Enterprise Data Management
Student’s Name
Instructor’s Name
Institutional Affiliation(s)
- Which 4-5 components of EDM would you implement first? Why?
The first step in the data management journey is to complete a data audit. As a leading management leader, I would chart or list data produced, deleted, and used in a business process. This is called a data-cataloging project, which is important in ensuring a big picture of the data. I will ensure in the catalog everything is comprehensive as possible in notes or even emails. Once data has cataloged, we need to clean and transform data into a standard format. Unfortunately, data preparation and data cataloging can be complex, intensive, challenging, but once the projects are completed, there will be a success in data management (Cashdollar, 2008).
The following are the components I will consider in my company.
- Data architecture is the set of policies, standards, rules, and models that will define and govern the type of data that will be collected and how they will be integrated, managed, used, and stored within the company. This will provide a formal approach to managing and creating the flow of data and how these data will be processed in the organization on the systems and applications.
- Data integration and development are the deployment, design, analysis, and maintenance of data solutions, which will minimize the enterprise’s value of data resources. This contains data management activities that will support the system building, deployment, and testing.
- Data operations management is the support and maintenance development with structured data resources to the enterprise. This governs the data through standards and processes based on the data making, activities, function, and governance of the data operations to be more consistent, more effective, and more efficient across the organization.
- Data security management is the execution, development, and planning of the procedures and security policies that will provide access, authorization, auditing, and authentication of the data information assets.
- Reference and master data management is the continuing maintenance and reconciliation of the master data and the reference data, which will provide for the context of analytical data and its transaction. Master data and reference are combined into a discipline where reference data management is controlled over defined domain values, while master data management controls data values.
- What do you see are the key organizational and technical risks?
Our data will be secure and available when needed in the business users whenever needed by making data management. This will benefit the team by ensuring the following are met (Hamlescher, 2014). There will be high-quality data for accurate analysis. There will be consistent data architecture that will scale the enterprise. There will be compliant and data security under regulations, and there will be consolidating data in multiple sources for increased efficiency.
Informatica is a data management solution that will assist in the implementation of all these. Data analysis and other data work will help the team be more efficient since people in the organization know where they will find the data they need. With well-governed data lineage, it will be easy to quickly identify data dependencies and understand who is using each data source. It will help one to make relevant tables more accessible. Data management works similarly with enterprise data management, but this technology will enable one to create a single view of data in the master record or master file.
References
Cashdollar, J. J., Smith, J. M., Clark, P. R., & Sanders, M. D. (2008). U.S. Patent Application No. 11/723,736.
Hamlescher, S., Vogler, H. K., & Babu, S. (2014). U.S. Patent No. 8,892,534. Washington, DC: U.S. Patent and Trademark Office.