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|style="width:50%"|'''Featured Article'''||'''Did you know?''' | |style="width:50%"|'''Featured Article'''||'''Did you know?''' | ||
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<blockquote> | <blockquote> | ||
<span style="font-size:14pt">'''[[Table Extraction]]'''</span> | <span style="font-size:14pt">'''[[Table Extraction]]'''</span> | ||
</blockquote> | </blockquote> | ||
[[file:simpletable.png|thumb|300px|Data in an Excel spreadsheet is an example of tabular data.]] | |||
Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved into Egyptian pyramids! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or a pyramid sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data. | Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved into Egyptian pyramids! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or a pyramid sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data. |
Revision as of 12:21, 9 January 2020
Featured Article | Did you know? |
Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved into Egyptian pyramids! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or a pyramid sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data. In Grooper, tabular data can be extracted using the Row Match, Header-Value, or Infer Grid table extraction methods. |
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New in 2.8 | Featured Use Case |
New Microfiche Processing capabilities including
Two additional batch activities
Two additional IP commands New extraction methods available to data fields Simpler and expanded Database Lookup capabilities. Expression based Field Mapping between data elements and their locations in external storage platforms, allowing for easier data formatting and exporting of batch processing metadata. |
Use case. Use case. Here a use case. There a use case. Everywhere a use case.
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