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πŸ§‘β€πŸŽ“ Monte Carlo University

  • Getting Started | MC University
  • Detect
    • πŸ§‘β€πŸŽ“ Assets
    • πŸ§‘β€πŸŽ“ Lineage
    • πŸ§‘β€πŸŽ“ Freshness Monitor
    • πŸ§‘β€πŸŽ“ Volume Monitor
    • πŸ§‘β€πŸŽ“ Schema Monitor
    • πŸ§‘β€πŸŽ“ Metric Monitor
    • πŸ§‘β€πŸŽ“ SQL Monitors
    • πŸ§‘β€πŸŽ“ Comparison Rules
    • πŸ§‘β€πŸŽ“ Monitors as Code
    • πŸ§‘β€πŸŽ“ Validation Monitor
    • πŸ§‘β€πŸŽ“ JSON Schema Monitor
    • πŸ§‘β€πŸŽ“ Query Performance Monitor
    • πŸ§‘β€πŸŽ“ Monitoring Agent
    • πŸ§‘β€πŸŽ“ Data Products
    • πŸ§‘β€πŸŽ“ Data Profiler
    • πŸ§‘β€πŸŽ“ Warehouse Navigation
  • Triage
    • πŸ§‘β€πŸŽ“ Key Assets
    • πŸ§‘β€πŸŽ“ Domains
    • πŸ§‘β€πŸŽ“ Alert Feed
    • πŸ§‘β€πŸŽ“ Incident Management Overview
    • πŸ§‘β€πŸŽ“ Status Updates
    • πŸ§‘β€πŸŽ“ Integrating Airflow
    • πŸ§‘β€πŸŽ“ Notifications as Code
    • πŸ§‘β€πŸŽ“ Triaging Notifications
  • Resolve
    • πŸ§‘β€πŸŽ“ Circuit Breakers
    • πŸ§‘β€πŸŽ“ Monte Carlo Python SDK
    • πŸ§‘β€πŸŽ“ Insights
    • πŸ§‘β€πŸŽ“ Resolving Notifications
    • πŸ§‘β€πŸŽ“ Daily Digest
    • πŸ§‘β€πŸŽ“ Usage Management
    • πŸ§‘β€πŸŽ“ Performance
    • πŸ§‘β€πŸŽ“ Exclusion Windows
    • πŸ§‘β€πŸŽ“ Monitor Templates
  • Measure
    • πŸ§‘β€πŸŽ“ Monitor Tags & Dimensions
    • πŸ§‘β€πŸŽ“ Data Quality Dashboard
    • πŸ§‘β€πŸŽ“ Data Operations Dashboard
    • πŸ§‘β€πŸŽ“ Table Health Dashboard
    • πŸ§‘β€πŸŽ“ Monte Carlo API
  • Settings
    • πŸ§‘β€πŸŽ“ SSO, User Groups and Permissions
    • πŸ§‘β€πŸŽ“ Billing Page
    • πŸ§‘β€πŸŽ“ User Profiles and Email Digest
  • Monte Carlo Mastery Series
    • πŸ§‘β€πŸŽ“ How To Avoid Alert Fatigue & Manage Incidents Effectively
    • πŸ§‘β€πŸŽ“ Creating an Alert Strategy that Guarantees Action
    • πŸ§‘β€πŸŽ“ Creating a Proactive Monitoring Strategy with Monte Carlo
    • πŸ§‘β€πŸŽ“ How to Scale Data Quality with Data Observability + Data Testing
    • πŸ§‘β€πŸŽ“ Setting Up Your Monitoring Strategy for Maximum Impact
    • πŸ§‘β€πŸŽ“ How to Optimize Cost, Stakeholder Experience and Data Trust with Performance
    • πŸ§‘β€πŸŽ“ Optimize Data Quality for Key Assets with Data Products
    • πŸ§‘β€πŸŽ“ How to Roll Out Data Observability to Your Organization

Product Usage

  • Monte Carlo at a Glance
  • Alerts
    • Interacting with Alerts
    • Alert Statuses
    • Introducing: Alerts
    • Marking Alerts as Incidents
  • Dashboards
    • Data operations
    • Data quality
    • Table health
    • Insights (deprecated)
      • Importance Score Calculation
      • Insight: Key Assets
      • Insight: Coverage Overview
      • Insight: Table Cleanup Suggestions
      • Insight: Field-level Cleanup Suggestions
      • Insight: Field importance scores
      • Insight: Events
      • Insight: Rule Results
      • Insight: Field Health Suggestions
      • Insight: Misconfigured Monitors
      • Insight: BI Dashboard Analytics
      • Insight: Alert History
      • Insight: Notifications by custom monitor
      • Insight: Data Product Recommendations
    • Activity
  • Performance
  • Assets
    • Using Assets
    • Muting
    • Asset tags
    • Field Lineage
    • Data Profiler
  • Data Products
  • Settings
    • Notifications
    • Authorization
    • Single Sign On (SSO)
      • Map SSO Groups to Authorization Groups
      • FAQs and Troubleshooting
    • SCIM
      • SCIM Provision with Okta
      • SCIM Provision with Microsoft Entra ID
    • Table Monitors
      • Recommended monitoring strategies for tables
    • Billing
  • Data exports
  • User Profile
    • Weekly Data Reliability Summary Email

