Best practices for enterprise systems data management
Enterprise resources planning (ERP) and enterprise asset management (EAM) are widely recognized as the transactional systems of record in manufacturing, production and other type enterprises. At the same time, long-time issues related to implementation and integration remain relevant for many using companies.
It has been said that IT and finance departments lean to the ERP side of the coin, while plant operators like EAM’s rich functionality. Different type databases, table structures, upgrade issues and system constraints add costs to on-going integration, while initial implementation costs remain an issue.
The single biggest issue facing managers in discrete manufacturing and process production industries is how to make use of all the data being collected. Correcting the absence of a structured data schema for analytics suitability requires accurate master data records, equipment hierarchies, problem-failure mapping systems, failure codes and more. Challenges remain when it comes to incorporating data from real-time automation systems into enterprise systems.
Tune into this webcast to learn how to tune your data to deliver meaningful information.
- How to leverage Big Data across the enterprise
- Understand how to standardize engineering across facilities
- Learn to implement engineering improvements efficiently
- Analyze performance efficiently
Kevin Parker, Content Manager, CFE Media and Technology