BigQuery for Data Warehousing
Managed Data Analysis in the Google Cloud
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Beschreibung
Create a data warehouse, complete with reporting and dashboards using Google’s BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization.
BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks.
You will:
- Design a data warehouse for your project or organization
- Load data from a variety of external and internal sources
- Integrate other Google Cloud Platform services for more complex workflows
- Maintain and scale your data warehouse as your organization grows
- Analyze, report, and create dashboards on the information in the warehouse
- Become familiar with machine learning techniques using BigQuery ML
Create a data warehouse, complete with reporting and dashboards using Google’s BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization.
BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks.
What You Will Learn
- Design a data warehouse for your project or organization
- Load data from a variety of external and internal sources
- Integrate other Google Cloud Platform services for more complex workflows
- Maintain and scale your data warehouse as your organization grows
- Analyze, report, and create dashboards on the information in the warehouse
- Become familiar with machine learning techniques using BigQuery ML
Who This Book Is For
Developers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers.
Explains how to load or stream your business data into BigQuery Suggests innovative ways to engage with business stakeholders for the long run Provides suggestions for enhancement of data analysis via machine learning
Autor*in
Mark Mucchetti
Themen in »BigQuery for Data Warehousing«
Big Query Google Cloud Platform GCP Big Data SQL BigQueryML Data Machine Learning Data Warehouse Data Mart Data Lake ETL