SQL performs better and faster than Excel no doubt, but often times the data size is so huge that SQL queries take significant amount of time to process data which can sometimes lead to diminishing results. In order to perform queries faster below are certain best practices followed in the data science industry.
Indexing
Indexing is one of the best methods to speed up retrieval and querying of your data. Index can be created for categories and subcategories of data and we can query the database basis our requirements. When a table in a database grows larger, searching for specific data can become time-consuming and resource-intensive. Indexing solves this problem by creating a separate data structure, known as an index, that organizes the data in a way that allows for faster searching and retrieval. By creating an index on one or more columns of a table, the database engine can locate the desired data more efficiently, reducing the need to scan the entire table. This results in faster query execution times and improved overall performance of the database system.
Build partition tables
Partition the data into smaller subsets, by partitioning the data set we are eventually reducing the data size , which in-turn saves the processing time as sql is reading through lesser Rows compared to your previous queries.
By partitioning a table, queries that involve filtering or searching based on partitioning criteria can be executed more efficiently. The database engine can leverage partition pruning, which involves skipping irrelevant partitions based on query predicates. This reduces the amount of data that needs to be scanned, leading to faster query execution times. Additionally, partitioning can improve data loading and maintenance operations by allowing for more targeted and granular operations on specific partitions instead of the entire table.
Stored Procedures
Stored procedures in SQL are pre-compiled and stored database objects that contain a series of SQL statements and logics. Stored procedures offer various benefits such as code reusability, maintainability, and security, and contribute to faster data retrieval. Data retrieval performance is enhanced by reducing network overhead. Instead of transmitting multiple SQL statements across the network, a single stored procedure call is made. This reduces the amount of data sent over the network and minimizes the round-trip time between the application and the database server. Consequently, the overall data retrieval process becomes more efficient. Use stored procedures to perform your routine data work. Build a standard stored procedure basis you needs, you can call your stored procedure instead of having to perform the tasks each time.
Hardware optimisation
Hardware optimisation is another method in which we can opt for a premium service to enable addition memory slots and storage which can help queries run faster. It is the expensive form of handling data since a hefty price will be charged for using enhanced memory, CPU performance and bandwidth.