Data Quality Radar - More market success through consistently high data quality
Data are a company’s digital riches, allowing targeted, effective acquisition and retention of customers and thus increasing sales and market share. The decisive prerequisite is that the data are of high quality.
In practice, however, the quality of the available data often does not permit market success.
Bad data hinder the digitization process and result in greater costs.
Examples
- Important information is missing.
- Data are recorded erroneously or in duplicate.
- Data are inconsistent across different systems.
- Data are insufficiently maintained and out of date.
- It is not possible to make good business decisions based on poor, missing and/or erroneous data.
- In such cases, even the use of AI and business intelligence techniques brings no benefit to the company.
- Opportunities for cross-selling, upselling, and developing new business models are limited.
- And employees’ time is occupied with replacing the erroneous data.
Data Quality Radar
The Data Quality Radar from curexus analyses the quality of your data at regular intervals in order to ensure the success of your digitization efforts.
The Data Quality Radar enables you to regularly check your data.
You can see and measure how the actual quality of your data changes over time. Long-term developments and trends become observable.
Necessary DQ interventions can be initiated in timely fashion.
The effectiveness of DQ interventions can be checked and verified.
Better data, more sales, more profits, faster ROI for your digitization efforts
Automate the quality assurance process for your data
The Data Quality Radar (DQ Radar for short) will give you an inside look at the quality of your data pool. This will make trends and long-term developments visible and allow changes in quality to be recognized immediately. As a result, your company can make decisions quickly and avoid the need for protracted, expensive data cleansing projects.
Highly automated data quality monitoring requires very little effort and provides quickly accessible and regularly updated analysis data.
Example entity account, field name
Illustration of the quality criteria completeness, correctness and unambiguity
Illustration of the evolution of data quality over time
Individual weighting of the DQ score including traffic light system across all data fields by dimensions
Scope of Data Quality Radar services:
- Preparatory meeting to discuss objectives and procedures and to define entities
- Data screening, creation of mapping, and setting benchmarks
- Running the Data Quality Radar scan
- Creation of a report, including an initial interpretation of results
- Meeting to present and discuss results
- Results provided as PDF report
- Recommendations for measures to improve data quality
- Repeat analysis and comparison of results