https://towardsdatascience.com/how-to-build-a-data-lake-from-scratch-part-1-the-setup-34ea1665a06e
How to build a data lake from scratch — Part 1: The setup
How to build a data lake from scratch — Part 1: The setup
Medium
How to build a data lake from scratch — Part 1: The setup
The complete tutorial of how to make use of popular technology to build a data engineering sandbox
https://towardsdatascience.com/how-to-build-a-data-lake-from-scratch-part-2-connecting-the-components-1bc659cb3f4f
How to build a data lake from scratch — Part 2: Connecting the components
How to build a data lake from scratch — Part 2: Connecting the components
Medium
How to build a data lake from scratch — Part 2: Connecting the components
The complete tutorial of how to make use of popular technology to build a data engineering sandbox
https://www.gojek.io/blog/a-toast-from-postgresql
How Postgres handles data storage of oversized attributes.
How Postgres handles data storage of oversized attributes.
www.gojek.io
A TOAST from PostgreSQL - 3 min read
How Postgres handles data storage of oversized attributes.
https://stackoverflow.com/questions/2519985/postgresql-to-data-warehouse-best-approach-for-near-real-time-etl-extraction
PostgreSQL to Data-Warehouse: Best approach for near-real-time ETL / extraction of data
PostgreSQL to Data-Warehouse: Best approach for near-real-time ETL / extraction of data
Stack Overflow
PostgreSQL to Data-Warehouse: Best approach for near-real-time ETL / extraction of data
Background:
I have a PostgreSQL (v8.3) database that is heavily optimized for OLTP.
I need to extract data from it on a semi real-time basis (some-one is bound to ask what semi real-time means a...
I have a PostgreSQL (v8.3) database that is heavily optimized for OLTP.
I need to extract data from it on a semi real-time basis (some-one is bound to ask what semi real-time means a...
https://www.linkedin.com/pulse/building-data-warehouse-fundamentals-principles-postgresql-r-s-j1tyc
Building a Data Warehouse: Fundamentals, Principles, and PostgreSQL Implementation
Building a Data Warehouse: Fundamentals, Principles, and PostgreSQL Implementation
Linkedin
Building a Data Warehouse: Fundamentals, Principles, and PostgreSQL Implementation
Introduction A data warehouse is a centralized repository designed to store and manage large volumes of structured data from various sources. It supports business intelligence (BI) activities, including querying, reporting, and data analysis, enabling organizations…
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https://www.linkedin.com/pulse/historical-data-tracking-postgresql-part-1-jaime-mart%C3%ADnez-verd%C3%BA/?trk=article-ssr-frontend-pulse_little-text-block
Historical Data Tracking in PostgreSQL - Part 1: Historical Table and Triggers
Historical Data Tracking in PostgreSQL - Part 1: Historical Table and Triggers
Linkedin
Historical Data Tracking in PostgreSQL - Part 1: Historical Table and Triggers
Introduction to Historical Data Tracking in PostgreSQL Historical data tracking, also known as #historification, plays a crucial role in maintaining a comprehensive record of changes made to data over time. This process allows us to access previous versions…
https://www.linkedin.com/pulse/historical-data-tracking-postgresql-part-2-trigger-mart%C3%ADnez-verd%C3%BA/?trk=article-ssr-frontend-pulse_little-text-block
Historical Data Tracking in PostgreSQL - Part 2: Trigger Functions
Historical Data Tracking in PostgreSQL - Part 2: Trigger Functions
Linkedin
Historical Data Tracking in PostgreSQL - Part 2: Trigger Functions
Introduction In the first article of this series, we explored the concept of historical data tracking in #PostgreSQL and discussed the importance of maintaining historical records in certain scenarios. To achieve this functionality in PostgreSQL, where native…