"Big Data & Machine Learning Innovation with Google Cloud Platform", Shira Kimchi Google Cloud Platform, Business Manager of MEA Watch more from Data Natives Tel Aviv 2016 here: http://bit.ly/2hw1MY0 Visit the conference website to learn more: http://telaviv.datanatives.io/ Follow Data Natives: https://www.facebook.com/DataNatives https://twitter.com/DataNativesConf Stay Connected to Data Natives by Email: Subscribe to our newsletter to get the news first about Data Natives 2017: http://bit.ly/1WMJAqS About the Author: Shira is the Business manager of MEA Google Cloud Platform, responsible for business strategy and growth of Google Cloud Platform solutions across Middle east and Africa.Shira has a rich technical background across Infrastructure and cloud services, working with Startups and Enterprise organizations. Prior to Google, Shira was an Account Executive at Microsoft leading the relationship with key Hi-Tech enterprise accounts. In the last few years her business focus is Cloud - including SAAS|PAAS|IAAS solutions that answer the business needs of various customers.

1. 1Data & Analytics
3rd Generation Data Platform:
From Buckets of Bits to Understanding

2. 2Data & Analytics
Data is Everything.
How well you use your data can determine the degree of your success.

3. 3
Street nameStreet number
Street View
Sign
Business facade
Sign
Business name
Traffic light
Traffic signStreet number

4. 4Data & Analytics
3rd Gen Data Platforms Challenges
Data access to a variety
of data sources.
Develop and build
analytic models.
Data preparation,
exploration and visualization.
Deploy models and integrate
them into business processes
and applications.
High performance and scalability
for both development
and deployment.
Perform platform, project
and model management.

5. 55
– Doug Cutting, Hadoop Co-Creator
“Google is living a few years
in the future and sending the
rest of us messages”

6. 6Data & Analytics
Google Cloud Platform Vision
Single-node computing
“Some assembly required”
True, on-demand cloud
An actual, global
elastic cloud
3rd Wave
Invest your energy
in great apps
Colocation
Your kit, someone
else’s building.
Yours to manage.
1st Wave
Today's Cloud:
Virtualized
Data Centers
Standard virtual kit,
for rent. Still yours
to manage.
2nd Wave

7. 7Data & Analytics
Bridging the Waves
AnalyzeStoreCapture
BigQuery
(large scale SQL)
Cloud Machine
Learning
Cloud Pub/Sub
Logs, App Engine
BigQuery streaming
Process
Cloud Dataflow
(stream and batch)
Cloud
Storage
(objects)
Cloud SQL
(SQL)
Cloud
Datastore
(NoSQL)
BigQuery
(structured)
Cloud Dataproc (Hadoop & Ecosystem)
Cloud
Bigtable
(NoSQL
HBase)
Cassandra hBase MongoDBRabbit MQ Kafka
Wave 2
Wave 3
Visualise
Cloud DataLab
(iPython/Jupyter)
Data Studio 360
Tableau Qlik

8. 8Data & Analytics
Exploration &
Collaboration
Databases Storage
Data
Preparation
& Processing
Analytics
Advanced
Analytics &
Intelligence
Google Cloud Data Platform
Mobile apps
Sensors and
devices
Web apps
Relational
Key-value
Document
SQL
Wide
Column
Object
Stream
processing
Batch
processing
Data
preparation
Federated
query
Data catalog
Data
exploration
Data
visualization
Developers
Data scientists
Business
analysts
Development
environment
for Machine
Learning
Pre-Trained
Machine
Learning
models
Data
Ingestion
Messaging
Logs

9. 9Data & Analytics
Data
Preparation &
Processing
Cloud Dataflow
Cloud Dataproc
Exploration &
Collaboration
Google BigQuery
Cloud Datalab
Google
Analytics 360
Cloud Dataproc
Google Cloud Data Platform
Mobile apps
Sensors and
devices
Web apps
Developers
Data scientists
Business
analysts
Data Ingestion
Cloud Pub/Sub
App Engine
Databases/
Storage
Cloud SQL
Cloud Bigtable
Cloud Datastore
Cloud Storage
Analytics
Google BigQuery
Google
Analytics 360
Cloud Dataproc
Google Drive
Advanced
Analytics &
Intelligence
Cloud Machine
Learning
Translate API
Vision API
Speech API

10. 10Data & Analytics
Managed Data Services - Focus on Insight vs Infrastructure
PB+ Scale, No-Ops, Batch & Streaming of Data
Insights/
Programming
Resource
Provisioning
Performance
Tuning
Monitoring
Reliability
Deployment &
Configuration
Handling
Growing Scale
Utilization
Improvements
Insights/
Programming

11. proprietary & confidential | not for distribution
"We are very excited about the productivity
benefits offered by Cloud Dataflow and Cloud
Pub/Sub. It took half a day to rewrite
something that had previously taken over six
months to build using Spark"
Paul Clarke, Director of Technology, Ocado
http://googlecloudplatform.blogspot.co.uk/2015/08/Announcing-General-Availability-of-Google-Cloud-Dataflow-and-Cloud-Pub-Sub.html

12. Hadoop + Local SSD
5X the IOPS at 0.5 the cost of AWS local SSD
Up to 1.5TB per instance
680,000 read IOPS and < 1ms latency1
2
3

13. 13Data & Analytics
– Mattias P Johansson, Software Engineer, Spotify
“With Google Cloud Platform, we benefitted by having a
virtual supercomputer on demand, without having to deal
with all the usual space, power, cooling and networking
issues.
Just a few years ago, we would have needed to use the
largest supercomputers on the planet to do what we’re
now able to do with Google”
– Mark Johnson, CEO, Descartes Labs
“Right at the start of the partnership we were able
to reduce time to insight from 96 hours to 30
minutes by using BigQuery.”
– Gary Sanders, Head of Digital Analytics, Lloyds Banking Group
“Everyone involved unanimously picked GCP. It came
down to this: we believe the core technology is better.”
– Peter Bakkam, Platform Lead, Quizlet
Do you feel this way about your Data Warehouse?

14. 14Data & Analytics
Data Warehouses/Lakes Machine Intelligence
Data Warehouse is the foundation of something bigger
Predictive
+
Prescriptive
analytics
=
Advanced
analytics
Cloud
On
Premises
Machine
Learning
APIs
Train
your own
Models

15. 15Data & Analytics
Automatically
categorize, and
automatically
extract value
Evaluate the model by
applying it against
additional manually
categorized data, correct
and tune
Machine intelligence is already making a huge difference
and there are many, many more opportunities
Capture lots of examples
of correct evaluations for
that categorization, and
use them to train an ML
model
Identify categorizations
that provide value,
categories you’re
already evaluating for
by hand today
1 2 3 4

16. 16| THE LEADERS CIRCLE
Rapidly accelerating use of deep learning at Google
AlphaGo
Android
Apps
Gmail
Maps
Photos
Robotics
Speech
Search
Translation
YouTube
and many others ...
Used across areas:
2012 2013 2014 2015
1500
1000
500
0
Number of directories containing model description files

17. 171717
BETAGA BETA
Cloud
Translate API
Cloud
Vision API
Cloud
Speech API
Natural
Language API
GA
Ready to use Machine Learning models

18. 18Data & Analytics
Machine learning will drive every
successful huge IPO win in the next 5 years.“
”Eric Schmidt
Executive Chairman, Alphabet Inc

19. 19Data & Analytics
Now
Stores and Analyzes
Next
Understands

20. 20Data & Analytics 20
Thanks!