Introduction to SQL for data science

Structured Query Language is a fundamental tool for any data scientist. It allows you to efficiently retrieve, manipulate and analyze structured data stored in relational databases. SQL provides capabilities to extract insights. In this article we will cover the basics of SQL and essential queries for data science. Why SQL for data Science Data Retrieval - SQL enables efficient extraction of data from databases. Data manipulation - SQL enables us to filter, aggregate and transform data before analysis. Performance - SQL is optimized for handling large datasets. Integration - SQL works seamlessly with python, R and BI tools. Basic SQL Queries SELECT statement The select statement is used to retrieve data from a database. Example returns for us the first and the second name from the customer table. WHERE clause used to filter data from a table. EXAMPLE only counts for us the customers who are from Kisumu HAVING clause used to filter aggregated data. EXAMPLE counts the total orders for only the customers who had more than one order ORDER BY Used to sort data in a specified order. that is ASCENDING or DESCENDING N/B - The default SQL order is Ascending Example lists for us the price from the lowest to the highest. SUMMARY in summary SQL is a crucial tool for data scientists. enabling efficient data retrieval, manipulation and analysis from a relational database. in this article we have covered key SQL concepts including basic queries as SELECT, WHERE, HAVING, ORDERBY for retrieving, filtering and sorting data.

Apr 16, 2025 - 11:04

Structured Query Language is a fundamental tool for any data scientist. It allows you to efficiently retrieve, manipulate and analyze structured data stored in relational databases. SQL provides capabilities to extract insights.
In this article we will cover the basics of SQL and essential queries for data science.

Why SQL for data Science

Data Retrieval - SQL enables efficient extraction of data from databases.
Data manipulation - SQL enables us to filter, aggregate and transform data before analysis.
Performance - SQL is optimized for handling large datasets.
Integration - SQL works seamlessly with python, R and BI tools.

Basic SQL Queries

SELECT statement
The select statement is used to retrieve data from a database.
Example

returns for us the first and the second name from the customer table.

WHERE clause
used to filter data from a table.
EXAMPLE

only counts for us the customers who are from Kisumu

HAVING clause
used to filter aggregated data.
EXAMPLE

counts the total orders for only the customers who had more than one order

ORDER BY
Used to sort data in a specified order.
that is ASCENDING or DESCENDING
N/B - The default SQL order is Ascending
Example

lists for us the price from the lowest to the highest.

SUMMARY
in summary SQL is a crucial tool for data scientists. enabling efficient data retrieval, manipulation and analysis from a relational database.
in this article we have covered key SQL concepts including basic queries as SELECT, WHERE, HAVING, ORDERBY for retrieving, filtering and sorting data.