InfoZoom Data Quality (IZDQ) – your way to sustainable clean data
Data quality is a continuous process. It is not sufficient to clean the data just once. With IZDQ, you can monitor the quality of your data continuously and automatically. This function is based on a highly flexible and demand-oriented set of rules that automatically detects errors. You can then rectify these errors without much effort.
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Data Quality Management with InfoZoom: Finally understand the complete data basis at one glance
Data are the basis for analyses and processes and therefore also for the company’s success. Poor data quality leads to disturbances in the workflow and to serious consequences.
IZDQ loop for continuous data quality management
The loop allows you to monitor your data continuously, automatically and 24/7. As the recording of data quality documents the improvements, you can control and monitor the actions taken over time.
Always the right decisions – high data quality as competitive edge
The decisions you make are closely related to the quality of your data. With IZDQ you promote data quality management throughout your company. If all your master data and transaction data are correct, this secures your competitiveness and paves the way for Big Data.
Bad data quality is expensive:
minimize risks with IZDQ
Poor data quality has a lot of negative consequences, which can lead to lasting damage and can become very expensive. You minimize these risks by monitoring and improving data quality with IZDQ.
Optimize your processes –
conveniently solve quality issues
With IZDQ, you integrate data quality management into your employee’s everyday work cost and time-efficiently. The reports generated are sent to the specialists responsible so that they can rectify errors immediately and without much effort. By detecting and eliminating errors at an early stage, you avoid subsequent errors and ill-founded decisions. With IZDQ, you control your company’s DQ strategy.
As fast as that:
ready to use in just one day
Usually only one day is needed to instruct users in the operation of IZDQ. The users will then be capable of developing the set of rules and workflows on their own. If required, our experts can help you design new rules.
What can we do for you? Consulting – let’s investigate your data together.
You want to get an impression of your data basis? You’re about to launch a DQ project? There’s a bit of a problem somewhere? Practice makes perfect – our experienced consulting team will be happy to support you in any phase of your data project.
A simple example:
missing customer e-mail addresses
missing customer e-mail addresses
You’re planning to launch an e-mail campaign for existing customers. Right before the launch, you suddenly realize that no e-mail addresses have been stored for 60% of them! This wouldn’t have happened with IZDQ! Based on a freely adjustable set of rules, IZDQ detects incorrect or missing records automatically and creates error reports. You can then send these reports to account managers asking them to enter the missing e-mail addresses.
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