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Microsoft Azure uses large-scale virtualization at Microsoft data centers worldwide and offers more than 600 services. [11] Microsoft Azure offers a service level agreement (SLA) that guarantees 99.9% availability for applications and data hosted on its platform, subject to specific terms and conditions outlined in the SLA documentation.
Azure Cosmos DB is a globally distributed, multi-model database service offered by Microsoft. It is designed to provide high availability, scalability, and low-latency access to data for modern applications.
Microsoft Azure Stream Analytics is a serverless scalable complex event processing engine by Microsoft that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media, and other applications. [1]
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 .
Azure SQL Database is built on the foundation of the SQL server database and therefore, kept in sync with the latest version [2] of it by using the common code base. Since the cloud version of the database technology strives to decouple it from the underlying computing infrastructure, it doesn't support some of the context specific T-SQL ...
XML for Analysis (XMLA) is an industry standard for data access in analytical systems, such as online analytical processing (OLAP) and data mining.XMLA is based on other industry standards such as XML, SOAP and HTTP.
Precisely Holdings, LLC, doing business as Precisely, is a software company specializing in data integrity tools, and also providing big data, high-speed sorting, ETL, data integration, data quality, data enrichment, and location intelligence offerings.
A staging area, or landing zone, is an intermediate storage area used for data processing during the extract, transform and load (ETL) process. The data staging area sits between the data source(s) and the data target(s), which are often data warehouses, data marts, or other data repositories.