Dustin Dorsey

This book shows how dbt is used to build data transformation pipelines that enable dependency management and allow for version control and automated testing. It explains how dbt is revolutionizing data transformation and the advantages that a command-line tool like dbt provides over and above the use of database stored procedures and other ETL and ELT tools that handle data transformations. You’ll see how to create custom-written transformations through simple SQL SELECT statements, eliminating the need for boilerplate code and making it easy to incorporate dbt as the transformation layer in your data warehouse pipelines. Additionally, you will learn how dbt enables data teams to incorporate software engineering best practices such as code reusability, version control, and automated testing into the data transformation process. Unlocking dbt walks you through using dbt to establish a project, build and modularize SQL models, and execute jobs in away that is easy to maintain and scale as your data ecosystem matures. You’ll begin by establishing and configuring a project, a process covered using both dbt Cloud and dbt Core, so that you can confidently stand up a project using either platform. From there, you’ll move into building transformations with peace of mind that your project will scale appropriately as you continue to develop it. After learning the basics needed to get started, you’ll continue to build on that foundation by looking at the unique ways in which dbt combines SQL with Jinja to take your code beyond what is capable in normal SQL. You will learn about advanced materializations, building lineage in your data flows, the unlimited potential of macros, and so much more. This book also explores supported file types and the building of Python models. Rounding things out, you will learn features of dbt that will assist you in making your transformation layer production ready. These includehow to implement automated testing, using dbt to generate documentation, and running CI/CD pipelines. What You Will Learn Understand what dbt is and how it is used in the modern data stackSet up a project using both dbt Cloud and dbt CoreConnect a dbt project to a cloud data warehouseBuild SQL and Python models that are scalable and maintainableConfigure development, testing, and production environmentsCapture reusable logic in the form of Jinja macrosIncorporate version control with your data transformation code Who This Book Is For Current and aspiring data professionals, including architects, developers, analysts, engineers, data scientists, and consultants who are beginning the journey of using dbt as part of their data pipeline’s transformation layer. Readers should have a foundational knowledge of writing basic SQL statements, development best practices, and working with data in an analytical context such as a data warehouse.

Migrate your existing, on-premises applications into the Microsoft Azure cloud platform. This book covers the best practices to plan, implement, and operationalize the migration of a database application from your organization’s data center to Microsoft’s Azure cloud platform.Data modernization and migration is a technologically complex endeavor that can also be taxing from a leadership and operational standpoint. This book covers not only the technology, but also the most important aspects of organization culture, communication, and politics that so frequently derail such projects. You will learn the most important steps to ensuring a successful migration and see battle-tested wisdom from industry veterans. From executive sponsorship, to executing the migration, to the important steps following migration, you will learn how to effectively conduct future migrations and ensure that your team and your database application delivers on the expected business value of the project. This book is unlike any other currently in the market. It takes you through the most critical business and technical considerations and workflows for moving your data and databases into the cloud, with special attention paid to those who are deploying to the Microsoft Data Platform in Azure, especially SQL Server. Although this book focuses on migrating on-premises SQL Server enterprises to hybrid or fully cloud-based Azure SQL Database and Azure SQL Managed Instances, it also cover topics involving migrating non-SQL Server database platforms such as Oracle, MySQL, and PostgreSQL applications to Microsoft Azure.What You Will LearnPlan a database migration that ensures smooth project progress, optimal performance, low operating cost, and minimal downtimeProperly analyze and manage non-technical considerations, such as legal compliance, privacy, and team executionPerform athorough architectural analysis to select the best Azure services, performance tiers, and cost-containment featuresAvoid pitfalls and common reasons for failure relating to corporate culture, intra-office politics, and poor communicationsSecure the proper executive champions who can execute the business planning needed for successApply proven criteria to determine your future-state architecture and your migration methodExecute your migration using a process proven by the authors over years of successful projectsWho This Book Is ForIT leadership, strategic IT decision makers, project owners and managers, and enterprise and application architects. For anyone looking toward cloud migration projects as the next stage of growth in their careers. Also useful for enterprise DBAs and consultants who might be involved in such projects. Readers should have experience and be competent in designing, coding, implementing, and supporting database applications in an on-premises environment.