I/O Announcement: Google Analytics Premium data in BigQuery is coming soon
Thursday, May 16, 2013 | 4:00 PM
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Announcements
Today at I/O, we announced that we are giving Google Analytics Premium users the
ability to glean new business insights by accessing session and hit
level data and combining it with separate data sets. Organizations and
developers can analyze in seconds without massive cost by leveraging Google BigQuery, a web service that lets developers and businesses conduct interactive analysis of big data sets and tap into powerful data analytics.
Interactive data analysis and data ownership
The upcoming BigQuery integration, happening later this year, is a
planned feature for Google Analytics Premium that allows clients to
access their session and hit level data from Google Analytics within
Google BigQuery for more granular and complex querying of unsampled
data. For those unfamiliar with Google BigQuery,
it’s a web service that lets you perform interactive analysis of
massive data sets—up to trillions of rows. Scalable and easy to use,
BigQuery lets developers and businesses tap into powerful data analytics
on demand. Plus, your data is easily exportable; you own it.
Benefits of BigQuery
- Leverage Google’s massive computing power to get business insights from big data in seconds rather than hours.
- Analyze massive amounts of data in the cloud with no up-front investments (hardware provisioning or software licensing investments).
- Share and collaborate quickly and securely using Access Control Lists.
- Store as much as you want, paying only for what you use.
- Protect your data with multiple layers of security from Google.
Potential Uses of the Google Analytics Premium and BigQuery Integration
Having Google Analytics session and hit level data available in BigQuery
opens several possibilities for developers and data scientists. Usage
includes, but is not limited to, the following
- Analyzing visitor behavior across very large date ranges. Answer the question: "From 2010 to 2013, which sections of my site had the most volatility in daily traffic volumes?"
- Joining against data from other sources. Make detailed, custom analyses, such as: "I have a database that contains all the metadata about each article posted on my site and would like to see the bounce rate, conversion rate and new visitors generated by author and topic."
- Understanding complex queries. Answer the question: "Of the visitors to my site that used a voucher code, how many originally discovered my brand from a voucher code site and how many left the checkout process and returned within 10 minutes with a voucher code? Which codes were used in each case?"
- Integrating with Data Warehouses. Make detailed, custom analyses, such as: "On a weekly basis, for each of my logged in customers, I want to see the top 5 products that they viewed but did not buy and add that information into their record in our CRM."
We are looking forward to getting this granular data access into the
hands of developers and data scientists. To receive more information
about this integration as it comes available, developers may register
their interest here: http://goo.gl/QJR9Y.
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