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BiPM Practice Tool Listing Page
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Data Monitoring Checklist
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This checklist enables a consistency and completeness of data monitoring activities. It contains the Data Monitoring imperatives for planning, design and execution. |
| This BiPM Practice Tool is linked to:
Data Quality,
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| This page is part of Data Quality Practice and Tool-Kit Package package, which is a paid service. To supplement the paid products, BiPMinstitute.com provides over 1000 pages of premium content as a Free service. |
| Our products provide a level of detail, that you need for 'on the ground and hands-on' implementations. |
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If you have not bought this service, please refer Data Quality Practice and Tool-Kit Package to review and buy our offering.
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Abstract
Header Information:
- Work-Tool Code: DQ01WT09
- Product Code: BIPM-DQPACK02
- Total Checklist items: 23
- Help File (excluding FAQs and Tips): 4 pages
- Relevant FAQ: 1
- Relevant Tips: 1
- Number of Main working-sheets: 1
Checklist Items Group
- Data Monitoring Plan and Specifications
- Data Monitoring Scripts and Configuration Development and Testing
- Data Monitoring Results management
Overall Usage Guide
Purpose of Data Monitoring Checklist-
Data Monitoring checklist is a conscience keeper at various stages of Data Monitoring. Data Monitoring Checklist is not a formal document, requiring approvals or sign-off. Data Monitoring needs to be well-balanced in terms of scope, as it can place some level of processing load on the systems and also placed the demand for analyzing these reports.
When is Data Monitoring Checklist used?-
Data Monitoring checklist is used for planning, specifications, design, test and results management phases. In other words, it is used through out the data monitoring lifecycle.
Who uses Data Monitoring Checklist?
This checklist is used by the IT specialist and business analyst linked with Data Monitoring. Occasionally it may also be referred by the Data Custodian and Data Steward.
Which are the linked work-tools?
Relevant FAQs:
- Production issues and a new system roll-out are natural candidates for Data Monitoring. How do we plan for pro-active data monitoring, which are not triggered by a specific event?
Relevant TIPs:
- Doing data monitoring across multiple systems
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