Presentación a cargo de Jeremy Rollinson, de Microsoft EU, en el 33er Encuentro de la Economía Digital y las Telecomunicaciones organizado por AMETIC y Santander Empresas en colaboración con la UIMP

1. Data sharing principles for Digital Transformation
33º Encuentro de la Economía Digital y las Telecomunicaciones
Palacio de la Magdalena - Santander
Monday, 02nd September 2019

2. Data Sharing &
the Open Data
Opportunity:
The challenges and
road to progress

9. do we

10. Open Data Initiative principles
1
Customer ownership
and control
3
Open and
extensible
2
AI-Driven
Business Outcomes

12. Challenges . . .

13. Advancing open
data is also
important to:

14. “Amazon’s computer models were
trained … by observing patterns in
resumes submitted to the company
over a 10-year period. Most came
from men, a reflection of male
dominance across the tech industry.”
“Many AI systems, e.g. face recognition tools, rely on machine
learning algorithms that are trained with labeled data. It has
recently been shown that algorithms trained with biased data
have resulted in algorithmic discrimination.”

15. The European Commission is expected
to study ways to provide greater
leeway for data sharing under
competition laws
Competition Policy for a Digital Era

17. Differential privacy introduces a small amount of noise, enabling researchers to
extract useful answers, while protecting individuals’ privacy
Differential Privacy Research Platform
Shared data model and workflow built in Azure, with rich
semantics and multi-party confidential compute with
differential privacy to unlock the value

18. A structured approach to making progress with
data sharing

19. Standard legal terms for data
access and sharing
Privacy preserving technologies
Software tools to enable data
sharing

20. news.microsoft.com/datainnovation

21. Existing
At rest
Encrypt inactive data
when stored in blob
storage, database, etc.
Examples include:
Azure Storage Service
Encryption for Data at Rest
SQL Server Transparent
Database Encryption (TDE)
In use
Protect/Encrypt data
that is in use during
computation
Examples include:
Trusted Execution Environments
such as Intel SGX and VBS
Homomorphic encryption
In transit
Encrypt data that is flowing
between untrusted public or
private networks
Examples include:
HTTPS
TLS

22. Working with industry to collaborate on confidential computing open
source technology and frameworks

23. Azure Data Share is a simple service for
big data sharing, helping organizations to:
• Enhance insights with data from
partners and customers
• Form industry-specific consortium to
pool data among members
• Innovate custom solutions and
expand markets via new service
capabilities
Azure
Data Factory
Azure
Databricks
(Prep-only)
Azure
Data Lake
Storage
Azure SQL
Data Warehouse
Power BI
Ingest & Prep
Store
Model & Serve Visualize
Manufacturer
Azure
Data ShareSuppliers
Azure
Data Share
Azure
Data Share
Company A Company B Company C
Azure
Data Share
Share

25. Thank you
To learn more about data sharing, open data, and
recently released data use agreements and join the
conversation, visit
news.microsoft.com/datainnovation