When statistical programmers or statisticians starts in open-source programming, we usually begin with installing Python and/or R on our local computer and writing codes in a local IDE such as Jupyter notebook or RStudio, but as biometric team grow, and advanced analytics become more prevalent, collaborative solutions and environments are needed. Traditional solutions have been SAS® servers, but nowadays, there is a growing need and interest for Cloud Computing. The paper is written for those who want to know about the Cloud Computing environment (e.g., AWS) and its possible implementation for the Biometric Department. The paper will start with the main components of Cloud computing – databases, servers, applications, data analytics, reports, visualization, dashboards etc., and its benefits - Elasticity, Control, Flexibility, Integration, Reliability, Security, Inexpensive and Easy to Start. Most popular Cloud computing platforms are AWS, Google Cloud and Microsoft Azure, and this paper will introduce AWS Cloud Computing Environment. The paper will also introduce the core technologies of AWS Cloud Computing – computing (EC2), Storage ( EBS, EFS, S3), Database ( Redshift, RDS, DynamoDB ), Security (IAM) and Networking (VPC ), and how they could be integrated to support modern-day data analytics. Finally, the paper will introduce the department-driven Cloud computing transition project that the whole SAS programming department has moved from SAS Window Server into AWS Cloud Computing. It will also discuss the challenges, and the lessons learn and its future in the Biometric department

1. Introduction ofAWS Cloud
Computing and its future for
Biometric Department
Kevin Lee

2. Disclaimer
The views and opinions presented here represent those of the
speaker and should not be considered to represent any
companies or organizations.

3. • Introduction of Cloud Computing
• Computing Services in Cloud
• Benefits of Cloud Computing
• Main Platforms of Cloud
• Core Technologies of AWS
• AWS Implementation in
Biometrics Department
• AWS Cloud Computing Open-
source Programming Transition
Project
• Future of Cloud Computing in
Biometric Department
• Conclusion

4. “The Magic Faraway Tree Adventure”
Astory about three children climbing up a big tree
to cloud and adventuring a magical land in the
cloud.
- To Ignite Children’s imagination
- To encourage exploring their own creativity

5. 5
What is Cloud
Computing?
-Thru internet,
users will be able
to access all the
computing
services.

6. 6
Cloud Computing
Databases
Servers
Application
s
Data
Analytics
Reports
Visualizati
on
Dashboard
s
Computing
Services of
Cloud
Computing

7. Functionalities / Benefits
of Cloud Computing
• Elasticity
• Flexibility
• Integrated
• Reliable (Highly available)
• Secure
• Cost-saving
• Easy to get started

8. Cloud Computing - Elasticity
• The company is
able to scale up
and down the
computing systems
easily.
• In low demand
period: 2 servers
• In high demand
period: 2 servers to
4 servers

9. Cloud Computing - Flexibility
• On-demand resources
• The company could choose
the best deployment option
among a range of options,
and change the system
based on the demand easily.
• Scalability
• Pay as you go pricing
• The company does not need
to purchase and maintain
the additional hardware.
• Accessibility control

10. Cloud Computing - Integration
• The company is able to
integrate the different
computing system or
application in the same
infrastructure.
• Integration
• Database
• Analytics
• Visualization
• Reporting
• Application

11. Cloud Computing - Reliability
• Cloud computing system
could be reliable and highly
available with multiple data
centers and disaster
recovery features.

12. • Despite popular perceptions,
Cloud computing system
could provide the broad and
deep security features and
management.
• Secure Access
• Encryption on Data
• Industry Compliance
Cloud Computing - Security

13. Cloud Computing – Cost Saving
• The company could save
the upfront cost in
expensive IT systems (e.g.,
hardware, software), and
only pay for the resources
they use rather than
investing IT systems that
might only be used
occasionally.

14. Cloud Computing – Easy to get started
• The company can quickly
create the new systems or
retire them in seconds,
making it easy to prototype
and test new ideas and
applications.
• Sometime, department itself
could build Cloud
Computing environment
without IT support.

