SlideShare a Scribd company logo
1 of 29
Today’s Agenda
Bob Liebowitz
March 11, 2020
Strictly ConfidentialStrictly Confidential
• Overview: Connected data and graphs
• Market landscape
• Neo4j Introduction
• Case studies
• Wrap-up
Topics
Networks of People Business Processes Knowledge Networks
E.g., Risk management, Citizen
Service, Payments
E.g., Employees, Citizens,
Suppliers, Partners,
Influencers
E.g., Enterprise content,
Domain specific content,
eCommerce content
Data connections are increasing as rapidly as data volumes
The Rise of Connections in Data
Graphs have been universally recognized as a great solution
for specific types of problems
- Graph Problems -
and
recognition is GROWING!
Look at this data…
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Time challenge #1: What if J fails?
?
Look at this data again…
If your business problem has a lot of dependencies - which in IT /
database terms are represented by JOINs between different entities -
and if solving for these dependencies in near real time is important
to you, then your problem is probably easiest solved with graph
technology - and we can safely call it a
GRAPH PROBLEM.
Identifying Graph Problems
2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…
The Graph Problem at Scale: Panama
Papers
DB-engines Ranking of Database Categories
Graph DB
2013 2014 2015 2016 2017 2018 2019
• Graph DBMS
• Key-value stores
• Document stores
• Wide column store
• RDF stores
• Time stores
• Native XML DBMS
• Object oriented DBMS
• Multivalue DBMS
• Relational DBMS
Popularity of Graphs
Strictly Confidential
16
Graph is a Top Technology Trend for 2020
“Choice (from 3:00 to 6:00), during
which the DBMS technology asset
class typically moves from
adolescent status into the early
mainstream. This is the phase of
highest growth in demand (market
penetration potentially reaches
50%), during which supply options
should grow…”
17
Graphs in the Early Mainstream
Making Graph Database Market History:
An Emerging Open Standard
Neo4j Company Update
A Vibrant
Growing
Community
A Vibrant
Growing
Community
50%
1000+
Sign ups for Startup Program
Neo4j is one
of the Fastest
Growing Skills
76%FORTUNE
100
have adopted
or are piloting
Neo4jFinance
20 of top 25
7 of top 10
Software
Retail
7 of top 10
Airline
s
3 of top 5
Logistic
s
3 of top 5
Telco
4 of top 5
Hospitalit
y
3 of top 5
Growing
Adoption
in the
Enterprise
Case Studies
Background
• US IT consulting firm helped US Army streamline
equipment deployments and maintenance spending
• Saving lives by improving the operational readiness
of Army equipment like tanks, radios, transports,
aircraft, weaponry, etc.
Business Problem
• Needed to modernize procurement, budget and
logistics processes for equipment & spare parts
• Millions of connections among a tank’s bill-of-
materials, for example
• Improve “what if” cost calculations when planning
missions and troop deployments
• Mainframe systems required over 60 man-hrs to
calculate changes… planning took too long.
Solution and Benefits
• 118M nodes & 185M relationships
• Shed cost estimation times by 88%
• Improved parts delivery timing and accuracy
• DBA labor required dropped by 77%
• Equipment TCO more predictable
• Safer soldiers
US Army / Calibre Systems Equipment Logistics
Parts Assembly & Equipment Maintenance25
Background
• The MITRE Corporation is a federally-funded, not-
for-profit company that manages cybersecurity for
seven national research and development
laboratories around the United States including the
Center for National Security
• Founded in 1958, engaged in numerous public-
private partnerships as well as independent
research
Problem
• Constantly-evolving networks – devices,
configurations
• Huge volumes of “noise” from virus warnings to
failed logins
• Isolated datapoints with no context to separate the
most serious threats from the benign
• Existing database could not provide the context or
performance to manage a real-time environment
Solution and Benefits
• CyGraph - Agencies now have scalable,
comprehensive analytic and visualization capabilities
• Allowed agencies to capture a picture of their
cybersecurity environment that connects previously
isolated data points
Mitre Cybersecurity for Federal Agencies
26
“CyGraph’s comprehensive knowledge base tells
a much more complete story than that of basic
attack graphs or mission dependency models. [It]
includes potential attack-pattern relationships that
fill in gaps between known vulnerabilities and
threat indicators.”
- Steven Noel, Principal Cybersecurity
Engineer
Background
• Social network of 10M graphic artists
• Peer-to-peer evaluation of art and works-in-progress
• Job sourcing site for creatives
• Massive, millions of updates (reads & writes) to Activity
Feed
• 150 Mongos to 48 Cassandras to 3 Neo4j’s!
Business Problem
• Artists subscribe, appreciate and curate “galleries” of
works of their own and from other artists
• Activities Feed is how everyone receives updates
• 1st implementation was 150 MongoDB instances
• 2nd implementation shrunk to 48 Cassandras, but it
was still too slow and required heavy IT overhead
Solution and Benefits
• 3rd implementation shrunk to 3 Neo4j instances
• Saved over $500k in annual AWS fees
• Reduced data footprint from 50TB to 40GB
• Significantly easier to introduce new features like,
“New projects in you Network”
Adobe Behance Social Network of 10M Graphic Artists
Social Network27
EE Customer since 2016 Q
Background
• Over 7M citizens suffer from Diabetes
• Connecting over 400 researchers
• Incorporates over 50 databases, 100k’s of Excel
workbooks, 30 database of biological samples
• Sought to examine disease from as many angles as
possible.
Business Problem
• Genes are connected by proteins or to metabolites,
and patients are connected with their diets, etc…
• Needed to improve the utilization of immensely
technical data
• Needed to cater to doctors and researchers with
simple navigation, communication and connections
of the graph.
Solution and Benefits
• Dr. Alexander Jarasch, Head of Bioinformatics and
Data Management
• Scientists can conduct parallel research without asking
the same questions or repeating tests
• Built views like a liver sample knowledge graph
DZD - German Center for Diabetes Research
Medical Genomic Research28
EE Customer since 2016 Q
#neo4j@lancewalter #neo4j

