Data Quality Management - Revision history

Tkokotas at 17:14, 16 November 2018

2018-11-16T17:14:59Z

← Older revision		Revision as of 17:14, 16 November 2018
Line 1:		Line 1:
			''Developed by Oliver Adam Mølskov Bech''


	==Abstract==		==Abstract==

Oliver.amb: /* Limitations and Difficulties of DQM */

2018-03-04T20:42:11Z

Limitations and Difficulties of DQM

← Older revision		Revision as of 20:42, 4 March 2018
Line 108:		Line 108:
	*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.		*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.
	*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.		*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.
	*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps the: initiating, planning, executing, controlling and closing (IPECC) scheme highlighted in PMBOK® could be used to formulate a superior framework as it also helps define procedures for initiating and closing of a process.		*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps the: initiating, planning, executing, controlling and closing (IPECC) scheme highlighted in PMBOK® could be used to formulate a superior framework in the future as it also helps define procedures for initiating and closing of a process.

	==Abbreviations==		==Abbreviations==

Oliver.amb: /* Abbreviations */

2018-03-04T20:41:33Z

Abbreviations

← Older revision		Revision as of 20:41, 4 March 2018
Line 112:		Line 112:
	==Abbreviations==		==Abbreviations==
	*'''DQM:''' Data Quality Management		*'''DQM:''' Data Quality Management
			*'''IPECC:''' Initiating-Planning-Executing-Controlling-Closing
	*'''ISO:''' International Organisation for Standardization		*'''ISO:''' International Organisation for Standardization
	*'''PDCA:''' Plan-Do-Check-Act		*'''PDCA:''' Plan-Do-Check-Act

Oliver.amb: /* Limitations and Difficulties of DQM */

2018-03-04T20:40:14Z

Limitations and Difficulties of DQM

← Older revision		Revision as of 20:40, 4 March 2018
Line 108:		Line 108:
	*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.		*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.
	*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.		*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.
	*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps ~~a cycle such as~~ the: initiating, planning, executing, controlling and closing (IPECC) ~~cycle~~ highlighted in PMBOK® ~~under project quality management would~~ be a superior framework as it also helps define procedures for initiating and closing of a process.		*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps the: initiating, planning, executing, controlling and closing (IPECC) scheme highlighted in PMBOK® could be used to formulate a superior framework as it also helps define procedures for initiating and closing of a process.

	==Abbreviations==		==Abbreviations==

Oliver.amb: /* Limitations and Difficulties of DQM */

2018-03-04T20:38:42Z

Limitations and Difficulties of DQM

← Older revision		Revision as of 20:38, 4 March 2018
Line 108:		Line 108:
	*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.		*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.
	*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.		*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.
	*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps a cycle such as the: initiating, planning, executing, controlling and closing (IPECC) cycle highlighted in ~~PMBOK~~ under project quality management would be a superior framework as it also helps define procedures for initiating and closing of a process.		*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps a cycle such as the: initiating, planning, executing, controlling and closing (IPECC) cycle highlighted in PMBOK® under project quality management would be a superior framework as it also helps define procedures for initiating and closing of a process.

	==Abbreviations==		==Abbreviations==

Oliver.amb: /* Bibliography */

2018-03-04T20:37:59Z

Bibliography

← Older revision		Revision as of 20:37, 4 March 2018
Line 128:		Line 128:
	'''Knowledgent. (2014): ''Building a Successful DQM Program''. Knowledgent White Paper Series.''' This paper provides an introduction to DQM within enterprise information management, explaining the basic concepts behind DQM and also explaining the data quality cycle framework.		'''Knowledgent. (2014): ''Building a Successful DQM Program''. Knowledgent White Paper Series.''' This paper provides an introduction to DQM within enterprise information management, explaining the basic concepts behind DQM and also explaining the data quality cycle framework.

	'''PMI. (2013): ''A Guide to the Project Management Body of Knowledge (PMBOK® Guide)'', 5th ed. Pennsylvania USA.''' The PMBOK® guide provides a wealth of knowledge regarding the different knowledge bodies of project management~~. In this article, the guide was particularly useful in identifying and understanding how data quality may influence different project management areas~~. This article references chapter 8 of the PMBOK®: project quality management.		'''PMI. (2013): ''A Guide to the Project Management Body of Knowledge (PMBOK® Guide)'', 5th ed. Pennsylvania USA.''' The PMBOK® guide provides a wealth of knowledge regarding the different knowledge bodies of project management. This article references chapter 8 of the PMBOK®: project quality management.

