Results for “da”

Provides expert guidance on modern SQL, cloud-native databases, and query optimization, covering performance tuning, data modeling, and hybrid analytical systems.

Provides expert guidance on modern SQL, cloud-native databases, query optimization, performance tuning, and data modeling for OLTP/OLAP workloads.

Audits codebases for GDPR and CCPA/CPRA compliance by inventorying PII fields, mapping data collection points, reviewing consent mechanisms, verifying data subject rights, tracing third-party data sharing, and checking retention policies.

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.

Automates college football data operations through Composio's College Football Data toolkit via Rube MCP, with tool discovery and connection management.

Executes GDPR Article 20 data portability requests, covering machine-readable format requirements (JSON, CSV, XML), direct controller-to-controller transfer mechanisms, and scope limitations to data provided by the subject on consent or contract basis. Activate for portability, data export, Art. 20, data transfer queries.

Execute KQL queries and manage Azure Data Explorer resources for fast, scalable big data analytics on log, telemetry, and time series data.

Send custom logs to Azure Monitor via Data Collection Rules and Data Collection Endpoints using the Java SDK.

Generate XML configuration files and execute SSMA Console commands for Oracle to SQL Server database migration, including schema conversion and data migration.

Manages biological datasets and models with LaminDB, covering setup, artifact registration, querying, lineage tracking, validation, ontology annotation, collections, branches, storage, and workflow integrations.

Fetches latest WHOOP recovery, sleep, and strain data and generates daily suggestions.

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

Automate web crawling and data extraction with Firecrawl: scrape pages, crawl sites, extract structured data, batch scrape URLs, and map website structures.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB da

Access and manage NocoDB databases, tables, and records via REST API. Use when the user wants to view bases, list tables, inspect column schemas, query or filter row data, or insert new records into a self-hosted NocoDB instance. Also use for spreadsheet-style database lookups and data entry.

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

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

Fast in-memory DataFrame analytics with Polars — lazy evaluation, parallel execution, and an Apache Arrow backend for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory, for 1-100GB datasets, ETL pipelines, or a faster pandas replacement. For larger-than-RAM data prefer dask or vaex. Part of the AlterLab Academic Skills suite.

Provides a fast in-memory DataFrame library for datasets that fit in RAM, with lazy evaluation, parallel execution, and an Apache Arrow backend for ETL pipelines and analytics.

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.

Design clear, accessible data visualizations with appropriate chart selection and styling.

Understand and query the NPSP data model, including namespace prefixes, GAU allocations, recurring donations, relationships, and affiliations.

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

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

The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.

Evaluates Power BI data model architecture, relationships, storage modes, and performance to identify optimization opportunities and ensure adherence to best practices.

Guides scaling decisions for Qdrant vector databases when data volume exceeds single-node capacity, covering tenant scaling, time window rotation, vertical scaling, and horizontal sharding.

Collects Chinese A-share stock data, fetching stock lists and daily, weekly, and monthly K-line history into a local SQLite database for quantitative analysis.

Manages Xata serverless databases via the xata CLI and REST API, covering discovery of workspaces, databases, branches, tables, schema, migrations, and record counts with read-only operations.

Design PostgreSQL schemas with best practices for data types, indexing, constraints, and performance patterns.

Fetches your latest WHOOP recovery, sleep, and strain data and generates a short set of daily suggestions.

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

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required.

Process and analyze large tabular datasets (billions of rows) that exceed available RAM using lazy, out-of-core DataFrames with fast aggregations, visualization, and machine learning integration.

Investigates insider threat indicators including data exfiltration attempts, unauthorized access patterns, policy violations, and pre-departure behaviors using SIEM analytics, DLP alerts, and HR data correlation.