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Grooper is a software application that helps organizations innovate workflows by integrating difficult data. Grooper empowers rapid innovation for organizations processing and integrating large quantities of difficult data. Created by a team of courageous developers frustrated by limitations in existing solutions, Grooper is an intelligent document and digital data integration platform. Grooper combines patented and sophisticated image processing, capture technology, machine learning, and natural language processing. Grooper – intelligent document processing; limitless, template-free data integration. |
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Database Export is one of the main ways to Deliver data Collected in Grooper. A completed Content Model and accompanying Batch for what will be built can be found here. It is not required to download to understand this article, but can be helpful because it can be used to follow along with the content of this article. This file was exported from and meant for use in Grooper 2.9 The most important goal of Grooper is to deliver accurate data to line of business systems that allow the information to be integrated into impactful business decisioning. Tables in databases remain, to this day, one of the main vessels by which this information is stored. Grooper's Database Export activity is the mechanism by which this delivery is performed. Database Export uses a configured Data Connection to establish a link to (Microsoft SQL Server or ODBC-compliant) tables in a database and intelligently populate said tables.Two key distinctions about Grooper's Database Export activity are its ability to take full advantage of its sophisticated hierarchical data modeling to flatten complex/inherited data structures, and the ease of delivery to multiple tables at once. For more information on Database Export, visit the full wiki artcile here. |
Database Lookups changed in version 2.80. Prior to Version 2.80, database lookups were performed on individual Data Fields in a Data Model, using simple field mappings. Now, lookups are configured on a Data Model, Data Section or Data Table’s properties, using SQL queries. Other improvements include:
Visit the Database Lookup article for more information. |
New in 2.9 | Featured Use Case | ||||||||||||||||||||||||||||||||||||
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In 1947, Oklahoma Senate Bill 125 created a Death, Disability and Retirement Fund for Department of Public Safety members. In 1980, a new bill established the Oklahoma Law Enforcement Retirement System (OLERS) which continued the previous plan and expanded upon it to include members of other law enforcement agencies. Currently, OLERS provides retirement funds to 11 different statewide law enforcement agencies. Key Outcomes:
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