	'''Shanks, G. and Darke, P. (1998): ''Understanding Data Quality in a Data Warehouse: A Semiotic Approach''. Massachusetts USA: University of Massachusetts Lowell, pg. 292-309.''' This paper provided an overview of data quality measures using a semiotic approach, explaining each semiotic level and how they are interlinked to data quality. The semiotic theory discussed is similar to the one later adopted by the ISO 8000-8 standard for data quality.		'''Shanks, G. and Darke, P. (1998): ''Understanding Data Quality in a Data Warehouse: A Semiotic Approach''. Massachusetts USA: University of Massachusetts Lowell, pg. 292-309.''' This paper provided an overview of data quality measures using a semiotic approach, explaining each semiotic level and how they are interlinked to data quality. The semiotic theory discussed is similar to the one later adopted by the ISO 8000-8 standard for data quality.

Oliver.amb: /* Resource Provision Process */

2018-03-04T20:36:46Z

Resource Provision Process

← Older revision		Revision as of 20:36, 4 March 2018
Line 98:		Line 98:

	This process is divided into two sub-processes which are: data quality organisation management and human resource management. This process allows the entire DQM process to function, providing input to the two other overarching processes. This process involves providing the necessary resources and management required for both data-related support and implementation to function. Data quality organisation management involves establishing the organisational structure of DQM process. This entails allocating roles, responsibilities, and giving authority for the execution of tasks. Human resource management in the DQM process involves training individuals to perform the required data quality tasks. This entails developing the knowledge and skills of the individuals within the organisation in regard to the DQM process<ref>Pg. 17, 2015 ed. ISO 8000-61: Data quality management: Process reference model, ISO</ref>.		This process is divided into two sub-processes which are: data quality organisation management and human resource management. This process allows the entire DQM process to function, providing input to the two other overarching processes. This process involves providing the necessary resources and management required for both data-related support and implementation to function. Data quality organisation management involves establishing the organisational structure of DQM process. This entails allocating roles, responsibilities, and giving authority for the execution of tasks. Human resource management in the DQM process involves training individuals to perform the required data quality tasks. This entails developing the knowledge and skills of the individuals within the organisation in regard to the DQM process<ref>Pg. 17, 2015 ed. ISO 8000-61: Data quality management: Process reference model, ISO</ref>.

	~~A detailed explanation of each process and sub-process of the DQM framework can be accessed via the ISO 8000-61 standard.~~

	==Limitations and Difficulties of DQM==		==Limitations and Difficulties of DQM==

Oliver.amb: /* DQM within Project Quality Management */

2018-03-04T20:35:13Z

DQM within Project Quality Management

← Older revision		Revision as of 20:35, 4 March 2018
Line 22:		Line 22:
	*'''Control Quality:''' monitoring process involving control activities related to quality performance. Includes providing future recommendations to improve quality based on findings from monitoring activities, i.e. striving for continuous improvement.		*'''Control Quality:''' monitoring process involving control activities related to quality performance. Includes providing future recommendations to improve quality based on findings from monitoring activities, i.e. striving for continuous improvement.

	The guidelines for project quality management as described in PMBOK® is designed to be compatible with ISO standards<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>. The DQM framework described in this article is based off the 8000-61 ISO guidelines and as such there are many parallels which allow for this DQM process to be compatible and function as a tool to support the overarching project quality management processes. Parallels in ISO compatibility between the DQM process and the project quality management processes include concepts such as continuous improvement using plan-do-check-act (PDCA) cycles<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>. As stated by PMBOK®, every project should ideally include and follow a plan for quality management, and such a plan should also include data support compliance for quality requirements<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>.		The guidelines for project quality management as described in PMBOK® is designed to be compatible with ISO standards<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>. The DQM framework described in this article is based off the 8000-61 ISO guidelines and as such there are many parallels which allow for this DQM process to be compatible and function as a tool to support the overarching project quality management processes. Parallels in ISO compatibility between the DQM process and the project quality management processes include concepts such as continuous improvement using plan-do-check-act (PDCA) cycles<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>. As stated by PMBOK®, every project should ideally include and follow a plan for quality management, and such a plan should also include data to support compliance for quality requirements<ref>Chapter 8. 2013 ed. A Guide to Project Management Body of Knowledge (PMBOK®): Project Quality Management. ed 5. PMI</ref>.

