1.1. Why Learn Data Analysis?

In today’s world, it is nearly impossible to go through the day without hearing about data. During the news, you may hear about how many visitors went to a local state park. During the work day, you may hear about how much revenue was made that day. While sitting at home, you may crack open your planner and start your monthly budget, updating personal spreadsheets as you go. This world and your life comes with so much data.

Data Analysis is a field in tech that focuses on finding data, digging through it, and reporting on the key takeaways. In the case of your monthly budget, finding data might include locating the monthly statements from your bank and other financial institutions. Digging through the data encompasses the part of the process where you start looking through transactions for your regularly occurring monthly expenses. Reporting that data is when you create graphs going over debt plans. On a larger scale, this process and the people who perform it are some of key members of an organization. Businesses today rely on data analysts to find the information needed to make decisions and chart paths forward.

Data Analysts use a wide variety of tools to accomplish these tasks. They code, use reporting software such as Tableau, and create databases. While this book focuses on how to use these tools as a data analyst, each tool is a valuable skill on its own. The tools used in this book include Python, various Python tools specifically geared towards data analysis, Azure Data Studio, and Tableau. Before reading further, you should bookmark this list of all the necessary software and tools for the class.

As you get to know these tools better, you will begin to see that while one tool can do many things, each tool is created to excel at one thing. In the case of learning data analysis, we first teach you how to code in Python so you can effectively use Python and its packages. As a data analyst, you may find yourself having to perform complex calculations and parse through large datasets, which is something Python is very good at. Azure Data Studio allows you to connect to SQL databases and write SQL queries, which is another key part of a data analyst’s work. Tableau can perform some calculations, as you will see, but it is best at creating beautiful visualizations. When you are working as a data analyst, visualizations are integral to creating an effective report of your work.