Should Developers Change The Already Intact Toolset Of SQL?
In the last few years, every business has aptly understood the requirement as well as the benefits of working with SQL. Starting from gathering the data to analyzing it, processing it, and putting it to work, SQL allows you to efficiently use data to reach a goal.
Programs like these allow you to streamline not only your work but also avoid several common mistakes in the process.
These processes require a lot of log inspection, type checking, and as well as documentation. Without the right tools, there can be a lot of issues with the same. Along with making the whole process a lot more time-consuming, this will also mean inaccurate results.
That said, there have been a lot of tools that help avoid such issues. These tools cover everything, starting from accumulating the data into the database to analyzing and transforming your data.
However, with the workflow and style changing every year, some minor updates have to be made to each. This blog further aims to compare SQL changes made to the data collection tools in the last year.
Changes in Data Collection Tools of SQL
There is no use of SQL if you cannot put your data in the database. However, you can easily transform messy data inputs into a SQL database with the tools mentioned below.
- Numidian Convert:
Converting your gathered data into a streamlined database can be quite a strenuous job. While some files are easy to transfer, others like CSV and JSON files can be a tad bit harder. However, with the Numidian Convert tool, you can easily get the data in your database from these types of files.
All you have to do here is include the file, device the transformation changes you want and click on ‘Create Table’ and ‘Insert’ statements. Apart from the two file formats mentioned here, it also supports Postgres SQLite and MySQL.
- Panoply:
Every coder faces the problem of gathering all the data in one place when the sources vary drastically. However, Panoply offers an easy way out of this.
This cloud data warehouse consists of several native data pipelines like MongoDB, MySQL, Google Analytics, Stripe, Salesforce, and much other such integration. Built on an AWS infrastructure, Panoply is a lot easier to manage and scale when compared to its alternatives.
These are the two most intriguing changes in the data collection process of SQL.