More Related Content

What's hot

JPJ1417 Data Mining With Big Data
JPJ1417   Data Mining With Big DataJPJ1417   Data Mining With Big Data
JPJ1417 Data Mining With Big Datachennaijp
 
From Science to Data: Following a principled path to Data Science
From Science to Data: Following a principled path to Data ScienceFrom Science to Data: Following a principled path to Data Science
From Science to Data: Following a principled path to Data ScienceInstitute of Contemporary Sciences
 
Big Data & Analytics for Government - Case Studies
Big Data & Analytics for Government - Case StudiesBig Data & Analytics for Government - Case Studies
Big Data & Analytics for Government - Case StudiesJohn Palfreyman
 
Using Graphs to Enable National-Scale Analytics
Using Graphs to Enable National-Scale AnalyticsUsing Graphs to Enable National-Scale Analytics
Using Graphs to Enable National-Scale AnalyticsNeo4j
 
Banji Adenusi - big data prezzie - InfoSci
Banji Adenusi - big data prezzie - InfoSciBanji Adenusi - big data prezzie - InfoSci
Banji Adenusi - big data prezzie - InfoSciBanji Adenusi
 
Big Data Landscape 2018
Big Data Landscape 2018Big Data Landscape 2018
Big Data Landscape 2018Leanne Hwee
 
Introduction to data science club
Introduction to data science clubIntroduction to data science club
Introduction to data science clubData Science Club
 
Big Data in Education Sector
Big Data in Education SectorBig Data in Education Sector
Big Data in Education SectorKaran Sachdeva
 
Personalized News and Video Recomendation System at LinkSure
Personalized News and Video Recomendation System at LinkSurePersonalized News and Video Recomendation System at LinkSure
Personalized News and Video Recomendation System at LinkSureLeanne Hwee
 
Big data, data science & fast data
Big data, data science & fast dataBig data, data science & fast data
Big data, data science & fast dataKunal Joshi
 
Big Data : Risks and Opportunities
Big Data : Risks and OpportunitiesBig Data : Risks and Opportunities
Big Data : Risks and OpportunitiesKenny Huang Ph.D.
 
