Results for “data”

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

Builds a configurable scraping agent that collects data from APIs, HTML, or RSS, enriches it with Gemini AI scoring, and stores results in Notion, Google Sheets, Supabase, or local files.

Process large ML datasets in parallel across CPU or GPU clusters, with streaming execution, multi-format I/O, and integration with Ray Train, PyTorch, and TensorFlow for batch inference and preprocessing pipelines.

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

Use to map where support conversation data actually goes — systems, vendors, countries, AI providers — and compare it against what the privacy notice and records say. Trigger for "where does our support data go", "map our data flows", "which vendors process our conversations", cross-border transfer review, ROPA accuracy for support, or a new tool that was connected without a review.

Design GraphQL schemas, resolvers, and DataLoader patterns, integrate with Apollo/urql, and implement federation for microservices.

Automate Diffbot data extraction and analysis through Composio's Diffbot toolkit via Rube MCP.

Develop SurrealDB WASM extensions in Rust, compile them to WebAssembly, and deploy them as database modules callable from SurrealQL.

Query, filter, transform, and aggregate JSON data using jq, with practical patterns for shell pipelines and CLI integration.

Applies Schema.org structured data principles to guide decision-making, structure analysis, and improve search visibility outcomes.

Operates Scaleway cloud resources through the scw CLI, covering instances, images, object storage, Kubernetes, and databases.

Create publication-quality statistical graphics in Python with dataset-oriented plotting, semantic mapping, and automatic statistical estimation.

Build and deploy machine learning models with TensorFlow, covering Keras, data pipelines, and production serving.

Prepares, audits, and organizes fundraising materials for investor due diligence, generating a readiness checklist and folder structure.

Design GraphQL schemas, resolvers, and DataLoader patterns, and integrate clients with Apollo or urql.

Create publication-quality statistical graphics in Python with dataset-oriented plotting, semantic mapping, and built-in statistical estimation.

Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis.

`analysis-agent`/`task-agent`/`review-agent`: use when personal-data purpose, retention, deletion, sharing, telemetry, or provider handling changes; skip legal-only work.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Build declarative UI and manage data flow with SwiftUI in iOS. Use when building declarative SwiftUI views or managing data flow with property wrappers.

Secure iOS apps with secure storage, biometrics, and data protection. Use when implementing secure storage, Face ID/Touch ID, or data protection in iOS.

Implement local persistence with SwiftData, Core Data, and secure storage. Use when setting up SwiftData models, Core Data stacks, or local persistence in iOS.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Prediction markets data - Polymarket, Kalshi markets, prices, positions, and trades. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Use this when reviewing database, storage, config, queue, or integration migrations for rollout safety, rollback feasibility, data correctness, and environment-specific deployment risk.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Expert patterns for Segment Customer Data Platform including Analytics.js, server-side tracking, tracking plans with Protocols, identity resolution, destinations configuration, and data governance ...