This content originally appeared on DEV Community and was authored by codeifys
Who is a Data Analyst?
Nowadays, companies receive a tremendous amount of information every day that can be used to optimize their strategies. To get insights from the massive data collected, they need a highly qualified professional: the Data Analyst.
The task of a Data Analyst is to process the varied data concerning the customers, the products, or the performances of the company, to release indicators useful for the decision-makers. Thus, the information provided by the data analyst enables companies to define the products to be offered to customers according to their needs, the marketing strategy to adopt, or the improvements to be made to the production process.
Data Analyst Qualifications
How to becoming a data analyst requires both academic qualifications and skills. Let us see these categories in detail below.
Academic Qualifications
It is recommended that graduate from a data analysis program and have a high GPA, it would be easy for you to land an entry-level data analysis job. Even if you don’t have a specialization in data analysis, but a degree in mathematics, statistics, or economics from a well-reputed University, can easily land a data analysis entry-level job.
I’m going to consolidate my conversation with him into 8 steps.- Programming Language (Python/R) - Python and R are the most widely used programming language. A grasp of one of these languages will help you understand how to clean, manipulate and analyze data. Some tips:
- Play around and pick a language you’re interested in, learn it thoroughly. There are tons of online courses or free youtube videos from which you can learn. An example of a comprehensive course - Business Analytics using R.
- Get your hands dirty. Check out Kaggle. They have tons of datasets and codes from other people who’ve analyzed the data. Pick a dataset you enjoy, analyze and make some observations. Lastly, check out what other people have done with the same dataset.
- SQL - to extract data. Be thorough with CRUD. Practice a few questions on Hackerrank (or similar websites!)
- Excel - I’m sure excel is familiar to most people. Take some time out and figure out what you do not know and try to learn them. Practice the basic functionalities required to build reports.
- Visualization Tools - After you’ve analyzed the data, you need to visualize it. There are lots of tools. Play around, pick one tool, and learn it. My suggestion is Tableau.
- Statistics - A basic understanding of statistics is extremely important. Make sure you know the following concepts:
- Descriptive Method and Inferential Method
- Mean, Variance, Standard deviation
- Measures of Central tendency (Mean, Median, Mode)
- Percentiles of Data distribution (First Quartile, Second Quartile, Third Quartile)
- Dispersion of data, Bell curve
- Hypothesis Testing
- Chi-Square Test
- Soft Skills - Communication skills are crucial to explaining your findings. Creative thinking is required to find details that other people might miss or ignore. No machine can replace the way you think, interpret and communicate. It is unique for each person!
- Models/Algorithms - After a good grasp of the above steps, move onto learning some basic models and algorithms that interest you.
- Business - Now, you have to decide what to analyze! You now have the skills and there are tons of industries where data analytics are required considering the amount of data generated every second. Figure out what you like, build your niche!
You can check out Originally Published: Data analyst roadmap
Happy Reading
This content originally appeared on DEV Community and was authored by codeifys
codeifys | Sciencx (2021-08-10T10:25:47+00:00) Data Analyst Complete Roadmap. Retrieved from https://www.scien.cx/2021/08/10/data-analyst-complete-roadmap/
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