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Architect, Build, and Optimize Your Data Warehouse


Are you ready to revolutionize the way your organization stores and accesses data? "Mastering Data Warehousing" is your definitive guide to architecting, building, and optimizing data warehouses that facilitate efficient data storage and retrieval. Whether you're a data architect designing robust warehouse structures or a business leader aiming to glean insights from your data, this book equips you with the knowledge and strategies to master the art of data warehousing.

Mastering Data Warehousing

  • 1.Introduction to Data Warehousing
    1.1.Understanding the Need for Data Warehousing
    1.2.The Evolution of Data Warehousing
    1.3.Key Concepts and Terminology
    1.4.Benefits and Challenges of Data Warehousing
    2.Data Warehouse Architecture
    2.1.Components of a Data Warehouse
    2.2.Data Warehouse Models: Inmon vs. Kimball
    2.3.Extract, Transform, Load (ETL) Processes
    2.4.Data Warehousing in the Cloud
    3.Designing a Data Warehouse
    3.1.Dimensional Modeling Concepts
    3.2.Fact and Dimension Tables
    3.3.Star Schema and Snowflake Schema
    3.4.Slowly Changing Dimensions (SCD)
    4.ETL and Data Integration
    4.1.ETL Workflow and Processes
    4.2.Data Transformation Techniques
    4.3.Data Cleansing and Quality Assurance
    4.4.Change Data Capture (CDC) Strategies
    5.Data Warehouse Storage and Management
    5.1.Choosing the Right Storage Solutions
    5.2.Data Compression and Partitioning
    5.3.Indexing Strategies for Performance
    5.4.Data Archiving and Retention Policies
    6.Data Warehouse Querying and Optimization
    6.1.SQL Basics for Data Warehousing
    6.2.Query Optimization Techniques
    6.3.Materialized Views and Query Performance
    6.4.Parallel Processing and In-Memory Databases
    7.Data Warehousing for Business Intelligence
    7.1.Enabling Business Decision-Making
    7.2.Data Visualization and Reporting Tools
    7.3.Self-Service BI and Dashboards
    7.4.Advanced Analytics in the Data Warehouse
    8.Data Security and Governance in Data Warehousing
    8.1.Ensuring Data Privacy and Security
    8.2.Data Governance Frameworks
    8.3.Auditing and Compliance in Data Warehousing
    8.4.Data Lineage and Metadata Management
    9.Scalability and Performance Tuning
    9.1.Scaling Up vs. Scaling Out
    9.2.Data Warehouse Performance Bottlenecks
    9.3.Monitoring and Tuning for Performance
    9.4.Predictive Analytics for Workload Management
    10.Advanced Data Warehousing Concepts
    10.1.Data Warehousing in Real-Time
    10.2.Federated Data Warehousing
    10.3.NoSQL and Unstructured Data in the Warehouse
    10.4.Geospatial and Temporal Data Warehousing
    11.Data Warehousing in Industry Domains
    11.1.Healthcare Data Warehousing
    11.2.Retail and E-commerce Data Warehousing
    11.3.Financial Services Data Warehousing
    11.4.Manufacturing and Supply Chain Data Warehousing
    12.Data Warehousing for Big Data and IoT
    12.1.Integrating Big Data into Data Warehousing
    12.2.Data Warehousing Challenges in IoT
    12.3.Processing and Analyzing Streaming Data in the Warehouse
    12.4.Building Data Lakes with Data Warehousing
    13.Data Warehousing Best Practices
    13.1.Collaboration between IT and Business Users
    13.2.Data Warehousing Project Management
    13.3.Common Mistakes and How to Avoid Them
    13.4.Future-Proofing Your Data Warehouse
    14.Future Trends in Data Warehousing
    14.1.Data Warehousing in the Age of AI and ML
    14.2.Quantum Computing Impact on Data Warehousing
    14.3.Hybrid Cloud Data Warehousing
    14.4.Ethical Considerations in Data Warehousing
    15.Building Your Data Warehousing Strategy
    15.1.Assessing Business Needs and Goals
    15.2.Selecting the Right Tools and Technologies
    15.3.Creating a Roadmap for Successful Data Warehousing
    16.1.Glossary of Data Warehousing Terms
    16.2.Recommended Tools and Resources
    16.3.Interviews with Data Warehousing Experts
    16.4.Sample Data Warehousing Project Plan
    About the author

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