- We will send in 10–14 business days.
/images/books/10331037/9781492044468.jpg)
- Author: Valliappa Lakshmanan
- Publisher: O'Reilly Media
- ISBN-10: 1492044466
- ISBN-13: 9781492044468
- Format: 17.8 x 23.3 x 2.7 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you'll examine how to analyze data at scale to derive insights from large datasets efficiently.
Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you're not familiar with or prefer to focus on specific tasks, this reference is indispensable.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 23d.18:11:03
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Valliappa Lakshmanan
- Publisher: O'Reilly Media
- ISBN-10: 1492044466
- ISBN-13: 9781492044468
- Format: 17.8 x 23.3 x 2.7 cm, minkšti viršeliai
- Language: English English
Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you'll examine how to analyze data at scale to derive insights from large datasets efficiently.
Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you're not familiar with or prefer to focus on specific tasks, this reference is indispensable.
Reviews