How Can You Become a Successful Data Analyst?

Data Science and Data Analyst are getting huge demand in multinational companies. According to Harvard Business Review, it is one of the sexiest jobs of the 21st century. The job of data analyst has job security, healthy salaries and benefits, due to which it is top of the food chain. To become a successful data analyst, you can take a

Work Of Data Analyst

A data analyst will collect, process, and perform some statistical analysis of the collected data. They are also responsible for making data useful in one way or another way. Data analysts will help other people make the right decisions and prioritize the raw data collected to make work easier. They will use specific formulas and apply the right algorithms to collect data.

Data Analyst is a great job for people who are passionate about numbers and algebraic functions and enjoy sharing work with others.

 

Requirements For Data Analyst

  • You should know Microsoft Excel to make structured data forms. It will help you to manage massive data easily and conveniently.
  • You should get SQL skills.
  • You need basic web development skills.
  • It would help if you found patterns in large data sets.
  • Data mapping is an essential skill for a data analyst.
  • You require the ability to analyze processed data.

 

Skills For Becoming a Successful Data Analyst

Python and R are the two most popular programming languages for data analysts to become professionals.

  • Python

Python is one of the simplest programming languages and is an ideal platform for beginners to start programming. You will find several libraries for data analysts like matplotlib, scipy, pandas, seaborn, anaconda, ipython, and ipython notebook.

  • R Programming

R programming usually supports statistical computing and graphics. R focuses on getting a good grasp of the language and your work. There is a bridge between R and SQL which we call Dplyr. It will help translate the codes in SQL languages and work together with both types of data. 

  • Statistics

There is no use in programming if your data is not interpreted correctly. Some statistical skills like mean, median, mode, forming data sets, standard deviation and other variables, histograms and many more are important for statistical development.

  • Mathematics

Mathematics is important for becoming a data analyst. It requires knowledge of matrices and linear algebra, relational algebra, CAP theorem, framing data and series. You can also learn it from 

  • Machine Learning

Machine learning combines multivariable calculus and linear algebra with statistics. It is one of the most powerful tools for data analysts. You can upgrade your skills instead of investing time in learning algorithms.

  • Data Wrangling

Data Wrangling is a process where all the collected data is gathered to form a single, cohesive whole. A data analyst will transform raw data into properly structured and logical sets. Now, these data can be used for further processing. You may require to know about both SQL and NoSQL databases.

Conclusion

A data analyst can work in multiple roles in different multinational companies like data analyst, data engineer, operation analyst, marketing analyst and many more. There is an average salary of USD 61,881, and in India, it is around 439,260 rupees per year. A data analyst will analyze the market research and work according to the requirement.

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