Ease of data access
| Characteristic Name: | Ease of data access |
| Dimension: | Availability and Accessability |
| Description: | Data should be easily accessible in a form that is suitable for 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 ease in data access |
| The number of complaints received due to lack of ease in data access |
GuidelinesExamplesDefinitons
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Routinely accessed information to continue operations, should be automatically delivered to stakeholders online without wasting their time to search for it. | (1) Daily exchange rates are linked into the accounting application or maintained in a dash board on the accountants desktop.
(2) Production efficiency is made available on a display board in the production floor. |
| Information needed for management reporting purposes should be identified and catered through built in reports where the users do not have to create the reports themselves. | (1) Order status is frequently searched information by different stake holder groups and hence a report is made available with multiple searching criteria. |
| Facilitate users by providing tools to query the database without using any specific technical knowledge and perform business analytics to bring innovation | (1) Technical infrastructure supports the users to develop their own reports based on dynamic information needs without consulting technical staff. |
| Facilitate the user to filter the relevant information depending on the need. | (1) Sales report with filtering criteria for customer and date range. |
| The interfaces and reports should be created conveniently the users do not have to write complex queries or further process information before usage. | (1) Product prices are ordered as per "Relevance" or "Price" to enable an e-commerce customer on a purchase decision |
Validation Metric:
| How mature is the process of maintaining ease in data access |
These are examples of how the characteristic might occur in a database.
| Example: | Source: |
|---|---|
| Consider a database containing orders from customers. A practice for handling complaints and returns is to create an “adjustment” order for backing out the original order and then writing a new order for the corrected information if applicable. This procedure assigns new order numbers to the adjustment and replacement orders. For the accounting department, this is a high-quality database. All of the numbers come out in the wash. For a business analyst trying to determine trends in growth of orders by region, this is a poor-quality database. If the business analyst assumes that each order number represents a distinct order, his analysis will be all wrong. Someone needs to explain the practice and the methods necessary to unravel the data to get to the real numbers (if that is even possible after the fact). | J. E. Olson, “Data Quality: The Accuracy Dimension”, Morgan Kaufmann Publishers, 9 January 2003. |
The Definitions are examples of the characteristic that appear in the sources provided.
| Definition: | Source: |
|---|---|
| Accessibility refers to the physical conditions in which users can obtain data Clarity refers to the data’s information environment including appropriate metadata. | LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf. |
| Speed and ease of locating and obtaining an information object relative to a particular activity | 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. |
| Data are available or easily or quickly retrieved. | WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33. |
Continuity of data access
| Characteristic Name: | Continuity of data access |
| Dimension: | Availability and Accessability |
| Description: | The technology infrastructure should not prohibit the speed and continuity of access to the data for the users |
| Granularity: | Information object |
| Implementation Type: | Process-bases approacd |
| Characteristic Type: | Usage |
Verification Metric:
| The number of tasks failed or under performed due to the lack of continuity in data access |
| The number of complaints received due to lack of continuity in data access |
GuidelinesExamplesDefinitons
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Convenient and efficient platform should be made available to access data depending on the task at hand | (1) For a sales person, a web based interface run on a smart device is more suitable to quickly access data |
| Speed of the data retrieval should be acceptable for users working pace | (1) For an online customer care executive, speedy retrieval of information is necessary since the customer cannot be kept waiting (2) With the growth of the database reports become slower (Anti example) |
| Continuous and unobstructed connectivity should be ensured for data retrievals | (1) Connection lost while accessing reports (Anti example) |
| Proper concurrency control has been implemented | (1) Controlling access to data by locks |
| Technological changes in the infrastructure/system should be handled in such a way that they should not make data inaccessible | (1) New version of the software does not provide access to " X out orders" since the new version does not allow the function "X out" |
Validation Metric:
| How mature is the process of maintaining an infrastructure for data access |
These are examples of how the characteristic might occur in a database.
| Example: | Source: |
|---|---|
| 1) For example, recording the age and race in medical records may be appropriate.
However, it may be illegal to collect this information in human resources departments. 2) 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. |
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: |
|---|---|
| 1) Is there a continuous and unobstructed way to get to the information?
2) Can the infrastructure match the user’s working pace? |
EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |
| Data is easy and quick to retrieve. | 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) availability of a data source or a system.
2) Accessibility expresses how much data are available or quickly retrievable. 3) The frequency of failures of a system, its fault tolerance. |
SCANNAPIECO, M. & CATARCI, T. 2002. Data quality under a computer science perspective. Archivi & Computer, 2, 1-15. |