Enterprise Architecture & Metadata Modeling: A Guide to Conceptual Data Model, Metadata Repository, Business and Systems Re-engineering
| Author | : | |
| Rating | : | 4.81 (533 Votes) |
| Asin | : | 0741453045 |
| Format Type | : | paperback |
| Number of Pages | : | 159 Pages |
| Publish Date | : | 2017-12-22 |
| Language | : | English |
DESCRIPTION:
. Carl has developed a myriad of systems and databases. Carl's consulting experience encompasses applications in compliance, asset management, banking, order processing, telecommunications, insurance, health care, manufacturing, merchandising, business services, and employee management & services. He brings this experience in business and technology to clients, when advising them on how to develop an efficacious ECDM and EMR that are scal
For executives who need to select an architecture of the Enterprise Conceptual Data Model and the Metadata Reposiory, this method will make these tools highly useful. See by example how to apply aforesaid concepts to three enterprises, with various degrees of business complexity. Develop Data Modeler skills and business acumen. From the Author For those who wish to know more about Metadata, Data Architecture & Data Modeling, Systems Architecture & design, functional decomposition this is the perfect learning tool. For more information about me, please google: Carl Turco . I am available t
EMR captures ECDM and applications, programs, databases, etc. With Enterprise Conceptual Data Model and Enterprise Metadata Repository, creating a neat blueprint of corporate data/systems infrastructures is easy. ECDM is the abstract portion of EMR. ECDM correlates the conceptual business world that executives relate to with the concrete world that techies relate to; hence a bridge is formed. Corporations should adopt this new methodology.. ECDM captures abstract business concepts. This facilitates swift drill-down into every database, system, and business display that needs to adjust to a business change. With ECDM it is desirable to use de-normalized data structures that greatly reduce the number of models, entities, and attributes that business folks must consider when implementing business changes