15. Main Platform of Cloud Computing
• Amazon AWS
• Microsoft Azure
• Google Cloud
• IBM Cloud

16. Core Technologies of
AWS
• Computing
• Storage
• Database
• Security
• Networking

17. AWS – Computing
• EC2 (Elastic Compute
Cloud) :
• Scalable computing
capacities
• Memory & CPU
• Application
• Analytic Environment
• SAS Viya
• R Studio
• Jupyter
• Tableau
• Power BI

18. AWS – Storage
• EBS (Elastic Block Store):
Storage (e.g., 6 GB) for
EC2 Instance.
• EFS (Elastic File System):
Storage (e.g., 6 GB) for
multiple EC2 Instance.
• S3 (Simple Storage
Service): Object Storage
(e.g., 10 TB)

19. AWS – Database
• Redshift : Data Warehouse
based on PostgreSQL
• RDS (Relational Database
Service) : Relational Database
(e.g., MySQL, PostgreSQL,
Oracle, Aurora)
• DynamoDB : NoSQL
Database

20. AWS – Security
• IAM (Identity and Access
Management ) - Access
management service that
manage users and group.
• KMS (Key Management
Service) – Encryption to
protect the data
• Compliance : GCP(Good
Clinical Practice), HIPAA,
GDPR
• VPC : Limited network
within AWS computing
systems.

21. AWS – Networking
• VPC (Virtual Private Cloud
) : Networking layer for
computing systems (e.g.,
EC2, EBS, EBF and
Database) so that all the
system could be connected
within.

22. AWS Cloud Implementation for Biometric Department
AWS Cloud Computing
Redshift Data Warehouse
(Database)
Central CDR (Clinical Data
Repository) – SDTM, ADaM
EC2 (computing)
SAS, R, Python, Tableau
EBS (Storage)
SAS Raw Dataset
SDTM & ADaM SAS Datasets
Define.xml
S3 (Storage)
SAS Raw Dataset
IAM (Security)

23. 23
Scope of AWS Cloud Computing Open-Source
Transition Project
SAS Server
SAS Studio
Window Server
SAS programming
SAS Programmers(150)
SAS codes(230)
Oracle Relational Database
AWS Cloud
R Pro Server ( R Studio, Jupyter)
AWS Cloud Computing(Linux)
Open-Source Programming ( R,
Python, SQL)
Data Scientists
R, Python & SQL codes (230)
AWS Redshift Data Warehouse

24. 24
New AWS
Cloud
Computing
Open-Source
Analytical
System AWS Cloud
Redshift
Data
Wareho
use
S3
EC2/
Linux
R
Studio
Jupyter
SQL
Workbe
nch
Git
Tableau

25. 25
Challenges for AWS Cloud Computing Open-Source
Programming Transition project
• Inexperience in Cloud Computing, Open-
Source programming
• Inexperience in new system / environment (
AWS Cloud Computing, R Studio, Jupyter,
Linux )
• Learning curve
• Daily works as well as existing SAS codes
conversion
• Lack of enterprise customer support on
Open-Source Programming & Cloud
Computing
• Uncertainty toward new culture created by
Cloud Computing

26. 26
Lessons Learned from AWS Cloud Computing
Open-Source Transition Project
• Support for programmers during the
Transition is critical.
• Training
• Workshop
• Dedicated Supporting Team during the
Transition is critical.
• Know-how / Experience on Existing SAS
Server and Cloud Computing is critical
• Change Management by Leadership is the
key to success.

27. Why Cloud Computing in Biometric Department?
• Organizational strategic direction
• Central Data Repository for SDTM
and ADaM
• More Advanced Analytics (e.g., Data
Visualization, Machine Learning, Big
Data, Open-Source Programming)
• Need for more flexible, highly
available, centralized, integrated
analytical system

28. 28
Conclusion
• Cloud Computing is / will be the future
computing environment for many
organization as organizational
strategic goals.
• Biometric department of some
organizations has moved or is
exploring the options moving into
Cloud computing environment.
• Unknown, Scary Adventure

29. Any Questions?