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Migration addresses the possible obsolescence of the data carrier, but does not address that certain technologies that use the data may be abandoned altogether, leaving migration useless. Time-consuming – migration is a continual process, which must be repeated every time a medium reaches obsolescence, for all data objects stored on a certain ...
Data discovery is the first step in the data transformation process. Typically the data is profiled using profiling tools or sometimes using manually written profiling scripts to better understand the structure and characteristics of the data and decide how it needs to be transformed.
The import and export of data is the automated or semi-automated input and output of data sets between different software applications.It involves "translating" from the format used in one application into that used by another, where such translation is accomplished automatically via machine processes, such as transcoding, data transformation, and others.
Data conversion can also suffer from inexactitude, the result of converting between formats that are conceptually different. The WYSIWYG paradigm, extant in word processors and desktop publishing applications, versus the structural-descriptive paradigm, found in SGML , XML and many applications derived therefrom, like HTML and MathML , is one ...
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
Data transformation or data mediation between a data source and a destination Identification of data relationships as part of data lineage analysis Discovery of hidden sensitive data such as the last four digits of a social security number hidden in another user id as part of a data masking or de-identification project
The application of data virtualization to ETL allowed solving the most common ETL tasks of data migration and application integration for multiple dispersed data sources. Virtual ETL operates with the abstracted representation of the objects or entities gathered from the variety of relational, semi-structured, and unstructured data sources.
Migration can be from a mainframe computer which has a closed architecture, to an open system which employ x86 servers. As well, migration can be from an open system to a Cloud Computing platform. The motivation for this can be the cost savings. [1] Migration can be simplified by tools that can automatically convert data from one form to another.