We’ve created a questionnaire that draws on some of the key requirements for ISO 9001.

You can use it to benchmark your organisation’s approach to data quality and see how you compare to an approved quality standard.

Create a list of the most important data sources that are supplied to your organisation. If no data sources are received then explore the data sources flowing into your department or area of the organisation.

Examine each data source and your relationship with the supplier and assess where improvements can be made in this process.

For example:

1. How is the contract worded? Does it favour the supplier or you, the receiver?

2. Is there any mention of data quality levels or expectations within this agreement?

3. How are the data format and data quality rules specified?

4. What monitoring takes place to ensure consistent supply of good quality data? (Check whether the supplier uses any form of data quality checking).

5. Discuss with the staff that receive the data and establish whether there are ever data quality issues found with the data.

6. What reports are created – both for the technical and management community to demonstrate that a quality product is being supplied?

7. Are there any thresholds or acceptance criteria? If there are, do they meet customer needs? If there are not, what would they look like.

Data lineage is a fundamental technique that many practitioners believe must be adopted to ensure long-term data quality management. How can you trust your data or improve it at source if you don’t know its origin?

This assignment is designed to help you understand how well your organisation manages data lineage and identify where improvements can be made.

Start by examining one of your core ‘data products’ in the organisation.

This could be a data warehouse, a management report, a customer application – anything that is vital to the business and has multiple data components merging together to form a cohesive information source or function.

Next, examine the data lineage of this data back to its source.

(If the system is large and complex then take one subject area to focus on).

Trace this data source back through the earlier data suppliers and systems, making a note of each critical node and process as you go.

Use this article to help you create questions to ask stakeholders, stewards and data workers along the way:

Finally, create a presentation or report that outlines your findings. In particular, draw attention to topics such as:

• Areas of weakness in the data lineage

• Suspect processes that are known issues

• Costly manual handling of data, either to clean up or manipulate data

• Lengthy bottlenecks or performance inhibiting stages

The key to success in this project was largely attributed to transforming the cultural awareness and attitude of data quality within the workforce, particularly the unskilled data workers.

Create a survey to gauge the cultural attitude towards data quality amongst your workforce so that you can identify areas for improvement or possible training.

You can use this spreadsheet as a starting point for designing your survey.