Enterprise Tag Manager
Data Quality & Data Governance
Avoid the cost of bad data management by ensuring qualitative and controlled data processes while complying with data governance standards.
Why do you need a strong Data Quality Monitoring?
According to Gartner, the cumulated cost of Bad Data quality amounts to 20% of income and $13 M / year for an average organization.
Those losses are due to a variety of consequences: some are direct like the wasted time and money spent to correct the discrepancies, some are seen on the long run like damaged reputation, client dissatisfaction or bad data-driven decisions.
A more insidious but lethal consequence on the growing AI-powered ecosystem of corporation might be feeding machine learning models with erroneous data: months of training wasted and bad output to repair at tremendous cost.
A university researcher pointed out that the cost of bad data correction is exponential as time passes:
- If the bad data is caught on entry: max cost is $1
- If you need to clean the data once in the system: $10
- If left unchecked: $100 or more
From the ⚛ Quantum Lounge
Manage and control your data assets while remaining compliant with regulations
Use Cases For Data Quality Monitoring
Bad data correction
A bug in your mobile app is affecting your data? No need to wait on your IT team to correct your data, it’s done in a minute with Data Cleansing.
Privacy breach monitoring
Tighter regulations require tighter controls. Our data monitoring algorithms send you alerts in case of non-compliance in personal data processing.
Manage Privacy Risks
Cookie scanner continuously monitors your cookies and provides ready to use descriptions and informations on them. Those can be used to feed a dynamic cookie notice on the website to provide the required informations to users.
Piggybacking tags are definitely an area where focus is needed for privacy compliance. Not all of it is bad but it is worrisome because of its hidden nature. Piggybacking monitoring is a useful feature to check tags dependencies and block them if needed.
PII detection is the latest addition to our privacy risks assessment features: it checks the collected variable values and alerts site owners in case a personally identifiable information might be present.
Monitor Data Quality in Real-Time
Refine your data strategy with the Live Event Inspector, a no-code solution designed to promptly identify and alert of any data discrepancies, ensuring the integrity of your data flow.
This feature offers a seamless real-time view of incoming events, whether from a specific source or across all channels. Its user-friendly interface facilitates efficient debugging, allowing for comprehensive inspection of all properties and the ability to narrow down by specific events or attributes. This accessibility makes it an invaluable asset for swiftly pinpointing and resolving data collection issues.
Enhancing its utility, the Live Event Inspector features a Debug Mode, effortlessly activated by adding a ‘test_code’ property to your events. This bypasses the intelligent sampling mechanism, guaranteeing visibility for all your test data.
Compatible with both Sources and Destinations, it provides a holistic approach to data verification, crucial for the testing phase and ensuring accurate data capture and analysis.
Take Control over your Data
In the era of AI-driven ads, not all customer data requested by platforms is necessary. Our server-side data control allows you to selectively stream data, ensuring only pertinent information is used, optimizing campaigns while protecting privacy.
Gain unparalleled control over your data; decide what to share for enhanced targeting or withhold for privacy. Our platform supports strategic, flexible data management, essential for safeguarding your valuable customer asset and complying with privacy standards.
Leverage encryption for sensitive data, reinforcing trust and compliance. Our tools allow for precise data governance, enabling advertisers to balance effective marketing with ethical data practices in a concise, secure manner.
