Tag: Data Quality

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Is BI Too Hard For Us?

We can attack this thorny question in many ways. But let’s set the scene by suggesting that, in concept, BI isn’t really about technology, at least not conceptually. “Business Intelligence” is a lousy term admittedly, because it is not exactly self-defining; pretty much everyone would agree that Business Intelligence is about getting and analyzing information [...]

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Pivotal IT Leverages Pervasive’s Technology to Create an Integrated Approach to Data Quality

One of the keys to successful data integration is taking the time to ensure data quality across business processes. However, few organizations have the patience or can afford the expense associated with attaining a sufficient level of data quality to ensure effective data integration. Pivotal Information Technology (IT) is employing Pervasive Software’s data quality and [...]

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Live from Pervasive Software’s IntegratioNEXT 2010 Conference: Envisioning Healthcare Interoperability

Healthcare and healthcare information technology (HIT) continue to be a data integration challenge for payers, providers, and consumers of healthcare services. This post will explore the role of Pervasive’s Data Integrator software in the solution envisioned by one of the partners presenting at the iNExt, Misys Open Source Solutions (MOSS). However, first we need to [...]

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Live from Pervasive Software’s IntegratioNEXT 2010 Conference: Pervasive Software Innovates Both Below and Above the Waterline!

Amid its 39th quarter of consecutive profitability, Pervasive has launched a new SaaS version of its flagship Data Integrator (DI) product called DI “Cloud Edition”. In short, as part of a process described by CTO Mike Hoskins as “innovating below the water line,” the Pervasive software development team has service-enabled the platform for SOA. This enables the DI product to bring its extensive connectivity to the cloud, either on the Pervasive DataCloud onAmazon’s EC2, or on any cloud…

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Data Quality and My Son’s Grades

Just as David Loshin pointed out in his recent post: “Data Quality Management: Problems and Horror Stories,” you can bump into data quality snafus in unlikely places. At least, I didn’t lose the Mars lander.

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