Learning Google Analytics: Creating Business Impact and Driving Insights
Date: December 20th, 2022
ISBN: 109811308X
Language: English
Number of pages: 342 pages
Format: EPUB True PDF
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Why is Google Analytics 4 the most modern data model available for digital marketing analytics? Because rather than simply report what has happened, GA4's new cloud integrations enable more data activation—linking online and offline data across all your streams to provide end-to-end marketing data. This practical book prepares you for the future of digital marketing by demonstrating how GA4 supports these additional cloud integrations.
Author Mark Edmondson, Google Developer Expert for Google Analytics and Google Cloud, provides a concise yet comprehensive overview of GA4 and its cloud integrations. Data, business, and marketing analysts will learn major facets of GA4's powerful new analytics model, with topics including data architecture and strategy, and data ingestion, storage, and modeling. You'll explore common data activation use cases and get guidance on how to implement them.
You'll learn:
• How Google Cloud integrates with GA4
• The potential use cases that GA4 integrations can enable
• Skills and resources needed to create GA4 integrations
• How much GA4 data capture is necessary to enable use cases
• The process of designing dataflows from strategy though data storage, modeling, and activation
Author Mark Edmondson, Google Developer Expert for Google Analytics and Google Cloud, provides a concise yet comprehensive overview of GA4 and its cloud integrations. Data, business, and marketing analysts will learn major facets of GA4's powerful new analytics model, with topics including data architecture and strategy, and data ingestion, storage, and modeling. You'll explore common data activation use cases and get guidance on how to implement them.
You'll learn:
• How Google Cloud integrates with GA4
• The potential use cases that GA4 integrations can enable
• Skills and resources needed to create GA4 integrations
• How much GA4 data capture is necessary to enable use cases
• The process of designing dataflows from strategy though data storage, modeling, and activation
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