The Self-Service Data Roadmap

Spis treści książki

• Preface
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
• 1. Introduction
  • Journey Map from Raw Data to Insights
    • Discover
      • Discovering a datasets metadata details
      • Searching available datasets and artifacts
      • Reusing or creating features for ML models
      • Aggregating missing data
      • Managing clickstream events
    • Prep
      • Managing aggregated data within a central repository
      • Structuring, cleaning, enriching, and validating data
      • Ensuring data rights compliance
    • Build
      • Deciding the best approach for accessing and analyzing data
      • Writing transformation logic
      • Training the models
      • Continuously integrating ML model changes
      • A/B testing of insights
    • Operationalize
      • Verifying and optimizing queries
      • Orchestrating pipelines
      • Deploying the ML models
      • Monitoring the quality of the insights
      • Continuous cost monitoring
  • Defining Your Time-to-Insight Scorecard
  • Build Your Self-Service Data Roadmap
• I. Self-Service Data Discovery
• 2. Metadata Catalog Service
  • Journey Map
    • Understanding Datasets
    • Analyzing Datasets
    • Knowledge Scaling
  • Minimizing Time to Interpret
    • Extracting Technical Metadata
    • Extracting Operational Metadata
    • Gathering Team Knowledge
  • Defining Requirements
    • Technical Metadata Extractor Requirements
    • Operational Metadata Requirements
    • Team Knowledge Aggregator Requirements
  • Implementation Patterns
    • Source-Specific Connectors Pattern
    • Lineage Correlation Pattern
    • Team Knowledge Pattern
  • Summary
• 3. Search Service
  • Journey Map
    • Determining Feasibility of the Business Problem
    • Selecting Relevant Datasets for Data Prep
    • Reusing Existing Artifacts for Prototyping
  • Minimizing Time to Find
    • Indexing Datasets and Artifacts
    • Ranking Results
    • Access Control
  • Defining Requirements
    • Indexer Requirements
    • Ranking Requirements
    • Access Control Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Push-Pull Indexer Pattern
    • Hybrid Search Ranking Pattern
    • Catalog Access Control Pattern
  • Summary
• 4. Feature Store Service
  • Journey Map
    • Finding Available Features
    • Training Set Generation
    • Feature Pipeline for Online Inference
  • Minimize Time to Featurize
    • Feature Computation
    • Feature Serving
  • Defining Requirements
    • Feature Computation
    • Feature Serving
      • Feature groups
      • Scaling
      • Feature analysis
    • Nonfunctional Requirements
  • Implementation Patterns
    • Hybrid Feature Computation Pattern
    • Feature Registry Pattern
  • Summary
• 5. Data Movement Service
  • Journey Map
    • Aggregating Data Across Sources
    • Moving Raw Data to Specialized Query Engines
    • Moving Processed Data to Serving Stores
    • Exploratory Analysis Across Sources
  • Minimizing Time to Data Availability
    • Data Ingestion Configuration and Change Management
    • Compliance
    • Data Quality Verification
  • Defining Requirements
    • Ingestion Requirements
      • Source and target datastore technologies
      • Data scale
      • Acceptable refresh lag
    • Transformation Requirements
    • Compliance Requirements
    • Verification Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Batch Ingestion Pattern
    • Change Data Capture Ingestion Pattern
    • Event Aggregation Pattern
  • Summary
• 6. Clickstream Tracking Service
  • Journey Map
  • Minimizing Time to Click Metrics
    • Managing Instrumentation
    • Event Enrichment
    • Building Insights
  • Defining Requirements
    • Instrumentation Requirements Checklist
    • Enrichment Requirements Checklist
  • Implementation Patterns
    • Instrumentation Pattern
    • Rule-Based Enrichment Patterns
      • Bot-filtering pattern
      • Sessionization pattern
      • User context enrichment pattern
    • Consumption Patterns
  • Summary
• II. Self-Service Data Prep
• 7. Data Lake Management Service
  • Journey Map
    • Primitive Life Cycle Management
    • Managing Data Updates
    • Managing Batching and Streaming Data Flows
  • Minimizing Time to Data Lake Management
    • Requirements
      • Namespace zones
      • Supported file formats
      • Serving layers
        • Key-value data model
        • Wide-column data model
        • Document data model
        • Graph data model
  • Implementation Patterns
    • Data Life Cycle Primitives Pattern
      • Schema evolution
      • Data versioning
      • Incremental updates
    • Transactional Pattern
    • Advanced Data Management Pattern
  • Summary
• 8. Data Wrangling Service
  • Journey Map
  • Minimizing Time to Wrangle
    • Defining Requirements
    • Curating Data
    • Operational Monitoring
  • Defining Requirements
  • Implementation Patterns
    • Exploratory Data Analysis Patterns
    • Analytical Transformation Patterns
  • Summary
• 9. Data Rights Governance Service
  • Journey Map
    • Executing Data Rights Requests
    • Discovery of Datasets
    • Model Retraining
  • Minimizing Time to Comply
    • Tracking the Customer Data Life Cycle
    • Executing Customer Data Rights Requests
    • Limiting Data Access
