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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Big Data Hub

The judiciary, like the legal system in general, is considered one of the largest “text processing industries” Language, documents, and texts are the raw material of legal and judicial work. As such, the judiciary has long been a field ripe for the use of technologies like automation to support the processing of documents.

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Business process reengineering (BPR) examples

IBM Big Data Hub

An early case study of BPR was Ford Motor Company, which successfully implemented reengineering efforts in the 1990s to streamline its manufacturing processes and improve competitiveness. Organizations of all sizes and industries implement business process reengineering.

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Data mesh 101: Domain-driven ownership and the Collibra Data Office

Collibra

When organizations pump everything into a central data lake, it separates the data from the subject matter experts, which decreases productivity. – James Serra, ‘Data Mesh: Centralized ownership vs decentralized ownership. Centralized data offices no longer take this on. Innovation slows.

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Sharing best practices in our new Data to Diamonds book

CGI

Making effective use of big data has become a top priority for commercial and government organizations. Having worked on many complex data and analytics projects over the years, we have compiled numerous best practices, and developed our Data2Diamonds methodology for the design and implementation of big data analytics solutions.

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APEC Privacy Update – Beijing Meetings

Hunton Privacy

In March this year, APEC and the Article 29 Working Party released the so-called Referential, a jointly developed mapping document comparing APEC CBPRs to the EU Binding Corporate Rules (“BCRs”). The document was intended to be a high-level guide for companies that are seeking approval and certification under both systems.

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How to build a decision tree model in IBM Db2

IBM Big Data Hub

Included references to IBM Db2’s documentation for the ML stored procedures I used in this tutorial. Check out the following resources to learn more about the ML features in IBM Db2 and see additional examples of ML use cases implemented with these features. Challenges in deploying machine learning: a survey of case studies.

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Kofax Intelligent Automation Deployment at Davies Turner Wins Ventana Award for Overall Digital Leadership

Info Source

“This award is a great illustration of how Kofax enables increased productivity to help organizations remain on track for profitable growth and significant competitive advantage—even in industries that face immense data management challenges and razor thin profit margins.”.