Average pay of a data analyst is way more than I.T. standard. How to be a data analyst? – TheDataMonk

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Average pay of a data analyst is way more than I.T. standard. How to be a data analyst?

Data analytic is a process of examining and extracting meaning from raw data [ historical or new] using specialized computer systems. It is used by various organizations and companies to make better decisions and also verify and disapprove existing theories or models. The most important skills in data analytic are not technical skills, it’s the thinking skills. Being able to separate good data from bad data and knowing where exactly can add value. Now let’s talk about the skills required to become a data analyst.

  • Programming skills
  • Statistical skills and mathematics
  • Machine learning skills
  • Data wrangling skills
  • Communication and Data visualization skills
  • Data institution

These are the required skills to become a data analyst. Any person can learn these skills as it is very easy. You just need to have some basic knowledge about programming and some basic mathematics and statistics. The programming languages you need to learn to become a data analyst are R and python(at max). These languages are very important. It is very important for professional to be able to think like a data analyst. The ability to find out raw data and convert it to another format that allows for a more convenient consumption of the data. Data analysts work mostly in industries like Healthcare, travel, gaming and energy management. The need of data analysts are growing and there are not many data analysts in the world. The package for a data analyst is handsome and there are many jobs up for grabs. Thedatamonk.com is a website which provides the right platform to get going in the field of data analysis. It has published many books which can be bought from amazon that provides you the perfect guidance to establish yourself in the modern world.

 

The path followed by most of the data analyst is more or less the same:-

  1. Start with any Query Language (SQL preferred). Try to get the basics clear on the very first go. Keep updating your knowledge
  2. Try to clear your statistical concepts. A data scientist is of no use until and unless he/she knows the stats behind the number
  3. Solve case studies – Be it pharmaceutical, web analytic, telecom, airlines, retail, etc. Just try to understand the way how people approach a problem

 

To help you in this preparation, we have – 100 Questions to solve data science interview
Check it out! You can also leave your review and comments on the amazon site after purchasing the book!

 


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