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Data Integrity Rules 2

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by Michael Brackett Precise data integrity rules  (defined in Data Integrity Rules 1) are grouped into six different types, specifically data value rules and conditional data value rules, data structure rules and conditional data structure rules, data derivation and data re-derivation rules, data retention rules, data selection rules, and data conversion rules. A data value…

Cognitive Computing Gives Hand Up to Healthcare

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by Jennifer Zaino IBM counts healthcare among the key sectors that it expects will realize business advantages with the help of Watson, its headline-making Cognitive Computing platform. The vendor has partnered with some of the best-known hospitals and health benefits organizations, such as Memorial Sloan-Kettering, the University of Texas MD Anderson Cancer Center, Cleveland Clinic…

“Governance Now” for Financial Reference Data Governance

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by Lowell Fryman & Dan Meers Many financial services organizations continue to deal with reference data as an application-level issue.  After all, every account or application requires some reference data.  Financial Reference Data is at the heart of accounting and financial reporting & analytics.  The growing level of support for solid master and reference data…

Graph Databases have Impact on Healthcare Sector

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by Jennifer Zaino Healthcare sector startups are ripe for exploiting NoSQL graph databases. With a data model predicated on nodes/vertices and relationships/edges, graph databases provide a sturdy means to probe connections between entities, especially the farther removed from each other they are. Healthcare organizations can “realize new opportunities and efficiencies by leveraging the connections within…

Enterprise Security in a Mobile World

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by Jelani Harper The objective of a growing number of trends within the data sphere is to empower the business user through what has become known as the consumerization of IT. Developments in self-service Business Intelligence, Cloud Computing, mobile technologies, and the proliferation of the Bring Your Own Device phenomenon has enabled end users to…

From Business Intelligence to Operational Intelligence

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by Jelani Harper Business Intelligence (BI) has emerged from the backrooms of IT departments to take up residence in the front offices of personnel in business and operations, and even of some C-level executives. Despite advancements in Data Discovery tools which considerably expedite the ease and insight offered, in Big Data applications the best of…

Heralding Software Defined Storage, Part 2

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by Jelani Harper The boons of Software Defined Storage and the specific applications of this technology that IBM has recently unveiled—Elastic Storage and Storlets—and the ways that SDS has restructured conventional notions of availability, scalability, and accessibility in the era of Big Data were discussed at length in part one of this article. What was…

Data Integrity Rules 1

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by Michael Brackett Developing formal business rules is an excellent concept that must be followed by both business professionals and data management professionals to ensure high quality processes and data. However, developing formal business rules is often oriented toward processes, procedures, and policies rather than toward data resource quality.  Formal business rules must be developed…

The Relevance of Open Source (Advanced) Analytics

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by Jelani Harper There are few limitations to the ways in which the confluence of Data Science and advanced analytics can aid the enterprise. The predictive capabilities of the latter can enable forecasting for Business Intelligence tools, accurately presage the needs, services, and advertising products most sought by consumers, or design applications that can proactively…

Heralding Software Defined Storage, Part 1

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by Jelani Harper The emergence of Big Data has restructured a number of facets of Data Management including options for analytics, accessibility (the Cloud), and application management. In the wake of these aforementioned advantages, very real concerns for storage due to the explosive volume of data generated by Big Data—which is largely unstructured—and a growing…