Category: Data Quality

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Big Ideas, Bright Minds Converge at IntegrationWorld-Europe 2012

A couple weeks ago, about a hundred of Pervasive’s EMEA-based partners, customers and industry analysts gathered to discuss best practices and trends around data integration – including, cloud, Big Data, and data quality – at IntegrationWorld-Europe, which took place at the fabulously modern Cumberland Hotel in London. The event included an informative keynote from EMA Vice President Shawn Rogers who [...]

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The New Data “Entrepreneurs”

With the growing interest in the potential business value to be gleaned from “Big Data” or Extreme Information analytics, a new role has been gaining interest: the Data Scientist. The data scientist is a hybrid role encompassing computer science, advanced statistics/mathematics, forensics analytics and other advanced skills, as well as business savvy. The data scientist [...]

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Pervasive IntegrationWorld: Where The World’s Best Innovative Minds Meet

More and more organizations are realizing that data integration done RIGHT can be a key differentiator.  But, with the ever-changing integration landscape, how can IT professionals be sure they are taking the right approach?  Has the democratization of integration services thanks to Cloud and SaaS-based services made the lives of business and technology innovators easier, [...]

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Data Quality: How did you get into this mess?

Thoughts on enterprise data quality Few things get better with time.  Without careful attention your data certainly won’t be one of them. For most organizations, a love/hate relationship exists with their data.  We love that we can draw together information from various systems and use it to see a picture of how effective we’re being. [...]

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Data Profiling – Helping the Business Ask the Right Questions

Business users possess the knowledge of how data is used for certain business processes — such business users are invaluable for examining business data: first, to determine its value in context, and second, to understand how it contributes to intelligence being gathered for the enterprise. Until data is understood in relationships to various systems and [...]

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