'data framework' 검색 결과

Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Maps NIST PF controls to GDPR requirements for dual-framework compliance. Keywords: NIST Privacy Framework, IDENTIFY function, ID.BE, ID.DA, ID.IM, ID.RA, privacy risk assessment, data actions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Stimulus JS framework for Symfony UX -- client-side behavior via HTML data attributes, zero server round-trips. Use when creating controllers for DOM manipulation, handling click/input/submit events, managing targets and values, wiring outlets between controllers, wrapping third-party JS libraries, or building toggles, dropdowns, modals, tabs, clipboard interactions. Code triggers: data-controller, data-action, data-target, data-*-value, data-*-class, data-*-outlet, stimulusFetch lazy, connect(), disconnect(), static targets, static values. Also trigger when the user asks "how do I add a click handler", "how to toggle a class", "how to build a dropdown/modal/tabs", "how to wrap a JS library in Symfony", "add keyboard shortcuts", "lazy-load a controller", "listen to global events", "communicate between controllers". Do NOT trigger for partial page updates without JS (use turbo), server-rendered reactivity (use live-component), or reusable Twig templates (use twig-component).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create HTML slides for a hospital board or regulators, explaining patient-data risks, safeguards, responsibilities, and required approvals. The skill uses a fixed presentation template with speaker notes to organize evidence and support a clear decision.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Briefing a hospital board on patient-data risks
• Explaining data controls and responsibilities to regulators
• Preparing slides for a data-governance approval

Create, modify, test, or package Python provider adapters, the components used for framework connections. Work covers framework dependencies, public imports, type inference, and provider metadata within python/providers, with a referenced workflow to consult before changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create or modify a Python provider adapter
• Adjust framework-specific dependencies and public imports
• Work on type inference and provider metadata

Build Handsontable demo pages for visual regression tests, which compare screenshots for appearance changes. It guides feature routes, URL-driven display states, sample data, and decisions about testing the same feature across framework wrappers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding a demo route for a new feature
• Creating multiple visual states through URL parameters
• Planning visual coverage across framework wrappers

Review Google Cloud workloads against the security principles of the Well-Architected Framework. Identify gaps in access control, network protection, data handling, and security operations, then receive prioritized recommendations linked to relevant Google Cloud products.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing security during Google Cloud architecture design
• Checking access permissions and network defenses
• Identifying gaps in data protection and security monitoring

Add DeepEval tracing to Python AI applications so execution steps appear in Confident AI. Choose a supported integration or manual @observe instrumentation, then capture inputs, outputs, step types, tags, and metadata.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Trace execution steps in a Python AI application
• Select tracing integrations for an existing framework
• Add manual tracing with @observe

Guidance for implementing CollectionView in .NET MAUI apps — data display, layouts (list & grid), selection, grouping, scrolling, empty views, templates, incremental loading, swipe actions, and pull-to-refresh. USE FOR: "CollectionView", "list view", "grid layout", "data template", "item template", "grouping", "pull to refresh", "incremental loading", "swipe actions", "empty view", "selection mode", "scroll to item", displaying scrollable data, replacing ListView. DO NOT USE FOR: simple static layouts without scrollable data (use Grid or StackLayout), map pin lists (use Microsoft.Maui.Controls.Maps), table-based data entry forms, non-MAUI list controls, CarouselView or BindableLayout questions, platform-specific handler or renderer customization, diagnosing CollectionView bugs in the MAUI framework itself, or general MVVM/binding questions that merely happen to mention a list (use maui-data-binding).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guidance for implementing CollectionView in .NET MAUI apps — data display, layouts (list & grid), selection, grouping, scrolling, empty views, templates, incremental loading, swipe actions, and pull-to-refresh. USE FOR: "CollectionView", "list view", "grid layout", "data template", "item template", "grouping", "pull to refresh", "incremental loading", "swipe actions", "empty view", "selection mode", "scroll to item", displaying scrollable data, replacing ListView. DO NOT USE FOR: simple static layouts without scrollable data (use Grid or StackLayout), map pin lists (use Microsoft.Maui.Controls.Maps), table-based data entry forms, non-MAUI list controls, CarouselView or BindableLayout questions, platform-specific handler or renderer customization, diagnosing CollectionView bugs in the MAUI framework itself, or general MVVM/binding questions that merely happen to mention a list (use maui-data-binding).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement the NIST Privacy Framework CONTROL function covering CT.DM data management, CT.DP data processing policies and procedures, and CT.PO disassociated processing. Provides technical control architectures, data management workflows, and de-identification implementation guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guides assessment and use of the EU-US Data Privacy Framework adequacy decision for transatlantic data transfers. Covers DPF self-certification with the Department of Commerce, DPF principles compliance, Data Protection Review Court, and annual EC review. Keywords: DPF, EU-US, adequacy, Privacy Shield, transatlantic transfers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guides managing conflicting privacy requirements across jurisdictions. Covers data localisation vs transfer freedom, consent standards variation, age thresholds, breach timelines, and resolution frameworks for incompatible obligations. Keywords: conflicting laws, data localisation, consent variation, age thresholds, resolution framework.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

