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Analytics Engineering with SQL and Dbt: Building Meaningful Data Models at Scale

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Item specifics

Condition
Very Good: A book that has been read but is in excellent condition. No obvious damage to the cover, ...
Brand
O'Reilly Media
Binding
TP
EAN
9781098142384
ISBN
1098142381
Book Title
Analytics Engineering with SQL and Dbt: Building M
Manufacturer
O'Reilly Media

About this product

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1098142381
ISBN-13
9781098142384
eBay Product ID (ePID)
14060882410

Product Key Features

Number of Pages
321 Pages
Language
English
Publication Name
Analytics Engineering with Sql and Dbt : Building Meaningful Data Models at Scale
Publication Year
2024
Subject
Programming Languages / Sql, Data Processing, Databases / Data Mining
Type
Textbook
Subject Area
Computers
Author
Helder Russa, Rui Pedro Machado
Format
Trade Paperback

Dimensions

Item Height
1.1 in
Item Weight
19.3 Oz
Item Length
9.2 in
Item Width
7 in

Additional Product Features

Synopsis
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. The data build tool (dbt) helps you take data further. This practical book shows data analysts, data engineers, Bl developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Fraudio 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. With this book, you'll learn: Essentials of data modeling techniques and their role in analytics engineering, Essentials of creating and maintaining databases with SQL, How SQL can be used to deliver data analytics insights and reports, The main tools and architectures for building useful, functional data models, What dbt is and how a dbt project is structured, How dbt fits into the data engineering and analytics worlds, How to build tests for data transformations, 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

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