Data Management
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data_quality_management_system:critical_data_element
Critical data element
Definition
A critical data element is a data element that is determined to be vital to the successful operation of the organization (Loshin, 2009).
Abbreviaton
CDE
Notes
- For example, an organization may define its critical data elements as those that represent protected personal information, those that are used in financial reports (both internal and external), regulatory reports, the data elements that represent identifying information of master data, the elements that are critical for a decision-making process, or the elements that are used for measuring organizational performance.
- The Factor Rating Method is method for deciding between two or more data elements.
- The Factor Rating Matrix is the output of the Factor Rating Method.
Purpose
The purpose of critical data elements is to prioritize efforts to improve and ensure the quality of the most valuable data in the organization.
Lifecycle
- Select a critical data element
- Deselect a critical data element
| Phase | Activity |
|---|---|
| Plan | * Determine the scope of the selection procedure. * Collect the data elements within the scope. * Select a method to determine the critical data elements. * Select or deselect critical data elements by the method. * Establish the critical data elements. |
| Do | * Use the critical data elements as input for actions to improve and assure the quality of the critical data elements. |
| Check | * Evaluate the set of critical data elements. |
| Act | * Decide whether the set of critical data elements should be amended. |
Characteristics
| Characteristic | Requirement |
|---|---|
| Criticality of a data element | A critical data element is a data element that exceeds a threshold for criticality. |
| Completeness of the set of critical data elements | The set of critical data elements]] is complete within the scope of the management system. |
| Actuality of the set of critical data elements | The set of critical data elements is up to date, e.g., it is not ten years old. |
Relations
| Critical data element | is child of | data element |
| Critical data element | is an element of a | data quality management system |
| Critical data element | are established based on the | data quality policy |
| Critical data element | are established based on the | stakeholder analysis |
| Critical data element | are established based on the | data quality objective |
| Critical data element | are input for the procedure to manage | data quality rules |
| Critical data element | are input for the procedure to manage | data cleansing |
| Critical data element | are included in | data lineage |
| Critical data element | are subject to | data quality monitoring |
Methods to select critical data elements
Method 1: Simple method
The simplest method to select the critical data elements is that the data owner selects and establishes the critical data elements.
Method 2: Factor Rating Method
The Factor Rating Method is a method the select critical data elements in more objective way and is appropriate when more stakeholders have a say in the selection.
The next procedure is followed:
- Determine the factors for selection the critical data elements.
- Determine the weight of each factor.
- Determine the rating classification (levels of criticality).
- Determine the algorithm to calculate the score (Score = Weight x Rate).
- Determine the criticality threshold for the score.
- Rate each combination of data element and factor.
- Calculate the scores.
- Compare the scores with the threshold.
- Select the critical data elements.
- Document the factor rating matrix.
Table 1: Factors for selection of critical data elements
| Label | Factor for selection a data element | Weight |
|---|---|---|
| Regulatory | Is used for regulatory reporting. | 3 |
| Compliance | Contributes to compliance to laws and regulations | 3 |
| Accounting | Is used for financial/management accounting | 2 |
| Operational | Has impact on the operational process and the quality of the product or service. | 1 |
Table 2: Rating classification
| Rate | Description |
|---|---|
| 0 | No impact |
| 1 | Low impact |
| 2 | Medium impact |
| 3 | High impact |
Table 3: Factor Rating Matrix
| Data element | Factor and Weight | Score | Critical data element? >10 |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Regulatory Weight: 3 | Compliance Weight: 3 | Accounting Weight: 2 | Operation Weight: 1 |
|||||||
| Rate | Score | Rate | Score | Rate | Score | Rate | Score | |||
| Customer number | 3 | 9 | 3 | 9 | 3 | 6 | 2 | 2 | 26 | Yes |
| Birth date | 3 | 9 | 3 | 9 | 0 | 0 | 3 | 3 | 19 | Yes |
| Acceptance status | 3 | 9 | 3 | 9 | 3 | 6 | 3 | 3 | 27 | Yes |
| Mobile phone | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | No |
| Gender | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 2 | 1 | No |
Threshold is 10.
Story
The customer database of telephone company CallMe is contaminated. This resulted in customer dissatisfaction and avoidable bill disputes, causing extra workload for Client Services. Efforts to clean up the database failed because of the amount of work involved. The owner of the database then decided to select data elements that matter. He invited a few key players (stakeholders) to determine which data elements these would be. They all agreed that the name of the customer was the most important data element (critical data element). This selection was also fully in line with the data quality policy and data quality objectives.
The owner of the database then first tightened the data quality rules around names, to prevent further contamination. Furthermore, he hired a name specialist to clean up the names automatically where possible and, where necessary, to approach customers personally to ask for their correct name. This action was highly appreciated by customers because they felt seen by CallMe. It has also helped its own organization to realize improvements in data and a reduction of the workload.
References
DAMA (2017). DAMA-DMBOK. Data Management Body of Knowledge. 2nd Edition. Technics Publications Llc. August 2017.
DAMA Dictionary of Data Management. 2nd Edition 2011. Technics Publications, LLC, New Jersey.
ISO/IEC 11179-1:2015(en), Information technology — Metadata registries (MDR) — Part 1: Framework
Loshin, David (2009). Master Data Management. The MK/OMG Press.
Critical Data Element (2023). YouTube video. DAMA-NL.
data_quality_management_system/critical_data_element.txt · Last modified: 2024/03/08 13:33 (external edit)