Data KPIs
The achievement of a company's objectives and its ability to meet challenges are intimately linked to the quality of the data collected, stored and processed. The better the quality of this data, the more the company will optimize its time and make strategic decisions that are both reliable and, above all, profitable.
Companies that have realized the importance of data quality and implemented continuous improvement processes are seeing revenue growth of 15-20% thanks to "intelligent" decision-making. Conversely, it has been estimated that in 2016, US companies lost more than $3 billion as a result of decisions based on poor-quality data.
Improvement processes must integrate data quality monitoring, optimization solutions for incoming data (collection format, standardization, integrity, security, etc.) and specific processing in line with internal uses.
To assess the level of data quality, companies base themselves on seven characteristics.
It's important to understand that maintaining and improving the quality of your data is an ongoing process within your company. The implementation of Data Quality Management solutions necessarily has an upward impact on this level of quality throughout the data lifecycle. It's important to choose the right DQM solutions for your needs and expected quality objectives.
In addition to these key data quality evaluation features, Data Enso has introduced other indicators that provide additional insight into the use of our DQM solutions and the availability of our services.
When we set up our partnership, all these activity monitoring criteria are accessible in your My Data Enso space:
- Number of data items submitted for validation
- Response rate for our solutions
- Data validation rate ("ok" status)
- Corporate enrichment rate
- Average response time
- Service availability: server, website, solution APIs