✳️Select * from “Where” ??!!!!!⁉️🌐 🤔Or how to really make your database to answer the “Where” question
I love Geography, Spatial Data analysis, systems, and programming.
Knowing how to answer complex questions with data, especially with spatial data.
Using relational databases with SQL language and spatial makes the best of breed for me.
In this post, I will explain what SQL spatial is and what it can do for you.
First, some basics about SQL and spatial:
A relational database is a structured collection of data for storage, retrieval, and management.
SQL, or Structured Query Language, is the tool used to interact with relational databases efficiently.
Spatial SQL extends these capabilities to geographic information: storage, querying, and analysis of spatial data or spatial-related data, within the database.
Spatial SQL provides the ability of Spatial analysis to a wide range of roles in the organization and beyond. In a common known platform, place, and shared language.
From the DBA to the developer, almost everyone can use it.
The advantages of using SQL with spatial include:
Streamlined data management
Enforced data integrity
Scalability for growth, optimized query processing, high-speed
performance for big data
Broad application across the organization and beyond it
Usability, reuse of processes, efficiency
Documentation and sharing
Development ready: for back ends and front ends
Integration with any client-side, desktop software, or web
Utilizing a database, adding to it the spatial dimension with important external spatial data for enriching and analyzing, will give you the ability to use SQL’s built-in spatial queries, together with the “regular” SQL queries.
It will transform your data and analysis to really answer the questions:
“Where” together with “What”, “When”, and” Why”, gives you accurate and new results and answers.