“data”的搜索结果

Check article pages for structured data, machine-readable details that help search engines understand content. Review required properties, add Article metadata in JSON-LD format, and verify the rendered page and HTTP response for specific implementation gaps.

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• Checking structured data on blog articles
• Adding Article metadata in JSON-LD format
• Finding missing headlines, images, dates, or authors

Review database migration files before merging changes. It gathers evidence about what the changes do, rollback limits, database locks, and risks from large data volumes, then reports blockers when evidence needed for a decision is missing.

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• Review database changes before merging
• Check rollback limits
• Assess database locks and data-volume risks

Create, edit, and clean spreadsheet files, including Excel workbooks and CSV data. Add formulas, formatting, and charts, preserve existing workbook conventions, and recalculate formulas with error checks before delivering the spreadsheet.

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• Clean messy CSV data into a spreadsheet
• Edit an Excel workbook while preserving its formatting
• Create a financial model with recalculating formulas

Helps plan and implement database structure changes and data transformations using Sequelize, TypeORM, or Prisma. Includes staged changes intended to avoid downtime, plus transaction and backup examples for rolling back failed migrations.

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• Renaming database columns in stages
• Splitting stored addresses into separate fields
• Preparing rollback steps for failed migrations

Design dbt data transformations with clearly organized models, data quality tests, documentation, and incremental processing that updates only part of a dataset. Use it to structure analytics tables and organize a dbt project.

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• Organizing a dbt project into model layers
• Adding data quality tests
• Designing incremental updates for large tables

Analyzes one .NET project to plan integration tests for an Oracle-to-PostgreSQL migration. Identifies database access methods, prioritizes migration risks, and documents test cases, seed data, and coverage, including empty strings, NULL values, and timezone behavior.

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• Identifying database access methods that need integration tests
• Prioritizing tests for Oracle-specific behavior
• Planning checks for empty strings, NULL values, and timezones

Prepare raw credit data for pre-loan modeling by checking data quality and screening variables. Review missing values, predictive usefulness, stability, noise, and correlation, then export an Excel report with organization-level statistics and cleaning results.

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• Prepare credit data before building a model
• Compare missing values and bad-sample rates across organizations
• Screen variables for usefulness, stability, and redundancy

Investigate suspected data theft from AWS S3 by comparing access logs, GuardDuty findings, and Macie classifications. Identify unusual bulk downloads and transfers across accounts, assess sensitive data exposure, and build automated detection rules.

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• Investigating unusual bulk downloads from S3
• Checking transfers to external AWS accounts
• Assessing exposure of sensitive data

Analyze endpoint, cloud storage, and email logs for signs of insider data theft. Use pandas to compare upload volumes with normal user behavior and examine data loss prevention alerts, unusual file access, and activity outside working hours.

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• Investigating suspected insider data theft
• Finding users with unusually large uploads
• Reviewing file access outside working hours

Check training data and machine learning models for malicious changes, including backdoors that cause unexpected behavior on specific inputs. Combine data quality checks, model analysis, and file integrity verification, then document findings and retest after remediation.

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• Screening third-party data before training
• Checking downloaded model weights before deployment
• Investigating unexpected behavior on specific inputs

Design a database layer from business requirements, access patterns, and expected growth. Compare database technologies, define tables and relationships, and plan indexes, caching, scaling, migrations, backups, and recovery with clear reasons and trade-offs.

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• Choosing a database for a new service
• Designing tables, relationships, and indexes
• Planning database migrations and rollback procedures

Work with BigQuery to create datasets and tables, run SQL queries, ingest data, and manage processing jobs. The skill also covers connections to BigQuery ML and Gemini for machine learning and AI analysis.

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• Creating datasets and tables
• Analyzing data with SQL queries
• Ingesting data and managing processing jobs

Build document search and AI retrieval workflows with Chroma, a database for numerical representations of text. Cover document storage, meaning-based search, metadata filters, persistence, and connections to LangChain and LlamaIndex.

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• Building document search based on meaning
• Adding document retrieval to AI answers
• Filtering search results by document attributes

Retrieve locally stored Chinese A-share prices, financial statements, and valuation context through the project's shared interfaces. Look up technical indicators, inspect available data fields, and check data dates when results disagree.

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• Checking a stock's prices and valuation context
• Retrieving financial data across reporting periods
• Looking up technical indicators and their data dates

Check single-cell RNA-seq data quality, filter low-quality cells using median absolute deviation, a measure of spread, and compare plots before and after filtering. Outputs include filtered data and the original dataset with quality annotations.

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• Assess single-cell RNA-seq data quality
• Filter low-quality cells and rarely detected genes
• Compare quality plots before and after filtering

Analyze single-cell data with scvi-tools, using deep learning to combine datasets, correct differences between experiments, and transfer cell labels. Model guides and reusable scripts cover RNA, protein, chromatin accessibility, spatial data, and downstream analysis.

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• Integrate single-cell RNA datasets and correct batch effects
• Analyze paired RNA and protein or RNA and ATAC measurements
• Transfer cell-type labels from reference data

Run nf-core workflows on local sequencing files or public GEO/SRA datasets to analyze gene expression, genetic variants, or chromatin accessibility. The skill guides environment checks, sample table preparation, workflow configuration, execution, and output verification.

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• Analyze gene expression from RNA-seq data
• Identify genetic variants in WGS/WES data
• Analyze chromatin accessibility from ATAC-seq data

Review code for privacy risks, prepare data protection impact assessments, and track personal data requests and deadlines. The skill supports GDPR and German privacy compliance work, with final compliance decisions referred to a data protection officer or legal counsel.

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• Checking a service's code for privacy risks
• Preparing a data protection impact assessment
• Tracking deadlines for access and erasure requests

Turn plain language requirements into SQL, investigate slow queries, document database structures, and prepare migration templates with rollback plans. Support everyday database development and ORM use, where libraries connect application code to database tables.

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• Writing SQL for reports and data retrieval
• Investigating slow queries and repeated database calls
• Preparing schema changes and rollback plans

Write JavaScript for n8n Code nodes to aggregate, filter, and transform workflow data. Guidance covers data access, output formats, execution modes, common errors, and performance choices when processing large numbers of records.

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• Aggregating and deduplicating multiple records
• Transforming complex API responses
• Fixing data access and return format errors

Plan and configure GKE cluster networks, including private nodes, IP address ranges, DNS, and outbound connectivity. Use the guidance to set up VPC-native networking and Dataplane V2, which provides built-in network policy enforcement.

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• Designing a private GKE cluster network
• Planning IP ranges for Pods, Services, and nodes
• Configuring outbound access with a static source IP

Guides implementation of audience uploads, individual removals, and full replacements through the Data Manager API. It covers formatting and hashing identifiers, validating requests, and checking processing results for Customer Match and supported device ID audiences.

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• Upload Customer Match audience members
• Remove selected users from an audience
• Clear or replace an entire audience

Plan data ingestion and transformation workflows with Apache Airflow, Spark, and dbt. Get guidance on processing changed records, validating data quality, and rerunning failed or historical jobs without creating duplicate results.

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• Designing data ingestion and transformation workflows
• Processing only new or changed records
• Adding data quality checks between processing stages

Answer business data questions with Wren CLI by checking model definitions, reusing past queries, and executing SQL or predefined aggregations. The workflow also covers query verification, error diagnosis, and saving successful queries for future use.

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• Analyze monthly revenue trends
• Rank customers by purchase value
• Compare metrics across plans or regions