In daily operations, Excel often becomes the repository for our data. But as effective as Excel is, it doesn’t quite match the ease of data analysis in SQL and databases, particularly when dealing with larger data volumes. In this article, we’ll illustrate how to create tables graphically based on Excel data using SQLynx, a simple and efficient process.
Here are the detailed steps:
1. Prepare Your Excel Data
Before starting, ensure your Excel file, containing all the data to import, is ready. Let’s assume your file is named sqlynx_hotel.xlsx and your worksheet is titled hotel_order.
2. Import Your Excel Data
Open the SQLynx product platform and follow these steps:
a. Log into SQLynx
Sign in to your SQLynx account and select your preferred database.
b. Import the Excel File
On the SQLynx main interface, right-click table under your MySQL database dropdown list, find Create table by import or similar options, and select Import from Excel files.
- Click on the
Create table by importbutton. - Select your Excel file
sqlynx_hotel.xlsx. - Confirm the column mapping, ensuring a one-to-one correspondence between Excel columns and database table columns. The default type is
varchar(255), but you can alter the data type and the name based on your requirements. For columns not needing import, simply leave the target name blank. - Preview the data in the table to be generated. Currently, the default is not to exceed 50 rows.
- Generate the ultimate table
sqlynx_hotel.
3. Verify the Data
After importing data, execute a query to confirm whether the data has indeed been correctly imported:
1 | select * from sqlynx_hotel |
4. Use and Manage the Table
Now, your data is successfully imported into a new table in your MySQL database. Use SQLynx to execute SQL queries for managing and analyzing your data.
5. Conclusion
Creating tables from Excel files using SQLynx is an intuitive and efficient process. SQLynx’s easy-to-use import tool makes database management and data analysis a breeze. Share the capabilities of SQLynx with your friends or colleagues today, and let’s make data analysis an exciting part of our daily work!