管理咨询 (管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统，从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」，这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」，资深人偏 top-down 假设树减少 boil-the-ocean，但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」，「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的价值之辩 (「借你的表告诉你时间」「frameworks 是剧场表演 vs 真洞见」Matthew Stewart《The Management Myth》)、McKinsey 的丑闻 (Purdue 阿片类/独裁政府/ICE/利益冲突, Bogdanich & Forsythe《When McKinsey Comes to Town》)、咨询 vs 自建战略部、generalist 通才 vs specialist 专才之争、AI/GenAI 对初级分析师工作的冲击; (h) 流派 — 战略经典 (Porter 定位学派/五力 vs 资源基础观 RBV vs 蓝海战略 Kim&Mauborgne vs 颠覆式创新 Christensen vs Mintzberg 应急战略批判 planning school); 三巨头气质分野 (McKinsey 事实驱动/CEO 信任/通才, BCG 概念/思想领导力/经验曲线/增长-份额矩阵, Bain 结果导向/NPS 净推荐值/PE 关系/与客户深度绑定)。不含: 投行 M&A/财务顾问 (估值/承销超出范畴)、纯 IT 实施/系统集成 (SI 人力外包)、纯审计/税务、纯人力 RPO/猎头、内部战略部 only (虽相关但本 skill 聚焦专业服务咨询的外部视角)。) Master OS — automated mastery of 管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统，从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」，这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」，资深人偏 top-down 假设树减少 boil-the-ocean，但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」，「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Knowledge base from the NASA Digital Engineering Acquisition Framework Handbook (NASA-HDBK-1004). Use for acquiring digital/model-based data under contract: the Data Requirements Description (DRD) instrument and the Appendix A DRD suite (TDP, MBx, CDMP, CSA, CR, FCA/PCA, SDT, EMDAL, REF, MRI); the Data Type 1-5 control scale; SOW/RFP/Cost-Volume contract language and data rights (FAR/DFARS, Table 3 license categories); the Requirements Exchange Format (REF/ReqIF, UUID schema) and Master Records Index; model-based data definition (MBSE, CAD/PMI, M&S credibility, BOM, release-state mapping, PLM); digital data collaboration, the four owned architectures, and interoperability standards (MIL-STD-31000, STEP/ISO 10303, ASME Y14); the four MBE interoperability use cases; and MBE Plan development. Scope is the acquisition and contracting side of digital engineering. Does not reproduce ISO/STEP/ASME/MIL-STD/SAE standard text, and the companion NASA-HDBK-1009A carries the deeper digital-engineering practitioner detail this handbook defers to.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Ruby on Rails 앱의 구현과 검토에서 업무 처리, 검색, 폼의 책임을 정리합니다. 불필요한 데이터 조회를 줄이고 백그라운드 작업과 화면 구성 요소 설계도 돕습니다.

• 큰 controller의 업무 처리를 분리합니다
• 여러 모델을 갱신하는 폼을 설계합니다
• 중복 검색과 데이터 조회를 검토합니다

Django 모델, 화면, API를 테스트부터 작성해 구현하고 검증합니다. 테스트 데이터 생성, 외부 서비스 모의 처리, 코드 커버리지 확인도 다룹니다.

• 테스트부터 Django 기능 개발하기
• API 인증과 입력 검증 확인하기
• 재사용할 테스트 데이터 준비하기

기술이나 설계를 선택한 이유를 배경, 대안, 영향과 함께 Markdown으로 기록합니다. 일련번호와 색인으로 정리하고 기존 기록에서 과거 판단의 근거도 찾습니다.

• 프레임워크나 데이터베이스 선택 이유 기록
• 설계 대안과 장단점 정리
• 과거 기술 결정의 근거 확인

Plan market, competitor, consumer, or financial research with chapter outlines, data requirements, and chart plans. Then turn collected evidence into a structured Markdown report with comparisons, citations, and strategic implications, while clearly identifying missing data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning research chapters and data collection requirements
• Turning market and competitor findings into a report
• Organizing consumer insights and brand strategy analysis

Organize PyTorch models and data pipelines with PyTorch Lightning, automate training, save checkpoints, and track experiments. Includes templates and guidance for configuring training across multiple GPUs or TPUs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Restructure PyTorch training code into LightningModules
• Build reusable data preparation and loading pipelines
• Configure checkpoints, early stopping, and experiment logs

Generate or scaffold ASP.NET Core code — Razor Pages, Blazor components, MVC controllers, views, and Minimal API endpoints — without using ASP.NET Core CLI scaffolding/code-generation tools. Use when (1) adding CRUD pages, views, or API endpoints backed by Entity Framework (EF Core) and a database, (2) generating code to create, read, update, and delete data using a DbContext, (3) scaffolding UI components that match the project's existing CSS framework and coding patterns, or (4) creating data-driven forms, tables, and navigation for a model class. Do not use for non-ASP.NET projects or when CLI-based scaffolding is preferred.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate or scaffold ASP.NET Core code — Razor Pages, Blazor components, MVC controllers, views, and Minimal API endpoints — without using ASP.NET Core CLI scaffolding/code-generation tools. Use when (1) adding CRUD pages, views, or API endpoints backed by Entity Framework (EF Core) and a database, (2) generating code to create, read, update, and delete data using a DbContext, (3) scaffolding UI components that match the project's existing CSS framework and coding patterns, or (4) creating data-driven forms, tables, and navigation for a model class. Do not use for non-ASP.NET projects or when CLI-based scaffolding is preferred.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.