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ETL tools are typically used by a broad range of professionals – from students in computer science looking to quickly import large data sets to database architects in charge of company account management, ETL tools have become a convenient tool that can be relied on to get maximum performance.
Power Query is an ETL tool created by Microsoft for data extraction, loading and transformation, and is used to retrieve data from sources, process it, and load them into one or more target systems. Power Query is available in several variations within the Microsoft Power Platform , and is used for business intelligence on fully or partially ...
Extract, transform, load tools are software packages that facilitate the performing of ETL tasks. Pages in category "Extract, transform, load tools" The following 35 pages are in this category, out of 35 total.
Spatial extract, transform, load (spatial ETL), also known as geospatial transformation and load (GTL), is a process for managing and manipulating geospatial data, for example map data. It is a type of extract, transform, load (ETL) process, with software tools and libraries specialised for geographical information. [1]
KNIME workflows can be used as data sets to create report templates that can be exported to document formats such as doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (not limited to the available RAM).
SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. [3] SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.
The SSIS Import/Export Wizard lets the user create packages that move data from a single data source to a destination with no transformations. The Wizard can quickly move data from a variety of source types to a variety of destination types, including text files and other SQL Server instances.
Dbt has the goal of allowing analysts to work more like software engineers, in line with the dbt viewpoint. [11] Dbt uses YAML files to declare properties. seed is a type of reference table used in dbt for static or infrequently changed data, like for example country codes or lookup tables), which are CSV based and typically stored in a seeds ...
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