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Teradata Releases Manufacturing Logical Data Model 4.0


Pre-packaged information blueprint adds seven significant business functions.

ORLANDO, FL — Teradata Corporation (NYSE: TDC), the global leader in enterprise data warehousing, today announces the general customer availability of Manufacturing Logical Data Model (MLDM) 4.0, which defines how different types of data relate to each other and is a roadmap for building an enterprise data warehouse. The upgrade, announced here at the SAP Logistics and Supply Chain Management conference, specifically addresses customer needs in a range of vertical manufacturing segments, including the automotive, consumer products and high-tech industries.

“The new Teradata Manufacturing Logical Data Model 4.0 is far more comprehensive than earlier models, reflecting the growing sophistication of customers in their use of an enterprise data warehouse to run business operations, and the demands of their markets,” said Keith Henry, Teradata vice president for manufacturing global industry solutions.

Teradata MLDM 4.0 provides manufacturers with a best-in-class framework for building an enterprise data warehouse. It includes more than 80 subject areas, more than 600 individual pieces of data from across the enterprise and more than 2,100 relationships among that data.

Seven new and expanded capabilities are included in MLDM 4.0. These include activity-based costing, planogram, trade funds management, party preferences, legal case management, account budgets and unstructured text capture. In addition, the new version includes additional capabilities in product warranty and quality, demand planning, yield management, dynamic shift scheduling and maintenance repair and overhaul.

The MLDM allows manufacturers to leverage Teradata’s knowledge acquired from years of data warehousing experience. By using this pre-built model, manufacturers can accelerate the typical time to deploy an enterprise data warehouse and realize return on investment in less time. The MLDM enables the consolidation of data from a wide variety of operational and legacy sources into a single repository.


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