	===Data Quality===		===Data Quality===

Oliver.amb: /* Abbreviations */

2018-03-04T20:33:35Z

Abbreviations

← Older revision		Revision as of 20:33, 4 March 2018
Line 113:		Line 113:

	==Abbreviations==		==Abbreviations==
	*DQM: Data Quality Management		*'''DQM:''' Data Quality Management
	*ISO: International Organisation for Standardization		*'''ISO:''' International Organisation for Standardization
	*PDCA: Plan-Do-Check-Act		*'''PDCA:''' Plan-Do-Check-Act
	*PMBOK: Project Management Body of Knowledge		*'''PMBOK:''' Project Management Body of Knowledge

	==Bibliography==		==Bibliography==

Oliver.amb: /* Limitations and Difficulties of DQM */

2018-03-04T20:32:38Z

Limitations and Difficulties of DQM

← Older revision		Revision as of 20:32, 4 March 2018
Line 105:		Line 105:
	There are a number of difficulties associated with the DQM process explained above. Some of the most prevalent limitations are described below:		There are a number of difficulties associated with the DQM process explained above. Some of the most prevalent limitations are described below:

	*Defining data quality requirements: in the implementation phase, the strategy aims to define the goals and objectives in terms of achieving sufficient data quality. However, defining the right strategy for the required data quality level can be immensely difficult due to the complexity of the term data quality. If the goals and objectives are set too high, the data quality level may be excessively high compared to the actual needs and requirements. However, if the goals for data quality are set too low, there is an increased risk that project outcomes may be adversely influenced. As mentioned earlier, the strategy must balance goals, costs and resources closely. Defining the required data quality level for the project is crucial in achieving the right balance, something that can be very difficult.		*'''Defining data quality requirements:''' in the implementation phase, the strategy aims to define the goals and objectives in terms of achieving sufficient data quality. However, defining the right strategy for the required data quality level can be immensely difficult due to the complexity of the term data quality. If the goals and objectives are set too high, the data quality level may be excessively high compared to the actual needs and requirements. However, if the goals for data quality are set too low, there is an increased risk that project outcomes may be adversely influenced. As mentioned earlier, the strategy must balance goals, costs and resources closely. Defining the required data quality level for the project is crucial in achieving the right balance, something that can be very difficult.
	*Complexity of processes: the activities involved in the DQM process can be complex and require extensive analysis and understanding of different IT systems. Complexity of the subject area can be an obstacle as it requires training and development of knowledge. In other words; it is not a simple process.		*'''Complexity of processes:''' the activities involved in the DQM process can be complex and require extensive analysis and understanding of different IT systems. Complexity of the subject area can be an obstacle as it requires training and development of knowledge. In other words; it is not a simple process.
	*Number of processes: the number of different processes and sub-processes involved in running a successful DQM process can be time and cost consuming.		*'''Number of processes:''' the number of different processes and sub-processes involved in running a successful DQM process can be time and cost consuming.
	*Obtaining resource provision: it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.		*'''Obtaining resource provision:''' it may be difficult to obtain support for the provision of the required resources for a successful DQM system. Appropriate IT systems and data specialists are required, both of which can be costly to a project or program.
	*Extensive documentation of data: the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.		*'''Extensive documentation of data:''' the DQM process requires data architecture and data transfer management that allows data to be stored systematically to ensure traceability and transparency of data. Over time, the accumulation of data can be extremely large and data warehouses can be difficult to manage as they get larger.
	*Initiation: the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps a cycle such as the: initiating, planning, executing, controlling and closing (IPECC) cycle highlighted in PMBOK under project quality management would be a superior framework as it also helps define procedures for initiating and closing of a process.		*'''Initiation:''' the PDCA cycle of the DQM process does not include an initiation phase. Without an initiation phase clearly defined, it can be difficult to kick-start a DQM process. Perhaps a cycle such as the: initiating, planning, executing, controlling and closing (IPECC) cycle highlighted in PMBOK under project quality management would be a superior framework as it also helps define procedures for initiating and closing of a process.

	==Abbreviations==		==Abbreviations==