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Stream & Export your Google Anaytics data to Bigquery Guide

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[vc_row][vc_column][vc_column_text]Google Analytics 360 Data BigQuery ExportAs a passionate Google Analytics 360 and BigQuery User, I always want to take quick actions on the current day data within a couple of minutes. And today, I am ecstatic that Google has rolled out a new streaming export feature. Google Analytics 360 users can now export their Google Analytics data in BigQuery within 10 minutes.

This enables you to carry out analysis and take actions six times within one hour using BigQuery which seems almost real-time data export. Aren’t you excited? Let me elaborate on just how awesome this new feature will prove to be!

Power of Unlocking Data Streaming Delivery Feature

All business giants who deal with tons of data points flowing into Google Analytics, require faster data access to identify high intent users, analyse internal promotions and quickly discover anomalies in your critical business metrics. Listed below are the few real-time actions that you can take based on your data:

  • Instant retargeting for higher conversions:
    In today’s fast-paced, dynamic world, every second counts. It is observed from the recent market trends that users are highly likely to convert if they get instant incentives. The sooner they come back to your website, better are the chances of them converting.

    Dynamic and instant remarketing approach will prove to be more promising and effective in driving greater engagements.
  • Real-time Prediction:
    This amazing feature will enable Data Scientist to run predictive algorithms in real-time. With quick download of data, predictions can be tested in a short span of time and new results can be used to retrain for better accuracies. One use case that analysts can make use of, is Predictive Lead Scoring. This will give marketers a score of leads with higher propensity to convert customers within a short span of time. And then automated emailers or push notifications can be sent to the leads where conversion rates can go up due to recency effect. Currently, with the data that is processed, predictions are carried out a day after and chances of conversion become comparatively slimmer.
  • Quick Issue Debugging:
    Frequent data updates in BigQuery will allow organizations to identify issues and help them to fix it quickly.
  • Taking data stitching to the next level:
    Business intelligence tools can also be empowered using raw, hit level, online-behavior data with offline data sources like CRM, call centres and POS data.

4 Easy Steps: Get Started with the all new Data Streaming Feature Now

You can start getting data more frequently by just changing your streaming preference option.

  1. Navigate to your Google Analytics 360 Admin settings
  2. Go to BigQuery Integration Page
  3. Click on Adjust link

You will now see a Streaming Preferences Options. Choose “Data exported continuously” option as shown following:

And voila! You are all set! And that too without any help from your go-to tech guy!

Got questions? Don’t worry, we got you covered!

Once you will opt for this feature, Google Analytics data will start streaming into your BigQuery project as fast as every 10 minutes. Note that this might take few hours to reflect in your BigQuery. As exciting as this is, I am sure this update must have lead to few queries for all of you. I am going to attempt and answer a few FAQs that we’ve experienced from within our team as well as our clients.

  • Is this chargeable? If yes, what is the cost?
    Yes, you will be. The new streaming export uses Google Cloud Streaming Service and that costs a $0.05 per GB. That’s why Google recommends that you choose your own streaming preferences so that you don’t end up with unknown additional cost.
  • Will I see changes in BigQuery?
    Yes, you will start seeing two new tables in your BigQuery cloud platform.
  1. ga_realtime_sessions: In this table, you will get the current day Google Analytics data.
  2. ga_realtime_sessions_view: This is a view – virtual table in BigQuery.

In the detailed section of ga_realtime_sessions_ table, you will also find information regarding the table’s Streaming Buffer if it is present. If there is no data in Streaming Buffer or table is not being streamed to (ga_sessions_intraday_), this section will be absent.

  • What additional data will I see?
    You will able to see updated BigQuery schema under ga_realtime_sessions_view_. Following fields are introduced : 

    1. exportTimeUsec – Unix timestamp when data gets exported to Google Cloud
      For ex. 1505981096384
    2. exportKey – It’s a combination of fullvisitorId, visitStartTime/visitID,
      Format : fullvisitorId:visitStartTime/visitID: exportTimeUsec
      For ex. 3601279501650676672:1505976859:1505981096384
    3. visitKey –  It’s a combination of fullvisitorId and visitStartTime/visitID
            For ex. 3601279501650676672:1505976859

If you don’t opt for the data streaming feature, then you will continue to see data streaming like you do today, which is about thrice a day i.e. every eight hours.

Concluding Thoughts:

All that which is captured through analytics tracking is included in this streaming export. Although be aware, data sources like AdWords and DoubleClick, Search console will be not included in same.

Happy data streaming!

What do you think about this new data streaming feature introduced by Google? I would love to hear your views and take on it. Please do write to me in the comments section below, I am looking forward to it. 

We at Tatvic also provide BigQuery Training for Corporates & Developers.[/vc_column_text][/vc_column][/vc_row]

Picture of Saikat Ghosh

Saikat Ghosh

Saikat is a Senior Business Development Manager at Tatvic. He headed business development in couple of other IT organization before joining Tatvic. He studied management at IIM Calcutta where he honed his skills as a manager. In his spare time, he loves to read books, listen to music and watch movies.

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