Analytics Engineering with SQL and DBT
Building Meaningful Data Models at Scale
Paperback Engels 2023 1e druk 9781098142384Samenvatting
With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL.
Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence.
With this book, you'll learn:
- What dbt is and how a dbt project is structured
- How dbt fits into the data engineering and analytics worlds
- How to collaborate on building data models
- The main tools and architectures for building useful, functional data models
- How to fit dbt into data warehousing and laking architecture
- How to build tests for data transformations
Specificaties
Lezersrecensies
Inhoudsopgave
Why We Wrote This Book
Who This Book Is For
How This Book Is Organized
Conventions Used in This Book
Using Code Examples
O’Reilly Online Learning
How to Contact Us
Acknowledgments
1. Analytics Engineering
Databases and Their Impact on Analytics Engineering
Cloud Computing and Its Impact on Analytics Engineering
The Data Analytics Lifecycle
The New Role of Analytics Engineer
Responsibilities of an Analytics Engineer
Enabling Analytics in a Data Mesh
Data Products
dbt as a Data Mesh Enabler
The Heart of Analytics Engineering
The Legacy Processes
Using SQL and Stored Procedures for ETL/ELT
Using ETL Tools
The dbt Revolution
Summary
2. Data Modeling for Analytics
A Brief on Data Modeling
The Conceptual Phase of Modeling
The Logical Phase of Modeling
The Physical Phase of Modeling
The Data Normalization Process
Dimensional Data Modeling
Modeling with the Star Schema
Modeling with the Snowflake Schema
Modeling with Data Vault
Monolith Data Modeling
Building Modular Data Models
Enabling Modular Data Models with dbt
Testing Your Data Models
Generating Data Documentation
Debugging and Optimizing Data Models
Medallion Architecture Pattern
Summary
3. SQL for Analytics
The Resiliency of SQL
Database Fundamentals
Types of Databases
Database Management System
“Speaking” with a Database
Creating and Managing Your Data Structures with DDL
Manipulating Data with DML
Inserting Data with INSERT
Selecting Data with SELECT
Updating Data with UPDATE
Deleting Data with DELETE
Storing Queries as Views
Common Table Expressions
Window Functions
Data Manipulation with DuckDB
Data Manipulation with Polars
Data Manipulation with FugueSQL
Bonus: Training Machine Learning Models with SQL
Summary
4. Data Transformation with dbt
dbt Design Philosophy
dbt Data Flow
dbt Cloud
Setting Up dbt Cloud with BigQuery and GitHub
Using the dbt Cloud UI
Using the dbt Cloud IDE
Structure of a dbt Project
Jaffle Shop Database
YAML Files
Models
Sources
Tests
Analyses
Seeds
Documentation
dbt Commands and Selection Syntax
Jobs and Deployment
Summary
5. dbt Advanced Topics
Model Materializations
Tables, Views, and Ephemeral Models
Incremental Models
Materialized Views
Snapshots
Dynamic SQL with Jinja
Using SQL Macros
dbt Packages
Installing Packages
Exploring the dbt_utils Package
Using Packages Inside Macros and Models
dbt Semantic Layer
Summary
6. Building an End-to-End Analytics Engineering Use Case
Problem Definition: An Omnichannel Analytics Case
Operational Data Modeling
Conceptual Model
Logical Model
Physical Model
High-Level Data Architecture
Analytical Data Modeling
Identify the Business Processes
Identify Facts and Dimensions in the Dimensional Data Model
Identify the Attributes for Dimensions
Define the Granularity for Business Facts
Creating Our Data Warehouse with dbt
Tests, Documentation, and Deployment with dbt
Data Analytics with SQL
Conclusion
Index
About the Authors
Anderen kochten ook
Tieme Woldman€ 29,99
Piethein Strengholt€ 69,24
Tomer Shiran€ 80,62
Markus Enhrenmueller-Jensen€ 80,62
James Serra€ 91,99
George Mount€ 69,24
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan