Data punctuality
Characteristic Name: | Data punctuality |
Dimension: | Availability and Accessability |
Description: | Data should be available at the time of its intended use |
Granularity: | Information object |
Implementation Type: | Process-based approach |
Characteristic Type: | Usage |
Verification Metric:
The number of tasks failed or under performed due to lack of data punctuality |
The number of complaints received due to lack of data punctuality |
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
Guidelines: | Scenario: |
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Standardise the timelines for the availability of information for a particular task | (1) Investment product pricing data is often provided by third-party vendors. As the success of the business depends on accessibility to that pricing data, service levels specifying how quickly the data must be provided are defined and compliance with those timeliness constraints. |
Create efficient processes for information delivery by removing the bottlenecks in information flow | (1) Billing details of a patient is gathered two hours before discharging the patient |
Validation Metric:
How mature is the process of ensuring data punctuality |
These are examples of how the characteristic might occur in a database.
Example: | Source: |
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1) For example, the best and easiest method to obtain demographic information may be to obtain it from an existing system. Another method may be to assign data collection by the expertise of each team member. For example, the admission staff collects demographic data, the nursing staff collects symptoms, and the HIM staff assigns codes. Team members should be assigned accordingly.
2) For example, patient census is needed daily to provide sufficient day-to-day operations staffing, such as nursing and food service. How- ever, annual or monthly patient census data are needed for the facilityís strategic planning. |
B. Cassidy, et al., “Practice Brief: Data Quality Management Model” in Journal of AHIMA, 1998, 69(6). |
The Definitions are examples of the characteristic that appear in the sources provided.
Definition: | Source: |
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1) The characteristic of getting or having the Information when needed by a process or Knowledge Worker.
2) The Characteristic of the Information being accessible when it is needed. |
ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. |
Is the information processed and delivered rapidly without delays? | EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |
Timeliness refers to the time expectation for accessibility and availability of information. Timeliness can be measured as the time between when information is expected and when it is readily available for use. For example, in the financial industry, investment product pricing data is often provided by third-party vendors. As the success of the business depends on accessibility to that pricing data, service levels specifying how quickly the data must be provided can be defined and compliance with those timeliness constraints can be measured. | LOSHIN, D. 2006. Monitoring Data quality Performance using Data Quality Metrics. Informatica Corporation. |
Timeliness reflects the length of time between availability and the event or phenomenon described. Punctuality refers to the time lag between the release date of data and the target date when it should have been delivered. | LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf. |
Data maintenance
Characteristic Name: | Data maintenance |
Dimension: | Availability and Accessability |
Description: | Data should be accessible to perform necessary updates and maintenance operations in it’s entirely |
Granularity: | Record |
Implementation Type: | Process-based approach |
Characteristic Type: | Usage |
Verification Metric:
The number of tasks failed or under performed due to lack of data maintenance |
The number of complaints received due to lack of continuity in data access |
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
Guidelines: | Scenario: |
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Technological changes in the infrastructure/system should be handled in such a way that they should not make data inaccessible | (1) Sales order is created once a customer signs a contract. Then it is updated in three instances 1)Delivery date and shipment date is updated once the production plan is created. 2) Actual quantity is updated once the manufacturing is complete 3) Total cost is updated once the freight changes are incurred. A sales order is achieved after one years from delivery. |
A maintenance policy for mission critical data should be developed and implemented to handle on going systematic updates (Create, read, update, delete, archive and cleanse) | (1) Customer data : Created when a customer enters into a contract, updated once the customer details change or contact change, archived once the contact end |
When multiple versions of the same data is available through different datasets\databases create a master record and make it available across the systems | (1) Master data management |
Leverage application and storage technology in such a way that the maintenance policies can be applied on data | (1)Addresses which were not updated during the last 24 months are prompted for validations |
Create a responsibility structure/Authorisation structure and a communication structure to manage the process of information generation maintenance and utilisation | (1) It is the responsibility of the work study team to provide SMV (standard minute values) for a garment. (2) Approved SMVs should be sent to the planning department for planning purposes. |
Validation Metric:
How mature is the data maintenance process |
These are examples of how the characteristic might occur in a database.
Example: | Source: |
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minutes of a meeting will be produced in draft form and reviewed by the members of the committee before being approved. Once this process of creation is finished the record must be fixed and must not be susceptible to change. If a record is changed or manipulated in some way, it no longer provides evidence of the transaction it originally documented. For example, if someone alters the minutes of a meeting after they have been approved, the minutes can no longer be considered an accurate record of the meeting. This is another issue that becomes more important in an electronic context. | K. Smith, “Public Sector Records Management: A Practical Guide”, Ashgate, 2007. |
The Definitions are examples of the characteristic that appear in the sources provided.
Definition: | Source: |
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A measure of the degree to which data can be accessed and used and the degree to which data can be updated, maintained, and managed. | D. McGilvray, “Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information”, Morgan Kaufmann Publishers, 2008. |
Can all of the information be organized and updated on an on-going basis? | EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |