2 Integrations with Stay Staffed
View a list of Stay Staffed integrations and software that integrates with Stay Staffed below. Compare the best Stay Staffed integrations as well as features, ratings, user reviews, and pricing of software that integrates with Stay Staffed. Here are the current Stay Staffed integrations in 2024:
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Syniti Data Connectivity
Syniti
Optimize access to your IBM Db2 data with high-performance connectivity products for application access to data on IBM Db2 databases. Our standards-based ADO.NET, ODBC, ADO and JDBC connectors enable your applications to easily share data to and from IBM Db2 databases, providing fast and reliable access to Db2 servers running on IBM i/iSeries/AS400, zOS/OS390, VSE/VM, AIX, Solaris, HP/UX, Windows and Linux platforms. AAdd security to your application by encrypting data using one of our security solutions. Efficient use of native IBM operating systems. Built with 20+ years of IBM Db2 expertise. A solution to meet the needs of every environment, ODBC, .NET, JDBC, OLE DB. Setup and toolbox for easy installation and use. Performance .NET data providers for IBM® Db2® with reliable access to Db2 data for third-party commercial applications and custom applications. -
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Syniti Knowledge Platform
Syniti
For the first time, data characteristics like meaning, usage, lineage, alignment to business outcomes and ownership that are repeatedly lost after every project can be captured and retained as tangible knowledge. These vital characteristics can now be reused downstream to advance strategic business initiatives that are dependent on trusted data. Reuse data to deliver your outcomes faster. Capture and release the latent power in your data. Unlock the potential of data in context of your business. Most of your projects require the same insights and understanding into your data, and it’s likely you are consistently reinventing this information. Syniti can deliver this knowledge at a fraction of the cost and with much greater accuracy. Don’t throw away your knowledge. Unlock and reuse insights and knowledge trapped in your data. Preserve knowledge for your future use and reference.
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