The document outlines a presentation on data science, contrasting workflows in sandbox environments versus industry settings. It discusses Oracle's data science solutions, highlighting challenges in data collection, collaboration, and model deployment. Additionally, it includes a demo on customer churn analysis and promotes Oracle cloud trials with credits for users.

1. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |

2. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Siyuan Yin
Solution Engineer, Oracle Reston Hub
Stuti Deshpande
Solution Engineer, Oracle Reston Hub

3. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Agenda for today
- Data Science in Sandbox vs. Industry
- Data Science Challenges Break-down
- Oracle Approach to DS workloads
- Demo time!
- Q&A

4. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
A Little Bit About Me...
- Background in Cognitive Psychology and Information Science
- Oracle Cloud Solution Engineer focusing on data science solutions using
cloud
- Multiple DS/ML projects in program & with startups in industry, mostly on
user behavior & engagement
...little did I know the real world is way more interesting

5. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |

6. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Data Science in Sandbox
- Where grass is green, data is clean, your teammates are data-geniuses,
and you can focus on playing with fancy machine learning models 100%

7. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Sandbox
Data
download to
laptop
Open source
frenzy!
Try different
models/classi
fiers, choose
deep learning
Evaluate &
Tuning
Report performance with
confusion Matrix, AUC,
MSE, etc
Scoring for competition, or
write 13-pages report
Hooray!
Oversimplify the industry:
1. Machine learning as a toy, and the only solution
2. Goal: cutting-edge technology

8. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Industry
Data
Collection

9. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Industry
Business problem
- What values can you
add?
Improve product
- Inferential stats
- A/B testing
Build new feature
- Market/domain analysis
Evaluation metrics?
- User engagement
- User impression
What data?
- User behavior, feature
usage, images
How to get data?
- Pipelines, connectors
What if no data?
Predicting housing
price from a picture
- how good is this
feature?
Data Collection

10. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Industry
Data
Collection
Open source
frenzy!
Build
models/classi
fiers, choose
deep learning
Problem
Definition
Data
Storage

11. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Industry
Tools installed and supported
both in production
environment?
Access to compute/storage
resources when needed?
Diversity: collaborate when
teammate using different tools?
Python(2.7 vs. 3.4),
R, Julia, SAS,
Excel……
Compatible?
Evaluate current
price prediction
feature Open source
vs. Proprietary
Environment & Resource

12. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Workflow in Industry
Data
Collection
Open source/
Proprietary
DS tools
Problem
Definition
Resource
Allocation
Data approaches
based on problem
Evaluate &
Optimization
Performance
Analysis
Productionize
Profit!
Version
Control
Performance
Monitoring

13. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Sandbox Industry
100% on FANCY MODELS!
80% of time:
- Begging for data,
- Begging for resource,
- 50 meetings with marketing
people to prove “this will bring
$$$ ”,
- Begging software engineers to
help deploy your result
20% of time:

14. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Data Collection
Data Storage
Discovery Data
Analysis
Inference
Machine Learning
& Optimization
AI & Deep
Learning
+ Marketing
+ Infrastructure
& Architecture
+ more….
One-fit-all Solutions?

15. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Problems break-down
Talent
• Business sense
• Domain
knowledge
• Data Science skill
sets
• Be skeptical about
results
Operation
Technology
• Resources
• Environment
supporting major
DS tools
• Performant
model/algorithm
• Long wait for
resources
• Difficult
collaborating with
talents
• No standardized
workflow
What Oracle
is solving!

16. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Oracle’s Approach
Oracle Data Science Cloud
Oracle PaaS & IaaS
Projects Notebooks
Open Source
Languages &
Libraries
Version
Control
Use Case
Templates
Model
Build & Train
Self-Service Scalable Compute (OCI)
Object
Store
Catalog
Data
Lake
Streamin
g
Autonomous
Data Warehouse
Model
Deployment
Model
Monitoring
Access
Controls &
Security
Resources
- Scalable
- Self-service access
Collaboration
- Native support for Github,
Gitlab, Bitbucket
- Project-driven UI
DS-oriented environments
- Support latest open source
tools
- Preconfigured environments
Operationalize ML models
- Easy deployment as
API

17. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Resource
RequestData
Collection
Open source/
Proprietary
DS tools
Problem
Definition
Data approaches
based on problem
Evaluate &
Optimization
Performance
Analysis
Productionize
Profit!
Version
Control
Oracle Data Science Cloud
Performance
Monitoring

18. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Data Scientists
● Self-sufficient
● Collaborative
environment
● Sustainable,
standardized workflow
IT Admins
● Preconfigured, data
scientists approved
environments
● Scalable resources,
low maintenance
Software Engineers
Business
Stakeholders
As our own customer, we are happy
● Integrate data workflow
with business decision
making process
● Easy collaboration with
data scientists
● Access to performant,
production-ready
solutions
● Easy deployment in all
scenarios, no more being
“dragged and dropped”

19. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Demo Time!

20. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Demo 1 - Customer Churn Analysis
Business Problem:
- What customer will terminate their service in the next 30 days?
- How can we know in advance?

21. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
Q&A

22. Copyright © 2018 , Oracle and/or its affiliates. All rights reserved. |
BTW, There is one more thing…...
Oracle Cloud Trials!
- $500 credits
- Unlimited access to Oracle cloud products
- Sign up at Oracle table