Comma separated values (CSV) files are frequently used in data science and machine learning, and MS Excel can be helpful for simple data editing for this format. However, Excel is not enough for executing more complex SQL queries on CSV files. You will need the help of a reliable SQL server. Therefore, it is often practical to import data and files from Excel or CSV into SQL databases to save time and effort—a method that continues to grow in popularity for the reasons listed below.
SQL is faster, especially when compared to Excel. It takes only a few seconds or minutes to accomplish tasks, and the other could take as much as an hour or more to do so. Although Excel can technically deal with a million rows, it may find it challenging to navigate pivot tables, functions, and multiple tabs.
Separate analysis from data
When you use SQL, data is stored separately from the analysis. So, instead of emailing a large Excel file, you can deliver smaller plain text files with instructions for analysis. Converting Excel files and CSV to SQL allows teams to access the same data and run analysis on their own without managing file versions. It helps reduce the chances of corrupting data while allowing users to rerun it on other data.
There are web-based SQL database management tools.
There is no doubt about the convenience that Microsoft SQL Server brings to database management. It is a unified data platform, after all! However, you can now choose a web-based SQL server data tool to access your files from any device. It is a more versatile alternative to SSMS as it allows you to perform more actions beyond importing Excel or CSV to SQL.
The web-based platform has a visual SQL query builder and a point-and-click, intuitive interface that lets you make and manage queries quickly and efficiently. Use it to create an SQL server database, parameterized reports, D3-based charts, and online dashboards and schedule SQL reports and jobs with just a few clicks.
Using this platform, you can import CSV data into a database table and upload the CSV file straight into them. It will automatically map table columns, and you can schedule import jobs to run automatically at regular intervals.