Excel and SQL are great steps to Tableau

Excel spreadsheets may not be enough for every data enthusiast. It’s true, but it’s sad. Two common limitations are what drive data pros to other software.
You’ve reached the limits in a spreadsheet. Maybe you’ve reached the limit of a spreadsheet’s row or cell count. You may not want to analyze a whole bucket of data. You want to analyze a data stream. It is time to look for a new tool.
Second, you are tired of looking at the same old data buckets and want to explore. SQL (or any other relational database language) can be your next solution. It’s not enough. It’s not enough to be a master at data collection and warehouse management.
Once you reach that point, you can upgrade to a better tool such as Tableau or Power BI (more on Power BI later).
Learn how to become a security expert with SPOTO’s Cybersecurity Training
Tableau combines data access and analysis in one platform. Anyone who has worked with spreadsheets for a while will find it refreshing and confusing to enter Tableau for the first-time. You got there, and Excel and SQL are great stepping stones for Tableau.
Excel is the gateway drug
Let’s do this. Excel is amazing. Excel is awesome, but it won’t be perfect forever. Excel is like your first car. Excel is the best tool for data exploration when you first start digging into it. It’s also the most popular choice in the business world. Excel is easy to use, and even non-technical businesspeople can learn to work with data exported from other programs.
Excel is a powerful tool that can be used to create complex data. However, if you use it enough, Excel will eventually surpass the limitations of the basic platform. Excel excels well at static data. Yes. Yes. However, it is possible to create pivot tables using dynamic data sources. Yes. Excel can be used to build a model and then refresh the data. It’s functional, but not ideal. Once Excel’s limitations are revealed, you will want to expand your Excel knowledge and use more powerful modeling tools, better visualization, or simply grab more data. SQL is the most popular choice.
Learning SQL is the next logical step
There is a point at which you don’t want to be served with the data. You want to search for it. This is where SQL learning comes in.
This is also where Excel and you might need to part ways. You might decide to take a step back. Instead of importing data into Excel, you can use SQL to directly interact with the source database(s). Performance is no longer an issue since you are working directly with a production relational data base. It’s a huge step once you reach that point — and it’s an improvement on Excel.
Excel is easy to break. Technically, an Excel worksheet can contain 1,048,576 rows or 16,384 columns. You can achieve even 10% of the maximum, but it is possible to be successful. Depending on the machine you have, you might see “Microsoft Has Stopped Working.” on a good day. Excel will crash more often. (No, Microsoft. I don’t want you to report the problem.
Once you have learned SQL, it is probably time to upgrade your data analysis software. You can also learn Python and use pandas to manipulate large.csv files. You can also use Tableau to make it easier.
Excel and SQL are crucial skills for data analysts. These are great tools to learn about data visualization, analysis, and even warehouse management. Excel is not the best tool for data analysts.
Upgrade to Tableau
You’ll want to move to Tableau if you get tired of Excel and SQL.
Many of the concepts you have learned in Excel and SQL can be easily translated to Tableau. Excel professionals will be familiar with Tableau workbooks and worksheets. You can also use SQL queries in Tableau for data retrieval from databases. Tableau can be used in a small desktop version or scale up to large enterprises.