Monitors

  • Monitors Overview
  • Table
    • Freshness
    • Volume
    • Schema Change
    • Migration
  • Metrics
    • Metric Monitors
      • Available Metrics
      • Custom Metrics
      • Segmentation
      • Backfill History
    • Comparison Monitors
  • Validations
    • Validation Monitors
      • Available Conditions
    • Custom SQL
      • Templates
    • Freshness Rules
    • Volume Rules
  • Job
    • Query Performance
  • Additional Resources
    • Monitor logs
    • Reducing noise from monitors
    • Partition filtering for monitors
    • Failure notifications
    • Misconfigured monitors
    • Allocating query cost
    • Monitor tags
    • Changes to legacy monitors

Anomaly Detection

  • Overview
  • Tuning thresholds
    • Exclusion Windows
    • Managing Holidays

Investigation

  • Metric investigation
  • Root Cause Analysis (RCA) Insights
  • Pull requests (public preview)

Architecture

  • Overview
  • Deployments
    • AWS: Data Store Deployment
    • AWS: Agent Deployment
    • Azure: Data Store Deployment
    • Azure: Agent Deployment
    • GCP: Data Store Deployment
    • GCP: Agent Deployment
  • Network Connectivity
    • AWS PrivateLink
      • AWS Endpoint Services
    • Azure Private Link
  • Data Collector
    • Upgrading the Collector
  • Additional Resources
    • Agent Management
    • Rotating Keys
    • Integration Specific Deployments
      • Snowflake Native App (public preview)
    • Platform Migrations
      • Migrating from a Remote Data Collector

Security & Compliance

  • Overview
  • Compliance
  • Privacy
    • Subprocessors
    • Information Monte Carlo Collects
      • Data Sampling
    • Customer Support AI Use at Monte Carlo
  • Security

Developer Tools

  • Overview
  • API
    • API Authentication
    • API Explorer
    • API Example Use Cases
      • General
      • Integrations
      • Lineage
      • Monitors
    • Troubleshooting and FAQs: API
  • SDK
  • CLI
    • Secret management with the CLI
  • Monitors as Code
    • Locally setting up Monitors as Code
    • Generating MC monitors from dbt tests
    • Notifications as Code

Integrations

  • Data Warehouses
    • Snowflake
    • BigQuery
    • Redshift
      • Redshift Datashares
    • Salesforce Data Cloud
    • Azure Synapse (public preview)
    • Teradata
    • MotherDuck (public preview)
    • Dremio (public preview)
    • ClickHouse (public preview)
    • Adding Additional Warehouses
  • Databricks
    • Troubleshooting & FAQ: Databricks
    • End of life for Notebook-based Metadata Collection on Databricks
    • Databricks Workflows (public preview)
      • Screenshot 2025-07-30 at 1.00.01PM
      • Screenshot 2025-07-30 at 12.59.42PM
  • Data Lakes
    • Metastores
      • Glue
      • Hive Metastore
    • Query Engines
      • Athena
      • Presto (public preview)
      • Hive SQL (public preview)
      • Spark
      • Presto, Hive, & EMR: Query Logs
    • Troubleshooting & FAQ: Data Lakes
    • Appendix: Data Lakes
      • Creating IAM Roles
      • Auto-generating IAM Policy Documents
      • Creating event notifications
      • Adding Additional Connections
  • Transactional Databases
    • SQL Server
    • Postgres
    • Azure SQL Database
    • Oracle DB (public preview)
    • MySQL
    • SAP HANA (public preview)
    • Salesforce CRM (public preview)
  • Vector Databases
    • Pinecone (public preview)
  • BI Tools
    • Looker
      • Troubleshooting and FAQs: Looker
    • Mode BI
    • Periscope/Sisense (public preview)
    • Power BI
      • Power BI - Credential Creation Process
      • Troubleshooting and FAQs: Power BI
    • Sigma
    • Tableau - Connected Apps version, recommended
      • Troubleshooting and FAQs: Tableau
      • Tableau - PAT version, CLI-only initial setup
      • Troubleshooting and FAQs: Tableau (PAT version, CLI-only)
    • Hex
  • Orchestration & Transformation
    • Airflow
      • Airflow in Lineage
      • Airflow Alerts and Task Observability
    • dbt Integration
      • dbt Cloud
      • dbt Core
      • dbt Failures As Monte Carlo Alerts
    • Fivetran Integration
      • Troubleshooting and FAQ: Fivetran
    • Informatica (public preview)
    • Kafka (public preview)
      • Confluent Cloud (public preview)
      • Self-Hosted Kafka (public preview)
      • MSK (public preview)
    • Prefect
    • Circuit breakers
      • Using providers
    • Azure Data Factory (public preview)
      • Additional Support for ADF in Lineage
  • Notifications & Collaboration
    • GitHub
    • Jira
    • Incident.io
    • Microsoft Teams
    • [Legacy version] Microsoft Teams
    • Opsgenie
    • PagerDuty
    • ServiceNow
    • Slack
    • Webex
    • Webhooks
    • GitLab (public preview)
    • Azure DevOps (Public Preview)
    • Google Chat
  • Catalogs
    • Alation
    • Atlan
    • Collibra (public preview)
    • data.world
    • Secoda
    • Select Star
  • Data Collection: Details per Integration
  • Data Asset Validators
  • Using self-hosted credentials
  • Updating an Integration

Resource Center

  • Advanced Usage
    • PII Filtering
    • Muting schemas/tables using regex
    • Audit Logging
  • Integration & Feature Lifecycles

Using providers

Monte Carlo providers can be used in your pipelines to get and create resources using our Python SDK or any other dependencies.

Orchestrators

Details

Airflow

https://pypi.org/project/airflow-mcd/

Updated about 2 months ago


Circuit breakers
Azure Data Factory (public preview)