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GL5707: PETROLEUM DATA QUALITY MANAGEMENT (2019-2020)

Last modified: 25 Sep 2019 09:58


Course Overview

The course will provide an understanding of: the value of data quality, the importance of data quality management and the consequences of poor data quality management. It will cover common data quality issues, and inherent uncertainty in data values, and demonstrate the need for data quality standards, business rules, policies and procedures, and how these are used to lead compliance activities. It will also show the relation between data governance and data quality. 

Course Details

Study Type Postgraduate Level 5
Session Second Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Robert Duncan

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The course will provide an understanding of: the value of data quality and data quality management; the consequences of poor data quality management; common data quality issues; inherent uncertainty in data values, implications for data use, tracking data quality and the importance of documenting assumptions and precision of data; the role of, value of, and need for data quality standards, business rules, policies and procedures, and how these are used to lead compliance activities; the difference between standards and rules deriving from the nature of the data, from the business purpose the data meets, how these change from country to country; monitoring, handling and reporting data quality issues; addressing data quality issues; use of business rules for loading and cleansing data and data sets; audit and assessment of business data quality processes, standards and business rules compliance; understanding of the relation between data governance and data quality. 


Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 15
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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Oral presentation

Assessment Type Summative Weighting 10
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Knowledge LevelThinking SkillOutcome
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Oral presentation

Assessment Type Summative Weighting 10
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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Reflective Report

Assessment Type Summative Weighting 10
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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Report: Group

Assessment Type Summative Weighting 25
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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Report: Group

Assessment Type Summative Weighting 30
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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Formative Assessment

There are no assessments for this course.

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualApplyExplain the key issues which can arise in data quality and data quality management
ProceduralAnalyseAnalyse business protocols and workflows to identify data quality issues, assess the impact on the business of poor data quality, and prioritize remedial actions
ProceduralCreateEvaluate data uncertainty, data provenance, & data security, and create a risk report that prioritizes remedial actions
ProceduralApplyApply compliance measures by creating robust models to demonstrate conformity with standards, business rules, and proper audit protocols
ConceptualApplyExplain the importance of dealing with data throughout the data lifecycle

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