How to Become a Data Analyst?

So you have decided that you want to be a data analyst and have started searching for a job for the same but due to different companies having different requirements for the same position you are not able to actually comprehend what to have as your skill-set for getting the “job” you always wanted.

I am going to list a few things I have done when I transitioned to Data Analyst that worked for me.

Steps for data analysis

1. Understanding the question (creating the question from the problem).
2. Creating the context after simplifying the ask.
3. Extracting the data points.
4. Define the analysis if it’s Descriptive, Diagnostic, Predictive, Prescriptive or more than one of them.
5. Create visualization charts

DATA ANALYSIS REQUIREMENTS

You should be able to extract the data (SQL)

There is no other option than learning SQL for extracting data unless your organisation is very generous and gives you data for analysis (Nobody does). Start small while learning. Start with aggregates, group by, temporary tables and then move to window functions.

Official Postgres is the best site to learn

You should be able to code (fast)

Since data analysis is a task where speed and precision are integral that’s why we should be able to create scripts quickly for cleaning or fast analysis or even for creating charts.

Python or R are prefered languages because they have statistical packages and have numerous libraries for visualisation, cleaning and advanced ML algorithms.

For getting started I have written this article which explains the steps

Basics to know before even you start exploratory data analysis (EDA)

comment if you want if I should create an article for most used libraries in Python

You should be able to create charts (Right)

Please see the article for this which explains all the moving parts and gives a great picture to understand the basics of visualisation :

The Only Guide You’ll Ever Need for the Data Visualisation

You should have knowledge of statistics (Basics)

Please see the article for this explaining best practices for using statistics and different tests while analysing the data.

Understanding tests in statistics, everyone should know this

You should be able to recommend and tell a story (simple)

Please see this case study for the same which takes a problem and gives step by step analysis for recommendation and finding the problem:

Product Affinity and Basket analysis for an e-commerce website

Please always remember to take two steps back for understanding the whole picture again and again so that your direction for analysis remains constant and you are not lost .

Thanks!