~로 Data Virtualization 단일한 의미론적 가상 레이어를 통해 여러 출처의 물리적 데이터에 접근할 수 있습니다. 이 가상 레이어는 데이터의 물리적 형식이나 위치를 알 필요도 없고, 데이터를 이동하거나 복사할 필요도 없이 데이터에 접근하고, 조작하고, 분석할 수 있음을 의미합니다.
Data Virtualization ' IBM
Cloud 자격 증명을 사용하여 서비스에 연결합니다. 특정 작업을 수행하려면 특정 Data Virtualization 역할이 있어야 합니다. 더 자세한 정보는 Data Virtualization 서비스에 연결하고 인증하기를 참고하세요.
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시작하려면 Data Virtualization, 다음의 고수준 단계를 따르십시오:
열기 Data Virtualization 서비스.
에서 Cloud Pak for Data 탐색 메뉴에서 데이터 > Data virtualization 선택하세요.
데이터 소스를 Data Virtualization.
데이터 소스 페이지 로 이동한 다음 연결 추가를 선택하여 연결을 추가합니다. Data Virtualization 수십 개의 관계형 및 비관계형 데이터 소스를 지원합니다.
데이터 소스의 테이블을 가상화합니다.
가상화 페이지 에서 가상화하려는 테이블을 선택한 다음 장바구니에 담기 > 장바구니 보기 버튼 을 선택하여 테이블을 가상화합니다.
테이블에 참여하여 통합된 보기를 만드십시오.
가상화된 데이터 페이지 에서 조인하려는 테이블을 선택한 다음 조인을 선택하여 객체를 조인합니다.
가상 객체를 쿼리합니다.
SQL 실행 페이지로 이동하여 내장된 SQL 편집기를 사용하여 가상 객체를 쿼리합니다.
데이터 패브릭의 다른 Cloud Pak for Data 서비스를 사용하여 데이터를 소비합니다.
프로젝트, 대시보드, 데이터 카탈로그, 기타 응용 프로그램에서 가상 테이블을 사용합니다. 더 자세한 정보를 원하시면, 대시보드 서비스를 참고하세요.
Use this interactive map to learn about the relationships between your tasks, the tools you need, the services that provide the tools, and where you use the tools.
Select any task, tool, service, or workspace
You'll learn what you need, how to get it, and where to use it.
Some tools perform the same tasks but have different features and levels of automation.
Jupyter notebook editor
Prepare data
Visualize data
Build models
Deploy assets
Create a notebook in which you run Python, R, or Scala code to prepare, visualize, and analyze data, or build a model.
AutoAI
Build models
Automatically analyze your tabular data and generate candidate model pipelines customized for your predictive modeling problem.
SPSS Modeler
Prepare data
Visualize data
Build models
Create a visual flow that uses modeling algorithms to prepare data and build and train a model, using a guided approach to machine learning that doesn’t require coding.
Decision Optimization
Build models
Visualize data
Deploy assets
Create and manage scenarios to find the best solution to your optimization problem by comparing different combinations of your model, data, and solutions.
Data Refinery
Prepare data
Visualize data
Create a flow of ordered operations to cleanse and shape data. Visualize data to identify problems and discover insights.
Orchestration Pipelines
Prepare data
Build models
Deploy assets
Automate the model lifecycle, including preparing data, training models, and creating deployments.
RStudio
Prepare data
Build models
Deploy assets
Work with R notebooks and scripts in an integrated development environment.
Federated learning
Build models
Create a federated learning experiment to train a common model on a set of remote data sources. Share training results without sharing data.
Deployments
Deploy assets
Monitor models
Deploy and run your data science and AI solutions in a test or production environment.
Catalogs
Catalog data
Governance
Find and share your data and other assets.
Metadata import
Prepare data
Catalog data
Governance
Import asset metadata from a connection into a project or a catalog.
Metadata enrichment
Prepare data
Catalog data
Governance
Enrich imported asset metadata with business context, data profiling, and quality assessment.
Data quality rules
Prepare data
Governance
Measure and monitor the quality of your data.
Masking flow
Prepare data
Create and run masking flows to prepare copies of data assets that are masked by advanced data protection rules.
Governance
Governance
Create your business vocabulary to enrich assets and rules to protect data.
Data lineage
Governance
Track data movement and usage for transparency and determining data accuracy.
AI factsheet
Governance
Monitor models
Track AI models from request to production.
DataStage flow
Prepare data
Create a flow with a set of connectors and stages to transform and integrate data. Provide enriched and tailored information for your enterprise.
Data virtualization
Prepare data
Create a virtual table to segment or combine data from one or more tables.
OpenScale
Monitor models
Measure outcomes from your AI models and help ensure the fairness, explainability, and compliance of all your models.
Data replication
Prepare data
Replicate data to target systems with low latency, transactional integrity and optimized data capture.
Master data
Prepare data
Consolidate data from the disparate sources that fuel your business and establish a single, trusted, 360-degree view of your customers.
Services you can use
Services add features and tools to the platform.
watsonx.ai Studio
Develop powerful AI solutions with an integrated collaborative studio and industry-standard APIs and SDKs. Formerly known as Watson Studio.
watsonx.ai Runtime
Quickly build, run and manage generative AI and machine learning applications with built-in performance and scalability. Formerly known as Watson Machine Learning.
IBM Knowledge Catalog
Discover, profile, catalog, and share trusted data in your organization.
DataStage
Create ETL and data pipeline services for real-time, micro-batch, and batch data orchestration.
Data Virtualization
View, access, manipulate, and analyze your data without moving it.
Watson OpenScale
Monitor your AI models for bias, fairness, and trust with added transparency on how your AI models make decisions.
Data Replication
Provide efficient change data capture and near real-time data delivery with transactional integrity.
Match360 with Watson
Improve trust in AI pipelines by identifying duplicate records and providing reliable data about your customers, suppliers, or partners.
Manta Data Lineage
Increase data pipeline transparency so you can determine data accuracy throughout your models and systems.
Where you'll work
Collaborative workspaces contain tools for specific tasks.
Project
Where you work with data.
> Projects > View all projects
Catalog
Where you find and share assets.
> Catalogs > View all catalogs
Space
Where you deploy and run assets that are ready for testing or production.
> Deployments
Categories
Where you manage governance artifacts.
> Governance > Categories
Data virtualization
Where you virtualize data.
> Data > Data virtualization
Master data
Where you consolidate data into a 360 degree view.