NOVA Data Science Meetup 1/19/2017 - Presentation 1
NOVA Data Science Meetup 1/19/2017 - Presentation 1NOVA Data Science Meetup 1/19/2017 - Presentation 1
NOVA Data Science Meetup 1/19/2017 - Presentation 1NOVA DATASCIENCE
 
AI: The next frontier by Amparo Alonso at Big Data Spain 2017
AI: The next frontier by Amparo Alonso at Big Data Spain 2017AI: The next frontier by Amparo Alonso at Big Data Spain 2017
AI: The next frontier by Amparo Alonso at Big Data Spain 2017Big Data Spain
 

What's hot (20)

JPJ1417 Data Mining With Big Data
JPJ1417   Data Mining With Big DataJPJ1417   Data Mining With Big Data
JPJ1417 Data Mining With Big Data
 
From Science to Data: Following a principled path to Data Science
From Science to Data: Following a principled path to Data ScienceFrom Science to Data: Following a principled path to Data Science
From Science to Data: Following a principled path to Data Science
 
What is big data
What is big dataWhat is big data
What is big data
 
BigDataCSEKeyNote_2012
BigDataCSEKeyNote_2012BigDataCSEKeyNote_2012
BigDataCSEKeyNote_2012
 
Big Data & Analytics for Government - Case Studies
Big Data & Analytics for Government - Case StudiesBig Data & Analytics for Government - Case Studies
Big Data & Analytics for Government - Case Studies
 
Using Graphs to Enable National-Scale Analytics
Using Graphs to Enable National-Scale AnalyticsUsing Graphs to Enable National-Scale Analytics
Using Graphs to Enable National-Scale Analytics
 
What is Data Science
What is Data ScienceWhat is Data Science
What is Data Science
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
Banji Adenusi - big data prezzie - InfoSci
Banji Adenusi - big data prezzie - InfoSciBanji Adenusi - big data prezzie - InfoSci
Banji Adenusi - big data prezzie - InfoSci
 
Big Data Landscape 2018
Big Data Landscape 2018Big Data Landscape 2018
Big Data Landscape 2018
 
Introduction to data science club
Introduction to data science clubIntroduction to data science club
Introduction to data science club
 
Big Data in Education Sector
Big Data in Education SectorBig Data in Education Sector
Big Data in Education Sector
 
Personalized News and Video Recomendation System at LinkSure
Personalized News and Video Recomendation System at LinkSurePersonalized News and Video Recomendation System at LinkSure
Personalized News and Video Recomendation System at LinkSure
 
HICSS - 50
HICSS - 50 HICSS - 50
HICSS - 50
 
Building up a Data Science Team from Scratch
Building up a Data Science Team from ScratchBuilding up a Data Science Team from Scratch
Building up a Data Science Team from Scratch
 
Big data, data science & fast data
Big data, data science & fast dataBig data, data science & fast data
Big data, data science & fast data
 
Big Data : Risks and Opportunities
Big Data : Risks and OpportunitiesBig Data : Risks and Opportunities
Big Data : Risks and Opportunities
 
Data Science and its impact on society
Data Science and its impact on societyData Science and its impact on society
Data Science and its impact on society
 
NOVA Data Science Meetup 1/19/2017 - Presentation 1
NOVA Data Science Meetup 1/19/2017 - Presentation 1NOVA Data Science Meetup 1/19/2017 - Presentation 1
NOVA Data Science Meetup 1/19/2017 - Presentation 1
 
AI: The next frontier by Amparo Alonso at Big Data Spain 2017
AI: The next frontier by Amparo Alonso at Big Data Spain 2017AI: The next frontier by Amparo Alonso at Big Data Spain 2017
AI: The next frontier by Amparo Alonso at Big Data Spain 2017
 

Similar to State of Florida Neo4J Graph Briefing - Keynote

Keynote: Graphs in Government_Lance Walter, CMO
Keynote:  Graphs in Government_Lance Walter, CMOKeynote:  Graphs in Government_Lance Walter, CMO
Keynote: Graphs in Government_Lance Walter, CMONeo4j
 
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4jNeo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4jNeo4j
 
A Successful Data Strategy for Insurers in Volatile Times (EMEA)
A Successful Data Strategy for Insurers in Volatile Times (EMEA)A Successful Data Strategy for Insurers in Volatile Times (EMEA)
A Successful Data Strategy for Insurers in Volatile Times (EMEA)Denodo
 
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)A Successful Data Strategy for Insurers in Volatile Times (ASEAN)
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)Denodo
 
Big Data, NoSQL, NewSQL & The Future of Data Management
Big Data, NoSQL, NewSQL & The Future of Data ManagementBig Data, NoSQL, NewSQL & The Future of Data Management
Big Data, NoSQL, NewSQL & The Future of Data ManagementTony Bain
 
final oracle presentation
final oracle presentationfinal oracle presentation
final oracle presentationPriyesh Patel
 
How to add security in dataops and devops
How to add security in dataops and devopsHow to add security in dataops and devops
How to add security in dataops and devopsUlf Mattsson
 
Geospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven RamageGeospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven RamageSteven Ramage
 
CTO Perspectives: What's Next for Data Management and Healthcare?
CTO Perspectives: What's Next for Data Management and Healthcare?CTO Perspectives: What's Next for Data Management and Healthcare?
CTO Perspectives: What's Next for Data Management and Healthcare?Health Catalyst
 
Data science.chapter-1,2,3
Data science.chapter-1,2,3Data science.chapter-1,2,3
Data science.chapter-1,2,3varshakumar21
 
Neo4j GraphTalks - Einführung in Graphdatenbanken
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j GraphTalks - Einführung in Graphdatenbanken
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j
 
Newcastle Intro 2015
Newcastle Intro 2015Newcastle Intro 2015
Newcastle Intro 2015Lee Schlenker
 
John Eberhardt NSTAC Testimony
John Eberhardt NSTAC TestimonyJohn Eberhardt NSTAC Testimony
John Eberhardt NSTAC TestimonyJohn Eberhardt
 
GraphTalks - Einführung
GraphTalks - EinführungGraphTalks - Einführung
GraphTalks - EinführungNeo4j
 
WWV2015: Jibes Paul van der Hulst big data
WWV2015: Jibes Paul van der Hulst big dataWWV2015: Jibes Paul van der Hulst big data
WWV2015: Jibes Paul van der Hulst big datawebwinkelvakdag
 
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Data Science Society
 
Activate Your Data Lakehouse with an Enterprise Knowledge Graph
Activate Your Data Lakehouse with an Enterprise Knowledge GraphActivate Your Data Lakehouse with an Enterprise Knowledge Graph
Activate Your Data Lakehouse with an Enterprise Knowledge GraphDATAVERSITY
 

Similar to State of Florida Neo4J Graph Briefing - Keynote (20)

Keynote: Graphs in Government_Lance Walter, CMO
Keynote:  Graphs in Government_Lance Walter, CMOKeynote:  Graphs in Government_Lance Walter, CMO
Keynote: Graphs in Government_Lance Walter, CMO
 
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4jNeo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
 
A Successful Data Strategy for Insurers in Volatile Times (EMEA)
A Successful Data Strategy for Insurers in Volatile Times (EMEA)A Successful Data Strategy for Insurers in Volatile Times (EMEA)
A Successful Data Strategy for Insurers in Volatile Times (EMEA)
 
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)A Successful Data Strategy for Insurers in Volatile Times (ASEAN)
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)
 
Big Data, NoSQL, NewSQL & The Future of Data Management
Big Data, NoSQL, NewSQL & The Future of Data ManagementBig Data, NoSQL, NewSQL & The Future of Data Management
Big Data, NoSQL, NewSQL & The Future of Data Management
 
final oracle presentation
final oracle presentationfinal oracle presentation
final oracle presentation
 
M.Florence Dayana
M.Florence DayanaM.Florence Dayana
M.Florence Dayana
 
Big data
Big dataBig data
Big data
 
Big Data et eGovernment
Big Data et eGovernmentBig Data et eGovernment
Big Data et eGovernment
 
How to add security in dataops and devops
How to add security in dataops and devopsHow to add security in dataops and devops
How to add security in dataops and devops
 
Geospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven RamageGeospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven Ramage
 
CTO Perspectives: What's Next for Data Management and Healthcare?
CTO Perspectives: What's Next for Data Management and Healthcare?CTO Perspectives: What's Next for Data Management and Healthcare?
CTO Perspectives: What's Next for Data Management and Healthcare?
 
Data science.chapter-1,2,3
Data science.chapter-1,2,3Data science.chapter-1,2,3
Data science.chapter-1,2,3
 
Neo4j GraphTalks - Einführung in Graphdatenbanken
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j GraphTalks - Einführung in Graphdatenbanken
Neo4j GraphTalks - Einführung in Graphdatenbanken
 
Newcastle Intro 2015
Newcastle Intro 2015Newcastle Intro 2015
Newcastle Intro 2015
 
John Eberhardt NSTAC Testimony
John Eberhardt NSTAC TestimonyJohn Eberhardt NSTAC Testimony
John Eberhardt NSTAC Testimony
 
GraphTalks - Einführung
GraphTalks - EinführungGraphTalks - Einführung
GraphTalks - Einführung
 
