Completeness of records
| Characteristic Name: | Completeness of records |
| Dimension: | Completeness |
| Description: | Every real world entity instance, that is relevant for the organization can be found in the data |
| Granularity: | Record |
| Implementation Type: | Process-based approach |
| Characteristic Type: | Usage |
Verification Metric:
| The number of tasks failed or under performed due to missing records |
| The number of complaints received due to missing records |
GuidelinesExamplesDefinitons
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Implement a process level validation mechanism to avoid occurrence of missing records | (1) A buyer must record/verify an expense or asset in accordance with accepting/receiving any purchased items. (2)New application are stored in a temporary cabinet after entering into the system and they will be transferred to the file cabinet at the end of every week after the property manager cross check them with the system |
| Execute database commits upon transaction sequences in application programs and make sure all the transactions in the sequence successfully commit and generate the required records at the end of the sequence. | (1) In generating the MRP, the database operations will not be committed unless all materials in BOM is successfully executed for MRP |
| When distributed databases are used or online data collection devices are used, ensure the synchronisation/replication of records happen successfully without distortions and omissions. | (1) EFTPOS transactions are replicated with bank database and create the new balance B/F in the account |
| Implement periodic audit process for critical tangible objects that are recorded as data in database | (1) Annual audit for tangible assets in the organisation |
| Implement a validation mechanism in data transfers considering the business rules to monitor and ensure all records relevant to a event/transaction is transferred successfully. | (1) Rules to verify the number of records in the source file and destination file (2) All records relevant to a customer trip is transferred to the central database from online data stores |
| Maintain error logs for system transactions and regularly monitor them and perform relevant forensic activities to find missing records. | (1) A failed sales order creation |
Validation Metric:
| How mature is the process to prevent missing records |
These are examples of how the characteristic might occur in a database.
| Example: | Source: |
|---|---|
| if Dept is a relation representing the employees of a given department, and one specific employee of the department is not represented as a tuple of Dept, then the tuple corresponding to the missing employee is in ref(Dept),and ref(Dept) differs from Dept in exactly that tuple. | C. Batini and M, Scannapieco, “Data Quality: Concepts, Methodologies, and Techniques”, Springer, 2006. |
| if a column should contain at least one occurrence of all 50 states, but the column contains only 43 states, then the population is incomplete. | Y. Lee, et al., “Journey to Data Quality”, Massachusetts Institute of Technology, 2006. |
| the database should contain all customers in North and South America, but it is known that the database reflects only a portion of the company’s customers. Coverage in this example is the percent- age of customers actually captured in the database compared to the population of all customers that should be in it. | D. McGilvray, “Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information”, Morgan Kaufmann Publishers, 2008. |
The Definitions are examples of the characteristic that appear in the sources provided.
| Definition: | Source: |
|---|---|
| A record exists for every Real-World Object or Event the Enterprise needs to know about. | ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. |
| Completeness of data refers to the extent to which the data collected matches the data set that was developed to describe a specific entity. Monitoring for incomplete lists of eligible records or missing data items will identify data quality problems. | HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality. |
| Quality of having all data that existed in the possession of the sender at time the data message was created. | ISO 2012. ISO 8000-2 Data Quality-Part 2-Vocabulary. ISO. |
| Data is complete if no piece of information is missing – anti-example: "The Beatles were John Lennon, George Harrison and Ringo Starr" | KIMBALL, R. & CASERTA, J. 2004. The data warehouse ETL toolkit: practical techniques for extracting. Cleaning, Conforming, and Delivering, Digitized Format, originally published. |
| Every real-world phenomenon is represented. | PRICE, R. J. & SHANKS, G. Empirical refinement of a semiotic information quality framework. System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on, 2005. IEEE, 216a-216a. |
Usefulness and relevance
| Characteristic Name: | Usefulness and relevance |
| Dimension: | Usability and Interpretability |
| Description: | The data is useful and relevant for the task at hand |
| Granularity: | Information object |
| Implementation Type: | Process-based approach |
| Characteristic Type: | Usage |
Verification Metric:
| The number of tasks failed or under performed due to the lack of usefulness and relevance of data |
| The number of complaints received due to the lack of usefulness and relevance of data |
GuidelinesExamplesDefinitons
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Define the content of the information object based on the user requirements (as required by the task at hand) and also considering all other compliance requirements so that the information is relevant and legitimate | (1) Customer invoice should contain information for the customer to understand his liability and for the delivery person to understand the point of delivery and the tax department to verify the applicable tax amount. |
| Regularly monitor the changes to the internal operational environment ( business process changes etc) and find out what are the new information requirements emerge due to the changes, and provide for them by amending the information structures | (1) Time stamp became an important attribute for GRNs (goods receipts notes) when Lean manufacturing started as all raw materials are expected to receive by six hours before production (GRN-record, and the time stamp -attribute) |
| Regularly monitor the changes in the external environment find out the new information requirements emerge due to such changes and provide for such data needs | (1) Competitors' rates have become important to price the existing products during the recession period since the traditional costing method does not give a competitive price. |
| Regularly check with knowledge workers to find out how their operations/decisions can be performed better with new data available to them and provide for such data in the information system | (1) An hourly working progress report is useful in identifying the bottlenecks in production lines and balance the lines |
| Monitor and measure the user satisfaction about the information provided | (1) User satisfaction survey |
Validation Metric:
| How mature is the process to maintain usefulness and relevance of data |
These are examples of how the characteristic might occur in a database.
The Definitions are examples of the characteristic that appear in the sources provided.
| Definition: | Source: |
|---|---|
| 1) The Characteristic in which the Information is the right kind of Information that adds value to the task at hand, such as to perform a process or make a decision.
2) Knowledge Workers have all the Facts they need to perform their processes or make their decisions. |
ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. |
| 1) Can the information process be adapted by the information consumer?
2)Can the information be directly applied? Is it useful? 3) Does the information provision correspond to the user’s needs and habits? |
EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |
| Relevance of data refers to the extent to which the data meets the needs of users. Information needs may change and is important that reviews take place to ensure data collected is still relevant for decision makers. | HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality. |
| Relevance is the degree to which statistics meet current and potential users’ needs. It refers to whether all statistics that are needed are produced and the extent to which concepts used (definitions, classifications etc.) | LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf. |
| The data includes all of the types of information important for its use. | PRICE, R. J. & SHANKS, G. Empirical refinement of a semiotic information quality framework. System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on, 2005. IEEE, 216a-216a. |
| 1) Intrinsic: The extent to which the information is new or informative in the context of a particular activity or community.
2) Relational Contextual:The amount of information contained in an information object. At the content level, it is measured as a ratio of the size of the informative content (measured in word terms that are stemmed and stopped) to the overall size of an information object. At the schema number of elements in the object level it is measured as a ratio of the number of unique elements over the total. 3) The extent to which information is applicable in a given activity. 4) The extent to which the model or schema and content of an information object are expressed by conventional, typified terms and forms according to some general-purpose reference source. |
STVILIA, B., GASSER, L., TWIDALE, M. B. & SMITH, L. C. 2007. A framework for information quality assessment. Journal of the American Society for Information Science and Technology, 58, 1720-1733. |
| 1) Data are applicable and useful for the task at hand.
2) The quantity or volume of available data is appropriate. 3) Data are of sufficient depth, breath and scope for the task at hand. |
WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33. |