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Cloud-based data warehouses like Amazon Redshift, Google BigQuery, Microsoft Azure Synapse Analytics and Snowflake Inc. have been able to provide highly scalable computing power. This lets businesses forgo preload transformations and replicate raw data into their data warehouses, where it can transform them as needed using SQL .
Snowflake Inc. is an American cloud-based data storage company. Headquartered in Bozeman, Montana, it operates a platform that allows for data analysis and simultaneous access of data sets with minimal latency. [1] It operates on Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
The term "load testing" is often used synonymously with concurrency testing, software performance testing, reliability testing, and volume testing for specific scenarios. All of these are types of non-functional testing that are not part of functionality testing used to validate suitability for use of any given software.
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format. This enables faster loading times.
Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...
Image source: The Motley Fool. Snowflake (NYSE: SNOW) Q4 2025 Earnings Call Feb 26, 2025, 5:00 p.m. ET. Contents: Prepared Remarks. Questions and Answers. Call ...
In computing, data transformation is the process of converting data from one format or structure into another format or structure. It is a fundamental aspect of most data integration [1] and data management tasks such as data wrangling, data warehousing, data integration and application integration.
Data vault modeling was originally conceived by Dan Linstedt in the 1990s and was released in 2000 as a public domain modeling method. In a series of five articles in The Data Administration Newsletter the basic rules of the Data Vault method are expanded and explained.