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Google BigQuery Analytics (Paperback)
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Google BigQuery Analytics (Paperback)
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This book shows business and data analysts how to use BigQuery most
effectively, avoid common pitfalls, and ultimately execute
sophisticated queries against large, complex data sets. The authors
will share tips and recipes for running complex queries. And they
will also show how to write code to communicate with the BigQuery
API. The authors will demonstrate best practices and techniques
against an extended real-world example -- a web application that
collects sensor data from mobile devices and displays a dashboard
visualizing the data in real-time. Along the way, the authors will
use examples to demonstrate streaming ingestion, transformation via
Hadoop in Google Compute engine, AppEngine datastore integration,
and using GViz with Tableau to generate charts of query results.The
authors will not just cover the mechanics of using BigQuery; they
will also cover the architecture of the underlying Dremel query
engine: understanding how a query will execute is a key to getting
good results from BigQuery. The book describes how Dremel works,
and pairs it with concrete query examples showing how to work
around limitations in the architecture. The query samples will be
in BigQuery's variant of SQL. And the web application examples will
be in Python, the most popular language for analytics. Where the
Java analogue of the Python samples would differ significantly,
Java samples will be given as well. All code and data sets will be
available on the book's companion website.
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