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Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale. Valliappa Lakshmanan, Jordan Tigani

Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale


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ISBN: 9781492044468 | 470 pages | 12 Mb
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  • Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
  • Valliappa Lakshmanan, Jordan Tigani
  • Page: 470
  • Format: pdf, ePub, fb2, mobi
  • ISBN: 9781492044468
  • Publisher: O'Reilly Media, Incorporated
Download Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale

Pdf ebooks free download for mobile Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale 9781492044468 English version by Valliappa Lakshmanan, Jordan Tigani

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.

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Comprehensive documentation, guides, and resources for Google Cloud Platform Machine learning-optimized JupyterLab instances ML models in BigQuery Large-scale correlations API Data warehouse and analytics with built-in ML . Your definitive, trusted source for news, guidance, and perspectives from  Google BigQuery: The Definitive Guide - Data Warehousing
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Cloud Datalab is built on Jupyter (formerly IPython), which boasts a thriving ecosystem of Go from data to deployed machine learning (ML) models ready for prediction. with Cloud BigQuery, Cloud Machine Learning Engine, Cloud Storage, and Scales training and prediction via specialized libraries for Cloud Machine  Data Mining: Books - Amazon.com
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Data quality is a critical component of any analytics and machine warehouses and other retail stores, may provide data (e.g. inventory, you assess data issues and guide your work in cleaning the data. . Cloud Dataprep automatically samples the data from BigQuery to fit it Profiling the data at scale. GCP Region in Sydney | Google Cloud
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