  • Defining Requirements
    • Current Pain Point Questionnaire
    • Interop Checklist
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Sensitive Data Discovery and Classification Pattern
    • Data Lake Deletion Pattern
    • Use CaseDependent Access Control
  • Summary
• III. Self-Service Build
• 10. Data Virtualization Service
  • Journey Map
    • Exploring Data Sources
    • Picking a Processing Cluster
  • Minimizing Time to Query
    • Picking the Execution Environment
    • Formulating Polyglot Queries
    • Joining Data Across Silos
  • Defining Requirements
    • Current Pain Point Analysis
    • Operational Requirements
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Automatic Query Routing Pattern
    • Unified Query Pattern
    • Federated Query Pattern
  • Summary
• 11. Data Transformation Service
  • Journey Map
    • Production Dashboard and ML Pipelines
    • Data-Driven Storytelling
  • Minimizing Time to Transform
    • Transformation Implementation
    • Transformation Execution
    • Transformation Operations
  • Defining Requirements
    • Current State Questionnaire
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Implementation Pattern
    • Execution Patterns
  • Summary
• 12. Model Training Service
  • Journey Map
    • Model Prototyping
    • Continuous Training
    • Model Debugging
  • Minimizing Time to Train
    • Training Orchestration
    • Tuning
    • Continuous Training
  • Defining Requirements
    • Training Orchestration
    • Tuning
    • Continuous Training
    • Nonfunctional Requirements
  • Implementation Patterns
    • Distributed Training Orchestrator Pattern
    • Automated Tuning Pattern
    • Data-Aware Continuous Training
  • Summary
• 13. Continuous Integration Service
  • Journey Map
    • Collaborating on an ML Pipeline
    • Integrating ETL Changes
    • Validating Schema Changes
  • Minimizing Time to Integrate
    • Experiment Tracking
    • Reproducible Deployment
    • Testing Validation
  • Defining Requirements
    • Experiment Tracking Module
    • Pipeline Packaging Module
    • Testing Automation Module
  • Implementation Patterns
    • Programmable Tracking Pattern
    • Reproducible Project Pattern
  • Summary
• 14. A/B Testing Service
  • Journey Map
  • Minimizing Time to A/B Test
    • Experiment Design
    • Execution at Scale
    • Experiment Optimization
  • Implementation Patterns
    • Experiment Specification Pattern
    • Metrics Definition Pattern
    • Automated Experiment Optimization
  • Summary
• IV. Self-Service Operationalize
• 15. Query Optimization Service
  • Journey Map
    • Avoiding Cluster Clogs
    • Resolving Runtime Query Issues
    • Speeding Up Applications
  • Minimizing Time to Optimize
    • Aggregating Statistics
    • Analyzing Statistics
    • Optimizing Jobs
  • Defining Requirements
    • Current Pain Points Questionnaire
    • Interop Requirements
    • Functionality Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Avoidance Pattern
    • Operational Insights Pattern
    • Automated Tuning Pattern
  • Summary
• 16. Pipeline Orchestration Service
  • Journey Map
    • Invoke Exploratory Pipelines
    • Run SLA-Bound Pipelines
  • Minimizing Time to Orchestrate
    • Defining Job Dependencies
    • Distributed Execution
    • Production Monitoring
  • Defining Requirements
    • Current Pain Points Questionnaire
    • Operational Requirements
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Dependency Authoring Patterns
    • Orchestration Observability Patterns
    • Distributed Execution Pattern
  • Summary
• 17. Model Deploy Service
  • Journey Map
    • Model Deployment in Production
    • Model Maintenance and Upgrade
  • Minimizing Time to Deploy
    • Deployment Orchestration
    • Performance Scaling
    • Drift Monitoring
  • Defining Requirements
    • Orchestration
      • Deployment endpoints
      • Model formats
      • Model deployment scenarios
    • Model Scaling and Performance
    • Drift Verification
    • Nonfunctional Requirements
  • Implementation Patterns
    • Universal Deployment Pattern
    • Autoscaling Deployment Pattern
    • Model Drift Tracking Pattern
  • Summary
• 18. Quality Observability Service
  • Journey Map
    • Daily Data Quality Monitoring Reports
    • Debugging Quality Issues
    • Handling Low-Quality Data Records
  • Minimizing Time to Insight Quality
    • Verify the Accuracy of the Data
    • Detect Quality Anomalies
    • Prevent Data Quality Issues
  • Defining Requirements
    • Detection and Handling Data Quality Issues
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Accuracy Models Pattern
    • Profiling-Based Anomaly Detection Pattern
    • Avoidance Pattern
  • Summary
• 19. Cost Management Service
  • Journey Map
    • Monitoring Cost Usage
    • Continuous Cost Optimization
  • Minimizing Time to Optimize Cost
    • Expenditure Observability
    • Matching Supply and Demand
    • Continuous Cost Optimization
  • Defining Requirements
    • Pain Points Questionnaire
    • Functional Requirements
    • Nonfunctional Requirements
  • Implementation Patterns
    • Continuous Cost Monitoring Pattern
    • Automated Scaling Pattern
    • Cost Advisor Pattern
  • Summary
• Index

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