand for skilled data analysts in various industrial sectors, says a research study. The study also predicts that more than 50 percent of the IT experts will have to upskill their data handling or data analyzing capabilities to retain their jobs as many of their old skills are becoming obsolete.

From data interpretation and handling to advanced programming with python or any other language, the need for skilled data analysts is increasing day-by-day. If pursuing a career in IT or any other data dominated field, taking python training in Delhi or any other cities in India can prove handy.


Other than good knowledge of programming, a good data analyst must also have crucial skills that include; good math, data mining, statistical and business intelligence. In this article, we will give youan idea of the skills that will likely get you hired before your peers.

Essential Skills of a Data Analyst

  1. Programming Skills

Good knowledge of coding is one of the most importantskills in the arsenal of a data analyst. A data analyst needs coding to conduct various statistical and numerical analysis of the massive data sets in the enterprise. The analyst must be proficient in one of the many programming, scripting and statistical languages utilized to manipulate data. Hence, once you have the fundamentals of coding on your fingertips, it becomes comparatively easy to adapt with different frameworks and syntax of various languages.

  1. Quantitative and Analytical Skills

Good knowledge of programming can help you do what is required as a data analyst. However, the big question is what you are supposed to do?Good quantitative skills help analysts in solving this problem. For becoming a good data analyst, you should know calculus, matrix and linear algebra, probability and statistics. Along withquantitative skills,analytical skills are also crucial to become a good analyst. The ability to collect, view and analyze information from data and use it for the benefit of the enterprise is necessary.

  1. Knowledge of Technologies

With good programming skills, knowledge of multiple technologies help you in growing as a data analyst. The wide range of technologies present in the market is not limited to programming alone. It spans over various platforms, hardware, tools and software. For instance, SQL and Excel are some basic tools and at an enterprise level SAS, MATLAB and SPSS are important to learn. The actual technologies that come into play while programming depends upon the working environment around you. It can also depend on the requirements of the project or the enterprise.

  1. Data Interpretation and Attention to Detail

The skills to interpret data is one that combines both your creativity and technical knowledge. It requires high precision of both mathematical skills and knowledge of data science. In most companies, employees rely on preconfigured dashboards and reports for delivering insights. This does not provide a holistic approach towards tackling the organizational data procurement and analyzation. The problem is also compoundedwiththe fragmentation of data systems creating problems in detailed analyses. It does not allow spotting of redundant information which is critical for results. Moreover, as many minute details are missed due to various silos in the organizations, it results in wastage of money and time.

  1. Communication Skills

Providing descriptive and accurate information to the decision makers in the enterprise is a vital role of data analysts. They must be able to understand the requirements of end-users and provide insights to executives based on that information. Therefore, analysts should possess good communication skills to ensure that they can explain the

communication skills

leaders, clients, employees and IT specialists on how to align the data-based insights to business objectives. The ability to communicate transparently helps in keeping everyone aware of the constraints and influences of the analyses they provide.

  1. Understanding of Business Outcomes

Even extremely efficient data analysis and insights are useless if they cannot be aligned to business settings. Therefore, analysts must have a strongunderstanding of the business domain they work in; it helps in identifying opportunities and threats based on their expertise. The expertise in business domain enables the analysts to communicate efficiently with stakeholders and executives.

The field of data analytics is growing rapidly,and so is the number of jobs. The field provides freshers great opportunities for a successful career. If you also wish to make use of these opportunities, begin by taking python training classes in Delhi or Noida. The training will help you get the basic idea of the industrial requirements for becoming a data analyst.

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