WWV2015: Jibes Paul van der Hulst big data
WWV2015: Jibes Paul van der Hulst big dataWWV2015: Jibes Paul van der Hulst big data
WWV2015: Jibes Paul van der Hulst big data
 
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
 
Activate Your Data Lakehouse with an Enterprise Knowledge Graph
Activate Your Data Lakehouse with an Enterprise Knowledge GraphActivate Your Data Lakehouse with an Enterprise Knowledge Graph
Activate Your Data Lakehouse with an Enterprise Knowledge Graph
 

More from Neo4j

Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfNeo4j
 
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...Neo4j
 
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosBBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosNeo4j
 
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Neo4j
 
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jGraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
 
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j
 
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfRabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j
 
Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Neo4j
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeNeo4j
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsNeo4j
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j
 
Neo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j
 
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...Neo4j
 
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AIDeloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AINeo4j
 
Ingka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignIngka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignNeo4j
 
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Neo4j
 
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxGraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxNeo4j
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxNeo4j
 

More from Neo4j (20)

Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdf
 
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
 
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosBBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
 
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
 
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jGraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
 
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfRabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG time
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge Graphs
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
 
Neo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with Graph
 
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
 
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AIDeloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
 
Ingka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignIngka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by Design
 
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
 
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxGraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
 

Recently uploaded

Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsRavi Sanghani
 
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...itnewsafrica
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
QCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesQCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesBernd Ruecker
 
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesMuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesManik S Magar
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersNicole Novielli
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Strongerpanagenda
 
Top 10 Hubspot Development Companies in 2024
Top 10 Hubspot Development Companies in 2024Top 10 Hubspot Development Companies in 2024
Top 10 Hubspot Development Companies in 2024TopCSSGallery
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesThousandEyes
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPathCommunity
 
React Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkReact Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkPixlogix Infotech
 
Bridging Between CAD & GIS: 6 Ways to Automate Your Data Integration
Bridging Between CAD & GIS:  6 Ways to Automate Your Data IntegrationBridging Between CAD & GIS:  6 Ways to Automate Your Data Integration
Bridging Between CAD & GIS: 6 Ways to Automate Your Data Integrationmarketing932765
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observabilityitnewsafrica
 

Recently uploaded (20)

Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and Insights
 
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...Abdul Kader Baba- Managing Cybersecurity Risks  and Compliance Requirements i...
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
QCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesQCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architectures
 
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesMuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software Developers
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
 
Top 10 Hubspot Development Companies in 2024
Top 10 Hubspot Development Companies in 2024Top 10 Hubspot Development Companies in 2024
Top 10 Hubspot Development Companies in 2024
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to Hero
 
React Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkReact Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App Framework
 
Bridging Between CAD & GIS: 6 Ways to Automate Your Data Integration
Bridging Between CAD & GIS:  6 Ways to Automate Your Data IntegrationBridging Between CAD & GIS:  6 Ways to Automate Your Data Integration
Bridging Between CAD & GIS: 6 Ways to Automate Your Data Integration
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
 

