How To Model Enterprise Data Management

Enterprise Data Management, or EDM, was made to harmonize data in companies worldwide. It aims to consistently define data and standardize them so that business owners and project managers can utilize the information for decision making, improvements and lastly, for simplification and standardization of work process flow.

Modeling Enterprise Data Management simply means that the data available is incorporated in models for it to be visually easier to understand. The following are the basic stages in Modeling EDM.

1.    Develop a Team. This team will be composed of project owners, sponsors, and the managers and staff directly utilizing the data. This data management initiative is usually a job on top of their current and regular workload. Because of this, there must be a strict timeline and habitual status meetings for this to pursue. Some companies hire an external expert who can lead the team, while others pull out one employee and he is tasked to lead the group.

2.    Planning Stage. The team should decide how to go about the data management. There must be a standard operating procedure on how the group will examine and organize the available information. Scope of work, resources, storage of data and other project guidelines must be clear with all parties. The technology to be utilized such as software and other tools must be mentioned. Also, the topic or data to be managed must be finalized in this stage. In this stage, the subject or EDM project must be well-defined. The following are samples of topics:

• If your enterprise is a university, you can manage data of complete student population and their vital information. Info may include scholarships, year/s in college, gender, religion, course, etc.
• If your enterprise is a logistics company, you can develop database management for your fleet. It can be the data on trucks, cargoes, and even your drivers.
• If you are on a manufacturing enterprise, you can develop EDM in the raw materials information or finished goods.

3.    Identification Stage. Based on the thesaurus, an entity can be synonymous to a body, unit, thing or article. A key entity is a unit that is considered part of the bulk data. For example, when you want EDM in the library (one of the easiest examples), the key entities center on the following:

• Title
• Author
• Publisher
• Date Published

4.    Development of Relationships in the Model. This stage requires in-depth analysis. It is in this stage that the actual modeling is done. The framework will be the relationship of the entities. In the library example previously, relationships can be as follows:

• One is to one: This is the relationship of publisher with the publishing house.
• One is to many: An author can have many titles made, or there can be one, two or more authors in one title.

5.    Documentation Stage. All the information available will now be keyed in or inputted in the entities. For easier tracking, every document must have a control number (such as ID number, book code, etc). Using the example above, all the name of the authors should be written under Author. The control number can be the book code where it will be stored.

6.    Integration Stage. In this stage, data is mapped into the business process. The I.T. representative is responsible in uploading data in the actual business system. However, the whole team is still checking for flaws, updates and further improvements.

7.    Implementation and Evaluation Stage. There must be training for end-users before giving them a free hand on the EDM system. Everyone must understand the data management’s goals and roles in the business. The evaluation stage can happen after a week or a month long implementation.