Best Practices: Data Admin & Data Management
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I built this presentation for Informatica World in 2006. It is all about Data Administration, Data Quality and Data Management. It is NOT about the Informatica product. This presentation was a hit, with standing room only full of about 150 people. The content is still useful and applicable today. If you want to use my material, please put (C) Dan Linstedt, all rights reserved, http://LearnDataVault.com
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Best Practices: Data Admin & Data Management
- 1. Best Practices: Data Administration and Quality Daniel Linstedt, all rights reserved, http://LearnDataVault.com
- 4. Defining Data Administration Issues
- 5. What is Data Administration? “ What do we mean by that in the case of data administration? We mean that DA must get out of the design review committee mentality and substitute something more value-added and flexible. It must recognize that systems tend to grow organically, and be a part of that process, rather than an instiller of order upon it.” Eric Rawlins, 1995 Originally Published by: Database Research Group, Inc http://www.well.com/user/woodman/organic.html
- 7. Cross-Organization Roles and Responsibilities Business ( Owner View) Data Steward Discipline Authority Business Process Manager Data Usage Contact Data Manager Data Modeler DA is a ROLE and typically involves more than one person in order to achieve success. Logical (Designer View) Data Administrator Physical ( Builder View) Database Administrator
- 10. Defining Data Administration Issues Top 4 Examples
- 20. DA: Architecting Data Governance Business Rules & IQ EDW Source Systems Non Compliant Data Marts Business Rules & IQ EDW Source Systems Data Marts Compliant Hard Business Rules Soft Business Rules & IQ Shift to process AFTER the EDW Hard Business Rules Still process Before the EDW
- 24. DA: Tracking Errors – KPIs at Work
- 26. Metadata Administration Lifecycle Identify New Metadata Integrate With Master Metadata Repository Edit and Manage Master Metadata (Provide Business Users with Web Interface) Stitch Master Metadata Together Compare Master Metadata With Business Process And Objectives Export Master Metadata or Deploy via SOA With Master Data Set Derived from Meta Integration Metadata Lifecycle
- 34. Thank you Contact us today: Dan Linstedt [email_address] http://LearnDataVault.com
Notes de l'éditeur
- The purpose of this slide show is to present and discuss the role of data administration in the data integration world. Here we define some of the business and technical problems that DA’s face on a daily basis, then we move on to discuss the types of activities that a DA will under-take in an enterprise level initiative. Please bear in mind, that the DA is a role, and may not end-up being just a single individual, but rather a group of individuals, some of whom are directly responsible for Data Management as well.
- In this section we define different DA roles, issues, and conceptual notions. We discuss the DA role from a 20,000 foot level where the enterprise “see’s” data administrators, and begins to understand what they do. The role of the DA ranges from monitoring business user meetings to over-seeing the design of data flow through business processes. Business Process flow has a large impact on the world of the DA and what they need to be capable of achieving. They need to work across multiple groups in order to achieve an enterprise vision of the data assets and models that will serve the enterprise.
- http://www.cio.gov.bc.ca/other/daf/DMRolesRespV1.pdf
- http://www.cio.gov.bc.ca/other/daf/DMRolesRespV1.pdf
- http://www.educause.edu/ir/library/text/CEM9047.txt
- Data Must Be: Auditable, Traceable, Stored in the granular format it arrived in, A “statement-of-fact” Business Rules must move to the output side of the equation. Data can be integrated by the same semantic grain, but cannot be altered.
- The Data Administrator is responsible for identifying auditable or audited sources of data. The DA will be responsible for ensuring which data sets can and should be utilized to load enterprise data warehouses. The DA will set policies and procedures for measuring, auditing, and assessing the quality of information flowing to and from the source systems.
- The Data Administrator is responsible for assigning or classifying different groups of errors, what will make the data set or break the data set. They are also responsible for the integrity of the data set, and ensuring that the data set matches the requirements set forth by the business users.
- The Data Administrator might use a live chart like this one to examine the errors and the occurrences of errors over time. The DA will be responsible for the quality of the data, as it relates to the business metrics put forward. The DA will be responsible for maintaining the logical models, and the business processes – and if the error count is too high for a specific area of expertise, then the Data Manager must be notified, and corrective action must be taken.
- Organic Data Administration, http://www.well.com/user/woodman/organic.html