State of Florida Neo4J Graph Briefing - Keynote

  • 1.
  • 3.
  • 5. Strictly ConfidentialStrictly Confidential • Overview: Connected data and graphs • Market landscape • Neo4j Introduction • Case studies • Wrap-up Topics
  • 6. Networks of People Business Processes Knowledge Networks E.g., Risk management, Citizen Service, Payments E.g., Employees, Citizens, Suppliers, Partners, Influencers E.g., Enterprise content, Domain specific content, eCommerce content Data connections are increasing as rapidly as data volumes The Rise of Connections in Data
  • 7. Graphs have been universally recognized as a great solution for specific types of problems - Graph Problems - and recognition is GROWING!
  • 8. Look at this data… Element Depends On A B A C A D C H D J E F E G F J G L H I J N J M L M
  • 9. Element Depends On A B A C A D C H D J E F E G F J G L H I J N J M L M Time challenge #1: What if J fails? ?
  • 10. Look at this data again…
  • 11. If your business problem has a lot of dependencies - which in IT / database terms are represented by JOINs between different entities - and if solving for these dependencies in near real time is important to you, then your problem is probably easiest solved with graph technology - and we can safely call it a GRAPH PROBLEM. Identifying Graph Problems
  • 12. 2.6 TB 11.5 million documents Emails, Scanned Documents, Bank Statements etc… The Graph Problem at Scale: Panama Papers
  • 13.
  • 14.
  • 15. DB-engines Ranking of Database Categories Graph DB 2013 2014 2015 2016 2017 2018 2019 • Graph DBMS • Key-value stores • Document stores • Wide column store • RDF stores • Time stores • Native XML DBMS • Object oriented DBMS • Multivalue DBMS • Relational DBMS Popularity of Graphs
  • 16. Strictly Confidential 16 Graph is a Top Technology Trend for 2020
  • 17. “Choice (from 3:00 to 6:00), during which the DBMS technology asset class typically moves from adolescent status into the early mainstream. This is the phase of highest growth in demand (market penetration potentially reaches 50%), during which supply options should grow…” 17 Graphs in the Early Mainstream
  • 18. Making Graph Database Market History: An Emerging Open Standard
  • 22. Neo4j is one of the Fastest Growing Skills
  • 23. 76%FORTUNE 100 have adopted or are piloting Neo4jFinance 20 of top 25 7 of top 10 Software Retail 7 of top 10 Airline s 3 of top 5 Logistic s 3 of top 5 Telco 4 of top 5 Hospitalit y 3 of top 5 Growing Adoption in the Enterprise
  • 25. Background • US IT consulting firm helped US Army streamline equipment deployments and maintenance spending • Saving lives by improving the operational readiness of Army equipment like tanks, radios, transports, aircraft, weaponry, etc. Business Problem • Needed to modernize procurement, budget and logistics processes for equipment & spare parts • Millions of connections among a tank’s bill-of- materials, for example • Improve “what if” cost calculations when planning missions and troop deployments • Mainframe systems required over 60 man-hrs to calculate changes… planning took too long. Solution and Benefits • 118M nodes & 185M relationships • Shed cost estimation times by 88% • Improved parts delivery timing and accuracy • DBA labor required dropped by 77% • Equipment TCO more predictable • Safer soldiers US Army / Calibre Systems Equipment Logistics Parts Assembly & Equipment Maintenance25
  • 26. Background • The MITRE Corporation is a federally-funded, not- for-profit company that manages cybersecurity for seven national research and development laboratories around the United States including the Center for National Security • Founded in 1958, engaged in numerous public- private partnerships as well as independent research Problem • Constantly-evolving networks – devices, configurations • Huge volumes of “noise” from virus warnings to failed logins • Isolated datapoints with no context to separate the most serious threats from the benign • Existing database could not provide the context or performance to manage a real-time environment Solution and Benefits • CyGraph - Agencies now have scalable, comprehensive analytic and visualization capabilities • Allowed agencies to capture a picture of their cybersecurity environment that connects previously isolated data points Mitre Cybersecurity for Federal Agencies 26 “CyGraph’s comprehensive knowledge base tells a much more complete story than that of basic attack graphs or mission dependency models. [It] includes potential attack-pattern relationships that fill in gaps between known vulnerabilities and threat indicators.” - Steven Noel, Principal Cybersecurity Engineer
  • 27. Background • Social network of 10M graphic artists • Peer-to-peer evaluation of art and works-in-progress • Job sourcing site for creatives • Massive, millions of updates (reads & writes) to Activity Feed • 150 Mongos to 48 Cassandras to 3 Neo4j’s! Business Problem • Artists subscribe, appreciate and curate “galleries” of works of their own and from other artists • Activities Feed is how everyone receives updates • 1st implementation was 150 MongoDB instances • 2nd implementation shrunk to 48 Cassandras, but it was still too slow and required heavy IT overhead Solution and Benefits • 3rd implementation shrunk to 3 Neo4j instances • Saved over $500k in annual AWS fees • Reduced data footprint from 50TB to 40GB • Significantly easier to introduce new features like, “New projects in you Network” Adobe Behance Social Network of 10M Graphic Artists Social Network27 EE Customer since 2016 Q
  • 28. Background • Over 7M citizens suffer from Diabetes • Connecting over 400 researchers • Incorporates over 50 databases, 100k’s of Excel workbooks, 30 database of biological samples • Sought to examine disease from as many angles as possible. Business Problem • Genes are connected by proteins or to metabolites, and patients are connected with their diets, etc… • Needed to improve the utilization of immensely technical data • Needed to cater to doctors and researchers with simple navigation, communication and connections of the graph. Solution and Benefits • Dr. Alexander Jarasch, Head of Bioinformatics and Data Management • Scientists can conduct parallel research without asking the same questions or repeating tests • Built views like a liver sample knowledge graph DZD - German Center for Diabetes Research Medical Genomic Research28 EE Customer since 2016 Q