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Found 19 Skills
Comprehensive Power BI data model design review prompt for evaluating model architecture, relationships, and optimization opportunities.
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.
Comprehensive plugin for SAP Datasphere development with 3 specialized agents, 5 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL views, local/remote tables, transformation flows), Business Builder (business entities, consumption models), analytic models (dimensions, measures, hierarchies), 40+ connection types (SAP S/4HANA, BW/4HANA, HANA Cloud, AWS, Azure, GCP, Kafka, Generic HTTP), real-time replication, task chains, content transport, CLI automation, catalog governance, and data marketplace. Includes 2025 features: Generic HTTP connections, REST API tasks in task chains, SAP Business Data Cloud integration. Keywords: sap datasphere, data warehouse cloud, dwc, data builder, business builder, analytic model, graphical view, sql view, transformation flow, replication flow, data flow, task chain, remote table, local table, sap btp data warehouse, datasphere connection, datasphere space, data access control, elastic compute node, sap analytics cloud integration, datasphere cli, data products, data marketplace, catalog, governance
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.
Use to design and document customer segments with clear criteria, metrics, and governance.
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.
Implement data quality checks, validation rules, and monitoring. Use when ensuring data quality, validating data pipelines, or implementing data governance.
Guide developers at OctoCAT Supply to build applications that are secure and compliant by design. You are an expert specializing in software compliance, privacy, and security.
BigQuery Expert Engineer Skill - Comprehensive guide for GoogleSQL queries, data management, performance optimization, and cost management Use when: - Running bq commands (query, load, extract) - Writing GoogleSQL queries (functions, JOINs, CTEs) - Designing partitioned/clustered tables - Using BigQuery ML or external data sources
Design and manage reference data systems — security master, client master, account master, identifier mapping, pricing data, and governance. Use when building or evaluating a security master database, mapping identifiers across systems (CUSIP to ISIN, SEDOL to FIGI), designing client master models for onboarding or KYC, defining account master attributes across custodians, implementing pricing validation with vendor hierarchy, establishing reference data governance and stewardship, handling identifier changes from corporate actions, or troubleshooting data quality issues traced to stale prices or missing identifiers. Trigger on: security master, CUSIP, ISIN, SEDOL, FIGI, client master, account master, pricing data, reference data, golden source, MDM, master data, identifier mapping, data governance, pricing validation.
Audit all Kafka topic configurations against production best practices using the Lenses MCP server. Checks replication factor, retention, partitions, compaction, naming conventions, orphaned topics and missing metadata. Use when user says "audit my topics", "check topic configs", "topic health check" or asks about retention, replication or partition settings. Do NOT use for creating, deleting or modifying topics.