How does a data warehouse work?
Posted: Wed Jan 08, 2025 3:18 am
What is the difference between a data warehouse and a data lake?
A data warehouse should not be confused with a data lake . Although in principle they are both data storage systems , their structures and purposes are completely different.
The analogy is cambodia phone data quite clear when we talk about a data warehouse or a data "lake" . We can easily imagine the major difference between these two systems. The data warehouse, like a physical warehouse , is structured, ordered, organized to allow access to all information easily by the applications and software that have access to it. A data lake, on the other hand, is a reservoir of raw , unprocessed data that still needs to be explored. This type of structure is used for machine learning and big data projects . The quantity and massive volume of jumbled data contained in data lakes do not allow the use of SQL queries as with a data warehouse.
To understand how a data warehouse works , you need to look at its IT structure, but also at its interaction with an operator via a software interface.
Computer operation of a data warehouse
From an IT perspective, a data warehouse is a database supported by a very large memory . A mix of SSD, HDD and RAM devices is assembled to obtain the best compromise between storage power, speed of access to information and especially installation cost. The warehouse management process is ETL type, to collect, transform and organize any type of data that can come from an infinite number of sources. These are first extracted as operational databases in CSV format before being transformed and formatted to meet the needs of the applications for the future. Little by little, the information is sorted, cleaned, organized by similarity and into classes according to the requests, before being made available to the applications to respond to the requests of the analysts. Accessibility to the data is guaranteed by the use of warehouse management systems .
A data warehouse should not be confused with a data lake . Although in principle they are both data storage systems , their structures and purposes are completely different.
The analogy is cambodia phone data quite clear when we talk about a data warehouse or a data "lake" . We can easily imagine the major difference between these two systems. The data warehouse, like a physical warehouse , is structured, ordered, organized to allow access to all information easily by the applications and software that have access to it. A data lake, on the other hand, is a reservoir of raw , unprocessed data that still needs to be explored. This type of structure is used for machine learning and big data projects . The quantity and massive volume of jumbled data contained in data lakes do not allow the use of SQL queries as with a data warehouse.
To understand how a data warehouse works , you need to look at its IT structure, but also at its interaction with an operator via a software interface.
Computer operation of a data warehouse
From an IT perspective, a data warehouse is a database supported by a very large memory . A mix of SSD, HDD and RAM devices is assembled to obtain the best compromise between storage power, speed of access to information and especially installation cost. The warehouse management process is ETL type, to collect, transform and organize any type of data that can come from an infinite number of sources. These are first extracted as operational databases in CSV format before being transformed and formatted to meet the needs of the applications for the future. Little by little, the information is sorted, cleaned, organized by similarity and into classes according to the requests, before being made available to the applications to respond to the requests of the analysts. Accessibility to the data is guaranteed by the use of warehouse management systems .