The document discusses Google's expertise in handling big data, emphasizing their ability to collect, store, and analyze vast amounts of information to create actionable insights. It highlights advancements in machine learning and the various applications, including traffic analysis and server optimization, demonstrating the practical benefits derived from data analysis. The text also touches on sentiment analysis related to user feedback on Waze's updates, showcasing the tool's improvements and its effectiveness in traffic reporting.

1. Big Insights with Big Data
Actionable Leads
Daniel Marcous
Google, Waze, Data Wizard
dmarcous@google.com

2. Data is Everything.
Apps (and companies) win or lose based on how they use it.

3. Organize the world’s
information and make it
universally accessible
and useful.
Google’s Mission
3
“

4. Google excels at collecting, storing, and extracting value from
big quantities of data
Google is a (Big) Data Company

5. Google in just 1 minute:
1000 new
devices
3M Searches 100 Hours
1B Activated
Devices
100M GB
Search
Content

6. 10+ Years of Tackling Big Data Problems
6
Google
Papers
20082002 2004 2006 2010 2012 2014 2015
GFS
Map
Reduce
Flume
Java
Millwheel
Open
Source
2005
Google
Cloud
Product
s
BigQuery Pub/Sub Dataflow Bigtable
BigTable Dremel PubSub
Apache
Beam
Tensorflow

7. “Google is living a few years in the
future and sending the rest of us
messages”
Doug Cutting, Hadoop Co-Creator

8. Capture ProcessStore Analyze
Data on your terms

9. Capture ProcessStore Analyze
Data on your terms

11. Machine Learning
“Machine Learning is concerned with computer
programs that automatically improve their
performance through experience. “
Herbert Simon
Turing Award 1975
Nobel Prize in Economics 1978

12. Machine Learning
“A breakthrough in machine learning would be worth
ten Microsofts” (Bill Gates, Chairman, Microsoft)
“Machine learning is the next Internet”
(Tony Tether, Director, DARPA)
“Machine learning is the hot new thing”
(John Hennessy, President, Stanford)

13. Google is no stranger to ML

14. So what do you actually do?
Gain Actionable Insights!

15. Trending Locations - Hilton TLV

16. Trending Locations / Day of Week Breakdown

17. Opening Hours Inference

18. Optimising - Ad clicks / Time from drive start

19. Time to Content (US) - Day of week / Category

20. Irregular Events / Anomaly Detection
Major events, causing out of the ordinary traffic/road blocks etc’ affecting large
numbers of users.

21. Dangerous Places - Clustering
Find most dangerous areas / streets, using custom developed clustering algorithms
● Alert authorities / users
● Compare & share with 3rd parties (NYPD)

22. Server Distribution Optimisation
Calculate the optimal routing servers distribution according to geographical load.
● Better experience - faster response time
● Saves money - no need for redundant elastic scaling of servers

23. Text Mining - Topic Analysis
Topic 1 - ETA Topic 2 - Unusual Topic 3 - Share info Topic 4 - Reports Topic 5 - Jams Topic 6 -Voice
wazers usual road social still morgan
eta traffic driving drivers will ang
con stay info reporting update freeman
zona today using helped drive kanan
usando times area nearby delay voice
real clear realtime traffic add meter
tiempo slower sharing jam jammed kan
carretera accident soci drive near masuk

24. Text Mining - New Version Impressions
● Text analysis - stemming / stopword detection etc.
● Topic modeling
● Sentiment analysis
Waze V4 update :
● Good - “redesign”, ”smarter”, “cleaner”, “improved”
● Bad - “stuck”
Overall very positive score!

25. Text Mining - Store Sentiments

26. Text Mining - Sentiment by Time & Place

29. Daniel Marcous
dmarcous@google.com
dmarcous@gmail.com