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Data catastrophes happen.
Your team can now anticipate them and scale up.

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Datastrophes happen. Often.

Structural changes, missing values, old data, inefficient AI models, migration of sources ... Data catastrophes - also known as "datastrophes" - can drastically impact the efficiency of your work and the confidence in your data projects' outcomes.

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Inefficient
scalability

How can your data usage scale if its quality cannot be guaranteed?

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Waste
of resources

How can you justify large investments in data if it may not be reliable?

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Poor
collaboration

How can teams work together efficiently if data keeps breaking along the chain?

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Lack
of confidence

How can you make the right decisions if you can’t fully trust your data?

What about observability?

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Data and analytics observability is about real-time tracking and measuring of your data usage performance across systems, projects and applications.

Simultaneously, it can enrich your data management ecosystem by sharing lineages, schemas and quality information with data catalogs, glossaries and incident management systems.

Observability is for everyone

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For Data Scientists

Remain confident about the models in production by being notified as soon as performance is deviating.

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For Heads of Data

Increase the productivity of your team by reducing the resources required to maintain existing data applications.

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For Data Engineers

Save time and trouble by easily increasing your visibility and control over data in production.

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For Analysts

Increase your trust in existing reports by being  immediately alerted as soon as data quality is out of range.

We've got your back

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Security

Because security matters to us and to our clients, we are SOC 2 compliant.

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On-premise

We provide an on-premise solution for corporations with specific needs.

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Cloud

You can benefit from all our features with a highly secured cloud solution.

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Trust what you deliver.