Loading...
Loading...
Found 34 Skills
Use this skill when authoring PolicyRuleDefinition and PolicyRuleDefinitionSet metadata XML for the Salesforce Enforce-O-Matic MDAPI (Data Cloud governance policies), or when editing *.policyRuleDefinition / *.policyRuleDefinitionSet files. Covers the category decision tree, full schema for all policy variants (ACCESS, GOVERNANCE, RECORD, TRANSFORM), UI-compatibility rules for the Data Governance Policy Builder, and validation guardrails. Do NOT use this skill for UserAccessPolicy, AccessPolicy, SharingRules, PermissionSet, or any non-Enforce-O-Matic access-control metadata — those have their own types and live outside the PolicyRuleDefinition schema.
Roll out self-serve analytics on MotherDuck for internal teams. Use when deciding the first governed dataset, the first Dive or share, ownership boundaries, and the rollout path from one audience to broader adoption.
Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
Audit and improve CRM data quality by identifying missing fields, inconsistent values, duplicate records, and stale data
Expert knowledge for Azure Databricks development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Unity Catalog, Lakeflow, Lakebase, Delta Sharing, Databricks SQL, or Model Serving workloads, and other Azure Databricks related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Machine Learning (use azure-machine-learning), Azure Data Factory (use azure-data-factory).
Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.
Expert patterns for Segment Customer Data Platform including Analytics.js, server-side tracking, tracking plans with Protocols, identity resolution, destinations configuration, and data governance best practices. Use when: segment, analytics.js, customer data platform, cdp, tracking plan.
Data lake and lakehouse platform patterns: ingestion/CDC, transformations, open table formats (Iceberg/Delta/Hudi), query and serving engines (Trino/ClickHouse/DuckDB), orchestration, governance/lineage, cost and operations. Self-hosted and cloud options.
Use to design and document customer segments with clear criteria, metrics, and governance.
Use this skill when the user wants to add or update metadata in DataHub: descriptions, tags, glossary terms, ownership, deprecation, domains, data products, structured properties, documents, or field-level metadata. Triggers on: "add tag to X", "update description for X", "set owner of X", "add glossary term", "deprecate X", "create a domain", "create a glossary term", "add a document", or any request to modify DataHub metadata.
Data handling best practices for Guidewire InsuranceSuite including entity management, data migration, batch operations, and data governance. Trigger with phrases like "guidewire data", "entity management", "data migration", "batch processing", "data governance guidewire".
Unity Catalog governance patterns, permissions models, security best practices, and policy enforcement for enterprise data governance.