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Data is one of the four critical resources in an organization, equivalent with the financial resource, real property, and the human resource. Yet most organizations fail to manage the data with the same priority, discipline, and attention that is applied to the other critical resource. The time for disciplined management of the data resource is long overdue.
Most public and private sector organizations face many challenges with burgeoning quantities of disparate data. These disparate data are not well understood, have high redundancy, are not consistent, have low quality, and fail to adequately support the organization’s business information demand. The only way to resolve this situation is to thoroughly understand how and why disparate data are created, and how those problems can be resolved.
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This online training course begins with common definitions of data disparity and its impact on the organization, and procedes to describe 10 sets of bad habits and good practices related to the architecture and governance components of data resource management.
You will learn:
- How to define and identify disparate data.
- How to identify the impact of disparate data on the business.
- How to define, identify, and manage data resource quality.
- The common problems with the architecture and governance of the data resource.
- The best practices to solve these architecture and governance problems.
This course is geared toward:
- Anyone who has responsibility for the architecture or governance of the data resource.
- Data resource quality practitioners at all levels.
- Business executives and managers who struggle with the business impacts of poor quality data.
- IT managers who are challenged to deliver reliable and trusted data to support the business information demand.
- Data and information system architects who need to break the cycle of disparate data creation.
Best Practices in Data Resource Management
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DQ-03-00 About the Course (5 min)
DQ-03-01 Introduction (26 min)
- Current Situation
- Halting Data Disparity
DQ-03-02 Architecture (93 min)
- Data Names
- Data Definitions
- Data Structures
- Data Integrity Rules
- Data Documentation
DQ-03-03 Governance (53 min)
- Data Orientation
- Data Availability
- Data Responsibility
- Data Vision
- Data Recognition
DQ-03-04 Conclusion (9 min)
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Click –here- to download a more detailed outline of this course.
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This exam tests knowledge and understanding of architectural and governance problems leading to disparate data and best practice solutions for data resource management.
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You will be tested in these areas:
- How to define and identify disparate data
- How to identify the impact of disparate data on the business
- How to define and manage data resource quality
- Specific problems and solutions for data resource architecture, including data names, data definitions, data structures, data integrity rules, and data documentation
- Specific problems and solutions for data governance and data resource management, including data orientation, data availability, data responsibility, data vision, and data recognition
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Additional Information
Number of Questions: 20
Time Limit: 40 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education documenting that you have demonstrated mastery of the topic. Further, the exam counts towards Certified Information Management Professional (CIMP) designation in Data Governance and Data Modeling & Metadata Management tracks.
We recommend that you take detailed notes and review the course material multiple times before taking this exam. Click here to learn more about CIMP exams.
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Course Review 
A wonderful course 