Data mesh & self-serve data

Data mesh & self-serve data

Deliver the data quality and integrity required to support data mesh and self-serve ownership of trustworthy data products.

The self-service capabilities of data observability helped build back trust in data. They knew who was accountable, they knew the teams were working on it, and everything became crystal clear.

Gopi Krishnamurthy, Director of Engineering

Monte Carlo supports the data mesh principles critical for a successful implementation in your organization:

Domain-driven ownership Data as a product Self-serve data platform Federated governance

Domain-driven ownership

Establish domains and domain owners, and equip them with the ability to detect, resolve, and prevent data incidents.

Domain definition & ownership

Leverage MC’s flexible domain definition to establish domains that map to your data sources and consumers with a few clicks or via API.

See API documentation
Domain definition & ownership

Reliable data across every domain

With Monte Carlo’s data observability platform, domain data producers are equipped to detect and resolve data incidents and anomalies as soon as they occur, and prevent bad data altogether.

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Reliable data across every domain

Data as a product

Build trustworthy and reliable products, allow them to be discovered, and establish reliability standards with Monte Carlo.

Service level objectives and indicators

Establish service level objectives (SLOs) and service level indicators (SLIs) for the quality of your data products based on data incidents and anomalies automatically detected by Monte Carlo.

Learn how
Service level objectives and indicators

Data product documentation

Monte Carlo automates data contextualization (e.g., lineage, usage, hierarchy) and enables documentation of data, including ownership and searchable tags.

How to build data products
Data product documentation

Self-serve data platform

Monte Carlo equips domain owners with end-to-end data observability across the central data infrastructure.

Unified data observability platform

Monte Carlo unifies monitoring, metadata, analytics, and collaboration in a platform that allows data teams to detect, resolve, and prevent data incidents.

See it in action
Unified data observability platform

Automated machine learning

Monte Carlo’s ML-powered monitors help drive adoption across data producer and engineering teams by reducing the effort to produce high quality and reliable data at scale.

Review available monitors
Automated machine learning

Federated governance

Monte Carlo provides teams with global and local visibility to support a federated governance model.

Standardized data quality

Monte Carlo’s data observability platform provides company and domain-level visibility into data quality metrics and SLO adherence.

Learn how
Standardized data quality

End-to-end lineage

Monte Carlo helps domain teams understand upstream sources and downstream impact of data issues, and empowers better data discovery for teams across the organization.

Check out our docs
End-to-end lineage

Implementing data mesh?

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