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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]
In tableau software, data blending is a technique to combine data from multiple data sources in the data visualization. [17] A key differentiator is the granularity of the data join. When blending data into a single data set, this would use a SQL database join , which would usually join at the most granular level, using an ID field where ...
DAX expressions allow a user to create calculated columns and measures to summarize and aggregate large quantities of data. Queries in the model are reduced to xmSQL, a pseudo-SQL language in the storage engines that drive the data model. [11] A companion feature to Power Pivot named Power Query may be used to perform ETL processes prior to ...
Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another ...
A comma separated list of the fields to use. Allowed fields are title, text, auxiliary_text, opening_text, headings and all. &cirrusMltUseFields (true or false) use only the field data. Defaults to false: the system will extract the content of the text field to build the query. &cirrusMltPercentTermsToMatch: The percentage of terms to match on.
A query language, also known as data query language or database query language (DQL), is a computer language used to make queries in databases and information systems. In database systems, query languages rely on strict theory to retrieve information. [1] A well known example is the Structured Query Language (SQL).
An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.