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Power Query was first announced in 2011 under the codename "Data Explorer" as part of Azure SQL Labs. In 2013, in order to expand on the self-service business intelligence capabilities of Microsoft Excel, the project was redesigned to be packaged as an add-in Excel and was renamed "Data Explorer Preview for Excel" [4], and was made available for Excel 2010 and Excel 2013. [5]
Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation.
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.
These are then converted to a SQL SELECT statement. The query is then compiled — this involves parsing the query (involves syntax checking and determining the columns to query in the database table), then converting into an internal Jet query object format, which is then tokenized and organized into a tree
Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
Power View A data visualisation tool that originally shipped as part of SQL Server 2012, later an add-in for Microsoft Excel [142] SQL14 SQL Server 2014 Version 12 [143] Hekaton: SQL Server In-Memory OLTP In-memory database engine built into SQL Server 2014 [144] SQL16 SQL Server 2016 Version 13 [145] Helsinki SQL Server 2017 Version 14 [146 ...
Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.
Query and update pipeline, processes queries, filters and updates requests to convert them into canonical command trees which are then converted into store-specific queries by the map provider. Metadata services , which handle all metadata related to entities, relationships and mappings.