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.
Monte Carlo supports the data mesh principles critical for a successful implementation in your organization:
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.
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.
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.
Data product documentation
Monte Carlo automates data contextualization (e.g., lineage, usage, hierarchy) and enables documentation of data, including ownership and searchable tags.
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.
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.
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.
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.
