1. Emily Kohne Oscar Rivera Adriana Perez Brenda Izaguirre

2. What is Google BigQuery?
Cloud-based big data analytics web service
Designed to analyze data on the order of billions of rows

3. How does BigQuery Work?

4. BigQuery is an API

5. Pros of BigQuery Scan billions of records in a few seconds
Provides massive computing power to small & large companies
Affordable
Charged per query & low storage cost
Unlimited storage
SQL

6. Cons of BigQuery Documentation is not complete
Performance is occasionally unstable
Error messages not clear
Can only run read-only queries

7. Users

8. Problems before BigQuery:
“From traditional batch processing with Dataproc, to rock-solid event delivery with Pub/Sub to the nearly magical abilities of BigQuery, building on Google’s data infrastructure provides us with a significant advantage where it matters the most”
Nicholas Harteau VP, Engineering & Infrastructure, Spotify
Problems before BigQuery:
Speed
Complex analysis
Single point failures
Internal Web UIs
After Big Query:
Speed (from ~17,500sec to ~500sec to get “top tracks by age”)
SQL - no learning curve
No more infrastructure
Adriana

9. Integrate data to gain a holistic view of the customer Strategy:
“Google Analytics Premium, combined with Google Tag Manager and BigQuery, has become an integral solution that gives us the technical agility and the analytics power we need to advance our marketing strategies."
Nick Dutch Head of Digital, Domino’s
Goal:
Break down data silos
Integrate data to gain a holistic view of the customer
Strategy:
Google Analytics Premium + BigQuery to connect digital data and CRM data
Results:
Realized an immediate 6% increase in monthly revenue
Improved insights & reporting visualized through dynamic dashboards

10. Competitors Amazon Redshift Google BigQuery Structured Unstructured
Pricing: Hourly rate based on type & number of nodes
Speed: limited
Live Streaming data - not possible
AWS
Google BigQuery
Unstructured
Pricing
$0.02 / month per GB stored
Stream uploads
Queries
Speed: fast
Live stream data uploads
compared-to-Amazons-Redshift -- particularly fond of the comment/response section\

11. Run Query:
SELECT word, corpus, SUM(word_count) as count
FROM (publicdata:samples.shakespeare)
WHERE word = "swagger"
GROUP BY word, corpus
ORDER BY count DESC
Demo