Total 50,510 skills, Data Processing has 2560 skills
Showing 12 of 2560 skills
Provides guidance for writing, packaging and executing Apache Beam pipelines on GCP using Cloud Dataflow. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Flex Template.
Use these skills when you need to handle large-scale data exploration and dataset management. Use when users need to find data assets or run SQL at scale. Provides metadata discovery and query execution across the data warehouse.
DataWorks Operations Center assistant for task and workflow operations, alert rule creation and management. Covers troubleshooting, failure recovery, baseline assurance, monitoring and alerting. Supports periodic, manual, and triggered tasks/workflows (excludes real-time/streaming tasks). Uses aliyun CLI to call dataworks-public OpenAPI (2024-05-18). Trigger keywords: query task, task instance, instance log, workflow, workflow instance, alert rule, operations center, task failure, instance status, upstream/downstream dependency, rerun, monitoring alert, custom monitoring, alert rule, task instance, workflow instance, operation log, baseline assurance, failure recovery, DataWorks operations. Do NOT trigger: data source management, compute resources, resource groups, data development, MaxCompute table management, ECS/RDS/OSS operations, workspace member management, data quality, data lineage, data preview.
Migrate Databricks workloads from classic compute to serverless compute. Scans code for serverless compatibility issues, provides concrete fixes for the serverless Spark Connect architecture, and guides the full migration to serverless environments. Use for classic-to-serverless migrations, serverless code compatibility checks, or writing new serverless-compatible notebooks and jobs. Not for classic DBR version upgrades or cluster configuration changes within classic compute.
Nasdaq Data Link integration. Manage Datasets. Use when the user wants to interact with Nasdaq Data Link data.
Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, or semantic nearest-neighbor lookup. Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext/keyword indexes (FULLTEXT INDEX, db.index.fulltext) — use neo4j-cypher-skill. Does NOT handle GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
Neo4j Graph Data Science (GDS) plugin — graph projection, algorithm execution, execution modes (stream/stats/mutate/write), memory estimation, and the GDS Python client (graphdatascience v1.21). Use when running gds.pageRank, gds.louvain, gds.wcc, gds.fastRP, gds.knn, gds.betweenness, gds.nodeSimilarity, or any gds.* procedure; projecting named in-memory graphs with gds.graph.project or graph.project; chaining algorithms with mutate mode; computing node embeddings for ML; building recommendation systems with FastRP + KNN. Also triggers on GraphDataScience, GdsSessions, graph catalog operations, ML pipelines, node classification, link prediction. Does NOT cover Aura Graph Analytics serverless sessions — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.
Diagnoses and fixes slow Neo4j Cypher queries by reading execution plans, identifying bad operators (AllNodesScan, CartesianProduct, Eager, NodeByLabelScan), and prescribing fixes (indexes, hints, query rewrites, runtime selection). Use when a query is slow, when EXPLAIN or PROFILE output needs interpretation, when dbHits or pageCacheHitRatio are poor, when cardinality estimation diverges from actuals, or when deciding between slotted/pipelined/parallel runtimes. Covers USING INDEX / USING SCAN / USING JOIN hints, db.stats.retrieve, SHOW QUERIES, SHOW TRANSACTIONS, TERMINATE TRANSACTION. Does NOT write new Cypher from scratch — use neo4j-cypher-skill. Does NOT cover GDS algorithm tuning — use neo4j-gds-skill. Does NOT cover index/constraint creation syntax details — use neo4j-cypher-skill references/indexes.md.
You are a **Data Engineer**, an expert in designing, building, and operating the data infrastructure that powers analytics, AI, and business intelligence. You turn raw, messy data from diverse sour...
Overview of LookML field types (Dimension, Measure, Filter, Parameter) and the role of the `sql` parameter in each. Use this skill to choose the right field type for your data modeling needs.
Standards and best practices for writing LookML tests to ensure data integrity, accuracy, and logic validation.
Use this skill when you need to create or modify a LookML Model file (.model.lkml). This includes defining connections, includes, and configuring model-level settings.