Transform Your Insights: Learn Data Analysis in Just 4 Simple Steps

 

First Step

SQL is fundamentally important for your data analysis career. Most enterprises use some kind of database, and the analyst’s job is to extract the knowledge from the database. SQL is the only tool that delivers you the relevant information, and SQL has the shortest path to learn. It only takes 1–4 weeks to master the SQL code.

Second step

The data analyst’s main role is to find a clear path for business growth. For example, you are seeking consumer behavior or reasons for product popularity.

1. You are concerned about product success or failure.
2. Business wants to know about recent marketing advantages.
3. How supply chains are impacted by certain events.
4. How many people are interested, and how many converted into customers?

There are many questions that are asked by the business. Your main job is to follow these questions, so you should learn why these questions are raised by the business managers and what are the key points to investigate.

Third step

The Python programming language is mostly used in data analysis. It has rich libraries that help you extract the relevant information. Learning Python requires 3–5 months; if you learn it, you have the most powerful tool in your hand.

Fourth step

SQL, business requirements, and Python are enough to make you a data analyst. Only the data visualization remains to be learned. Data visualization requires learning the most popular charts and platforms that visualize your summaries and results. Your storytelling abilities bring you more beauty in your work. In addition, you don’t need to be a graphic designer. Just present the facts with accurate metrics.

In summary, SQL, business requirements, Python, and data visualization are the essential components for data analysis. The SQL requires the shortest path, and Python takes a longer period. If you are interested in becoming a data analyst, you need to learn all four tools. When you are comfortable with four tools, you can add more tools to create more value for your work. Thanks for reading.