کتاب مدیریت داده در مقیاس بزرگ، ویرایش دوم

سفر به سوی داده‌محور شدن

Recent Technology Developments and Industry Trends • Data Management • Analytics Is Fragmenting the Data Landscape • The Speed of Software Delivery Is Changing • The Cloud’s Impact on Data Management Is Immeasurable • Privacy and Security Concerns Are a Top Priority • Operational and Analytical Systems Need to Be Integrated • Organizations Operate in Collaborative Ecosystems • Enterprises Are Saddled with Outdated Data Architectures • The Enterprise Data Warehouse: A Single Source of Truth • The Data Lake: A Centralized Repository for Structured and Unstructured Data • The Pain of Centralization • Defining a Data Strategy • Wrapping Up

سازماندهی داده‌ها با استفاده از دامنه‌های داده

Application Design Starting Points • Each Application Has a Data Store • Applications Are Always Unique • Golden Sources • The Data Integration Dilemma • Application Roles • Inspirations from Software Architecture • Data Domains • Domain-Driven Design • Business Architecture • Domain Characteristics • Principles for Distributed and Domain-Oriented Data Management • Design Principles for Data Domains • Best Practices for Data Providers • Domain Ownership Responsibilities • Transitioning Toward Distributed and Domain-Oriented Data Management • Wrapping Up

نگاشت دامنه‌ها به یک معماری فناوری

Domain Topologies: Managing Problem Spaces • Fully Federated Domain Topology • Governed Domain Topology • Partially Federated Domain Topology • Value Chain–Aligned Domain Topology • Coarse-Grained Domain Topology • Coarse-Grained and Partially Governed Domain Topology • Centralized Domain Topology • Picking the Right Topology • Landing Zone Topologies: Managing Solution Spaces • Single Data Landing Zone • Source- and Consumer-Aligned Landing Zones • Hub Data Landing Zone • Multiple Data Landing Zones • Multiple Data Management Landing Zones • Practical Landing Zones Example • Wrapping Up

مدیریت محصول داده

What Are Data Products? • Problems with Combining Code, Data, Metadata, and Infrastructure • Data Products as Logical Entities • Data Product Design Patterns • What Is CQRS? • Read Replicas as Data Products • Design Principles for Data Products • Resource-Oriented Read-Optimized Design • Data Product Data Is Immutable • Using the Ubiquitous Language • Capture Directly from the Source • Clear Interoperability Standards • No Raw Data • Don’t Conform to Consumers • Missing Values, Defaults, and Data Types • Semantic Consistency • Atomicity • Compatibility • Abstract Volatile Reference Data • New Data Means New Ownership • Data Security Patterns • Establish a Metamodel • Allow Self-Service • Cross-Domain Relationships • Enterprise Consistency • Historization, Redeliveries, and Overwrites • Business Capabilities with Multiple Owners • Operating Model • Data Product Architecture • High-Level Platform Design • Capabilities for Capturing and Onboarding Data • Data Quality • Data Historization • Solution Design • Real-World Example • Alignment with Storage Accounts • Alignment with Data Pipelines • Capabilities for Serving Data • Data Serving Services • File Manipulation Service • De-Identification Service • Distributed Orchestration • Intelligent Consumption Services • Direct Usage Considerations • Getting Started • Wrapping Up

مدیریت سرویس‌ها و API

Introducing API Management • What Is Service-Oriented Architecture? • Enterprise Application Integration • Service Orchestration • Service Choreography • Public Services and Private Services • Service Models and Canonical Data Models • Parallels with Enterprise Data Warehousing Architecture • A Modern View of API Management • Federated Responsibility Model • API Gateway • API as a Product • Composite Services • API Contracts • API Discoverability • Microservices • Functions • Service Mesh • Microservice Domain Boundaries • Ecosystem Communication • Experience APIs • GraphQL • Backend for Frontend • Practical Example • Metadata Management • Read-Oriented APIs Serving Data Products • Wrapping Up

مدیریت رویداد و اعلان

Introduction to Events • Notifications Versus Carried State • The Asynchronous Communication Model • What Do Modern Event-Driven Architectures Look Like? • Message Queues • Event Brokers • Event Processing Styles • Event Producers • Event Consumers • Event Streaming Platforms • Governance Model • Event Stores as Data Product Stores • Event Stores as Application Backends • Streaming as the Operational Backbone • Guarantees and Consistency • Consistency Level • Processing Methods • Message Order • Dead Letter Queue • Streaming Interoperability • Governance and Self-Service • Wrapping Up

اتصال نقاط

Cross-Domain Interoperability • Quick Recap • Data Distribution Versus Application Integration • Data Distribution Patterns • Application Integration Patterns • Consistency and Discoverability • Inspiring, Motivating, and Guiding for Change • Setting Domain Boundaries • Exception Handling • Organizational Transformation • Team Topologies • Organizational Planning • Wrapping Up

حاکمیت داده و امنیت داده

Data Governance • The Governance Framework • Processes: Data Governance Activities • Making Governance Effective and Pragmatic • Supporting Services for Data Governance • Data Contracts • Data Security • Current Siloed Approach • Trust Boundaries • Data Classifications and Labels • Data Usage Classifications • Unified Data Security • Identity Providers • Real-World Example • Typical Security Process Flow • Securing API-Based Architectures • Securing Event-Driven Architectures • Wrapping Up

دموکراتیک کردن داده‌ها با فراداده

Metadata Management • The Enterprise Metadata Model • Practical Example of a Metamodel • Data Domains and Data Products • Data Models • Data Lineage • Other Metadata Areas • The Metalake Architecture • Role of the Catalog • Role of the Knowledge Graph • Wrapping Up

مدیریت داده اصلی مدرن

Master Data Management Styles • Data Integration • Designing a Master Data Management Solution • Domain-Oriented Master Data Management • Reference Data • Master Data • MDM and Data Quality as a Service • MDM and Data Curation • Knowledge Exchange • Integrated Views • Reusable Components and Integration Logic • Republishing Data Through Integration Hubs • Republishing Data Through Aggregates • Data Governance Recommendations • Wrapping Up

تبدیل داده به ارزش

The Challenges of Turning Data into Value • Domain Data Stores • Granularity of Consumer-Aligned Use Cases • DDSs Versus Data Products • Best Practices • Business Requirements • Target Audience and Operating Model • Nonfunctional Requirements • Data Pipelines and Data Models • Scoping the Role Your DDSs Play • Business Intelligence • Semantic Layers • Self-Service Tools and Data • Best Practices • Advanced Analytics (MLOps) • Initiating a Project • Experimentation and Tracking • Data Engineering • Model Operationalization • Exceptions • Wrapping Up

به کارگیری تئوری در عمل

A Brief Reflection on Your Data Journey • Centralized or Decentralized? • Making It Real • Opportunistic Phase: Set Strategic Direction • Transformation Phase: Lay Out the Foundation • Optimization Phase: Professionalize Your Capabilities • Data-Driven Culture • DataOps • Governance and Literacy • The Role of Enterprise Architects • Blueprints and Diagrams • Modern Skills • Control and Governance • Last Words