In this webinar by Cambridge Semantics' VP of Solution Engineering, Ben Szekely, you will learn more about how the Enterprise Data Fabric prevails as the bedrock of enterprise digital strategy. Connected and highly available data is the new normal - powering analytics and AI. The data lake itself is commoditized, like raw compute or disk, and becomes an unseen part of the stack. Semantic graph technology is central to Data Fabric initiatives that meaningfully contribute to digital transformation. We share our vision for digital innovation - a shift to something powerful, expedient and future-proof. The Data Fabric connects enterprise data for unprecedented access in an overlay fashion that does not disrupt current investments. Interconnected and reliable data drives business outcomes by automating scalable AI and ML efforts. Graph technology is the way forward to realize this future.

2. 2020: The Data Fabric Vision2018: The Data Lake Converges, The Data Fabric Emerges2015: The Data Lake Emerges
™
™
2017 2018
From Data Lakes to the Data Fabric: Strategy and Vision

3. 2020: The Data Fabric Vision2018: The Data Lake Converges, The Data Fabric Emerges2015: The Data Lake Emerges
™
™
2017 2018
From Data Lakes to the Data Fabric: Strategy and Vision
The Enterprise Data Fabric Vision:
• Connects data across business units to accelerate growth and digital transformation.
• Overlays existing infrastructure and systems, applying semantics and metadata to access data.
• Grows incrementally, providing immediate value as business units and data sources join the fabric.

4. “Semantic approaches are the future of
the enterprise information fabric“
Michele Goetz - Principal Analyst - Forrester Research
The Information Fabric

5. Drug Discovery Preclinical Product Development FDA Review
Scale Up
Production
Post Marketing
Surveillance
PHASE 1 PHASE 2 PHASE 3
~5,000-10,000
Compounds
250
Compounds
5
Compounds
3-6 Years 6-7 Years 0.5 - 2 Years Indefinite
INDSUBMITTED
NDA/BLASUBMITTED
PREDISCOVERY
Number of Volunteers
20-100 100-500 1,000-5,000
Product
Development &
Regulatory
Voice of the
Customer Analytics
Source of Influence
Commercial
Analytics
R & D
Intelligence (CI)
$538m $119m $219m $255m $251m $39m
Medical Advisory
Board Analytics
Clinical Trial
Exploratory
Analytics
Real World
Research
FDA Approved
Clinical Data
Standards Mgmt
PV & Safety Case
Management
Clinical Trial
Operations
Scientific Data
Management

8. Claim ID Process Date Subscriber ID
44223 10/3/2015 C12345
44224 10/7/2015 C23412
… … …
Patient ID Condition Drug Name
BA213 Sleep Apnea Narcoleptol
CS289 Type II Diabetes Insulin
… …

10. Graph Driven Analytics

11. ●
●
●
●

12. ™ ™

13. ™
™ ™
●
●
●
●
●
●

14. Node 1 Node 2
AnzoGraph Cluster
Node N
…
Node 1 Node 2
Hadoop/Spark/HDFS Cluster
Node M
…
…
Anzo Servers (front-end)
Node 1 Node 2 Node P
…
Anzo Server
Anzo Servers (ingest)
Node 1 Node 2 Node P
…
Active Directory
Hi-Res Analytics,
OData, Spotfire, Tableau
HTTP/ODATA/SPARQL
Structured,
Graph Data
SPARQL
HTTP/GRPC
HTTP/JMS Metadata
Synchronization
HTTP/JMS
Metadata
Synchronization
HDFS
Fuse
Apache Livy
Metadata
HTTP/HTTPS
Elastic Search Cluster
Node 1 Node 2 Node N
…
DS1 DS2 DS3…
…
JDBC
…
Schema
Job Execution
HTTP/HTTPS
Unstructured
Data
Documents

16. Accelerate automation of
data-driven operations
with machine learning and
AI
Accelerate data science
with automated feature
engineering and selection
Achieve strategic data
objectives faster vs.
stitching many tools
together
Answer unanticipated
questions on complex data
across many sources
Self-service data access
and advanced analytics
Semantic layer on Cloud
data lakes and Hadoop
Data management and
prep for NLP, AI, and ML
? ! NLP AI
ML
1 2 3

17. CASE REPORT
Patient had headache.Patient was
taking DRUG X. Patient also
complained of bleeding from nose.
Patient is taking DRUG Y as
well.Reported: Sep 12, 2018

18. CASE REPORT
Patient had headache.Patient was
taking DRUG X. Patient also
complained of bleeding from nose.
Patient is taking DRUG Y as
well.Reported: Sep 12, 2018
CASE REPORT
CASE REPORT
CASE REPORT
CASE REPORT
CASE REPORT
CASE REPORT
Patient had headache.Patient
was taking DRUG X. Patient
also complained of bleeding
from nose. Patient is taking
DRUG Y as well.Reported: Sep
12, 2018
CASE REPORTS INGESTED DATA PROFILED DATA
REDACTED

19. ● Named Entity Recognition
● Relationship Extraction
● Semantic Pattern Extraction
CASE REPORT
Patient had headache.Patient
was taking DRUG X. Patient
also complained of bleeding
from nose. Patient is taking
DRUG Y as well.Reported: Sep
12, 2018
adverse reaction
drug
anatomy

20. CASE REPORT
Patient had headache.Patient
was taking DRUG X. Patient
also complained of bleeding
from nose. Patient is taking
DRUG Y as well.Reported: Sep
12, 2018
Drug X Drug Y
Headache Bleeding
Nose
Feature Selection in Anzoadverse reaction
drug
anatomy

21. ● Predicted Value
● Accuracy Measure
Feature Selection in Anzo
ML Data Layer Options
in Anzo

22. Accelerate automation of
data-driven operations
with machine learning and
AI
Accelerate data science
with automated feature
engineering and selection
Achieve strategic data
objectives faster vs.
stitching many tools
together
Answer unanticipated
questions on complex data
across many sources
Self-service data access
and advanced analytics
Semantic layer on Cloud
data lakes and Hadoop
Data management and
prep for NLP, AI, and ML
? ! NLP AI
ML
1 2 3

31. Graph Driven - Access and Exploration

34. Accelerate automation of
data-driven operations
with machine learning and
AI
Accelerate data science
with automated feature
engineering and selection
Achieve strategic data
objectives faster vs.
stitching many tools
together
Answer unanticipated
questions on complex data
across many sources
Self-service data access
and advanced analytics
Semantic layer on Cloud
data lakes and Hadoop
Data management and
prep for NLP, AI, and ML
? ! NLP AI
ML
1 2 3

35. •
•
•
•
•
•
•
•
•
•
…
•

43. 2020: The Data Fabric Vision2018: The Data Lake Converges, The Data Fabric Emerges2015: The Data Lake Emerges
™
™
2017 2018
From Data Lakes to the Data Fabric: Strategy and Vision