Results for “da”

Safe patterns for evolving database schemas in production with decision trees and troubleshooting guidance.

Task and todo list management. Create, organize, and track tasks with priorities and due dates.

Build a launch checklist with owners, dates, dependencies, decision gates, and follow-through.

Scaffolds Web3 dApps with wallet connection, contract interaction, and transaction management

Generate realistic test data with proper relationships, constraints, and edge cases

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

New Jersey Data Privacy Act (NJDPA) compliance, effective January 15, 2025. Covers consumer rights (access, correction, deletion, portability, opt-out), controller obligations, sensitive data requirements, universal opt-out mechanism recognition, 30-day cure period (sunsets after 18 months), and AG enforcement. Keywords: NJDPA, New Jersey, data privacy, consumer rights, sensitive data, universal opt-out, AG enforcement.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Design comfortable, accessible dark mode interfaces with proper color adaptation, contrast, and surface hierarchy.

Adopt the voice and methodology of Spotify's Daniel Ek to guide product strategy, marketplace design, and iterative growth decisions.

Embody David Hume's empiricist and skeptical method to analyze causal claims, inductive arguments, moral reasoning, and metaphysical concepts.

Queries Korean public holidays and performs business day calculations via the HuDy MCP server, including counting business days and managing custom holidays.

Use when the user says "plan my morning" or wants to fill out morning journaling (Gratitude, Better Day, Daily Affirmation) and personal/work tasks for today's daily note.

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Use essa skill para processar e analisar grandes conjuntos de dados tabulares (bilhões de linhas) que excedem a RAM disponível. Vaex excels em operações DataFrame out-of-core, avaliação lazy, agregações rápidas, visualização eficiente de big data e machine learning em datasets grandes. Aplique quando usuários precisarem trabalhar com arquivos CSV/HDF5/Arrow/Parquet grandes, realizar estatísticas rápidas em datasets massivos, criar visualizações de big data ou construir pipelines de ML que não cabem em memória.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Deploy privileged access management for database systems including Oracle, SQL Server, PostgreSQL, and MySQL, covering session proxy configuration, credential vaulting, query auditing, dynamic credential generation, and least-privilege database roles.

Use to build Cell's data and code deposition plan and the Data and Code Availability statement that lives inside STAR Methods Resource Availability — approved repositories, accessions/DOIs at submission, and Cell's three-bullet availability format with Mendeley Data as Elsevier's default.

Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms, turning metrics into actionable operational views.

Wire UI controls to ViewModel properties with compile-time safety, change notification, and minimal overhead using .NET MAUI data bindings.

Generates a single-page team management dashboard with tabs for members, details, and activity log, including charts and CSV export.

Creates interactive, publication-quality charts with 40+ types, hover tooltips, zoom, and web-embeddable exports for dashboards and exploratory analysis.

Verifica la reproducibilidad y consistencia de un análisis de datos antes de presentarlo, validando contra la pregunta original y documentando limitaciones.

Analiza datasets con Pandas y NumPy: explora distribuciones, correlaciones y patrones, y aplica tests de hipótesis para extraer conocimiento no obvio.

Optimize SQL queries, design database schemas, and tune performance across cloud-native and hybrid OLTP/OLAP environments.

Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

DataFrame operations with pandas and polars — groupby, joins, reshaping, performance. Use when manipulating tabular data, choosing between pandas and polars, optimizing DataFrame code, or translating between the two libraries.

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

Design normalized database schemas with tables, relationships, indexes, and constraints for any application domain. Use when the user requests database schema design or provides relevant inputs for this workflow.

MongoDB - NoSQL document database with flexible schema design, aggregation pipelines, indexing strategies, and Spring Data integration

SynthText: Synthetic Data for Text Detection

Data-Centric Artificial Intelligence: A Survey