The Informed Company : How to Build Modern Agile Data Stacks That Drive Winning Insights.

Cover -- Title Page -- Copyright Page -- Contents -- About This Book -- Why Write This Book -- Who This Book Is For -- Who This Book Is Not For -- Who Wrote the Book -- Who Edited the Book -- Influences -- How This Book Was Written -- How to Read This Book -- Foreword -- Introduction -- Merging Business Context with Data Information -- The Four Stages of Agile Data Organization -- Stage 1 Source aka Siloed Data -- Chapter 1 Starting with Source Data -- Common Options for Analyzing Source Data -- Chapter 2 The Need to Replicate Source Data -- Replicate Sources -- Create Read-OnlyAccess -- Chapter 3 Source Data Best Practices -- Keep a Complexity Wiki Page -- Snippet Dictionary -- Use a BI Product -- Double Check Results -- Keep Short Dashboards -- Design Before Building -- Stage 2 Data Lake aka Data Combined -- Chapter 4 Why Build a Data Lake? -- What Is a Data Lake? -- Reasons to Build a Data Lake Summarized -- Chapter 5 Choosing an Engine for the Data Lake -- Modern Columnar Warehouse Engines -- Modern Warehouse Engine Products -- Database Engines -- Recommendation -- Chapter 6 Extract and Load (EL) Data -- ETL versus ELT -- EL/ETL Vendors -- Extract Options -- Load Options -- Multiple Schemas -- Other Extract and Load Routes -- Chapter 7 Data Lake Security -- Access in Central Place -- Permission Tiers -- Chapter 8 Data Lake Maintenance -- Why SQL? -- Data Sources -- Performance -- Upgrade Snippets to Views -- Stage 3 Data Warehouse aka the Single Source of Truth -- Chapter 9 The Power of Layers and Views -- Make Readable Views -- Layer Views on Views -- Start with a Single View -- Chapter 10 Staging Schemas -- Orient to the Schemas -- Pick a Table and Clean It -- Other Staging Modeling Considerations -- Building on Top of Staging Schemas -- Chapter 11 Model Data with dbt -- Version Control -- Modularity and Reusability -- Package Management.

Organizing Files -- Macros -- Incremental Tables -- Testing -- Chapter 12 Deploy Modeling Code -- Branch Using Version Control Software -- Commit Message -- Test Locally -- Code Review -- Schedule Runs -- Chapter 13 Implementing the Data Warehouse -- Manage Dependencies -- Combine Tables Within Schemas -- Combine Tables Across Schemas -- Keep the Grain Consistent -- Create Business Metrics -- Keeping Accurate History -- Chapter 14 Managing Data Access -- How to Secure Sensitive Data in the Data Warehouse -- How to Secure Sensitive Data in a BI Tool -- Chapter 15 Maintaining the Source of Truth -- Track New Metrics -- Deprecate Old Metrics -- Deprecate Old Schemas -- Resolve Conflicting Numbers -- Handling Ongoing Requests and Ongoing Feedback -- Updating Modeling Code -- Manage Access -- Tuning to Optimize -- Code Review All Modeling -- Maintenance Checklist -- Stage 4 Data Marts aka Data Democratized -- Chapter 16 Data Mart Implementation -- Views on the Data Warehouse -- Segment Tables -- Access Update -- Chapter 17 Data Mart Maintenance -- Educate Team -- Identifies Issues -- Identify New Needs -- Help Track Success -- Chapter 18 Modern versus Traditional Data Stacks: What's Changed? -- What's Changed? -- Chapter 19 Row- versus Column-Oriented Database -- Row-Oriented Databases -- Column-Oriented Databases -- Summary -- Chapter 20 Style Guide Example -- Simplify -- Clean -- Naming Conventions -- Share It -- Chapter 21 Building an SST Example -- First Attempt-Same Tables with Prefixes -- Second Attempt-Operational Schema (Source Agnostic) -- Third Attempt-Application Separate, Other Sources Smashed -- Less Planning, More Implementing -- Acknowledgments and Contributions -- Thank-yous -- Index -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.