SlideShare a Scribd company logo
1 of 18
ENEL Electricity Grids on
Neo4j Graph DB
Andrea Bielli
Solution Architect Topology Domain
Enel Grids Digital Hub
Agenda 01
ENEL GROUP
02
ENEL Grids
03
Enel Grids Digital Hub
04
ENEL Grids Topology:
Neo4j graph DB
05
ENEL Grids Topology:
Neo4j graph DB
Use Cases
06
Next Step
Copyright © 2021 Enel S.p.A. All rights reserved. 2
INTERNAL
ENEL Group
Enel's leadership
Copyright © 2023 Enel S.p.A. All rights reserved. 3
The largest private
operator in
renewables2
The operator with the
largest customer
base in the world3
1° operator in
distribution
networks1 ~76 mln
# Users
~59 GW
Renewables
~70 mln
# Customers
Capital Markets Day 2022 Data
1. By number of users. Public operators excluded
2. By installed capacity. Includes managed capacity of 3.3 GW
3. Including customers on the free energy and gas marketPublic operators excluded
INTERNAL
ENEL Group
The companies
Copyright © 2023 Enel S.p.A. All rights reserved. 4
Enel Green Power & Thermal
Generation Enel Grids
Enel X Global retail
Global Energy and
Commodity Management
Enel X Way
INTERNAL
ENEL Group
The transformation of the Group
Copyright © 2023 Enel S.p.A. All rights reserved. 5
Renewable capacities (GW)
Users (mln)
2021 2024 2030
SAIDI (min)
Renewable production
(TWh | share%)
Zero emissions production
(incl. nuclear)
RAB (Mld€)
Demand Response (GW)
Electric Bus (k)
Battery Storage1 (MW)
Charging points (mln)
Electricity sold 2 (TWh)
1. Behind the meter
2. Includes power customers
- free and regulated
market
53,4
118 | 51%
62%
75,2
243
43
~186 | 67%
77%
81
216
~77
49
~340 | 80%
>85%
86
~ 100
65
~154
309
7,7
>3
80
0,32
~13
13
~300
1,1
~353 ~550
>20
>20
>1.000
>5
INTERNAL
ENEL Group
Enel Grids overview
Copyright © 2023 Enel S.p.A. All rights reserved. 6
INTERNAL
Copyright © 2021 Enel S.p.A. All rights reserved. 7
INTERNAL
ENEL Group
The energy transition is driven by …
Copyright © 2021 Enel S.p.A. All rights reserved. 8
8
Urbanization
New customers’ needs
Digitalization
Electrification
Decarbonization
Energy Transition is not a new trend, it is just happening faster
INTERNAL
ENEL Group
Digitization: a journey through innovation
Copyright © 2023 Enel S.p.A. All rights reserved. 9
Full Cloud
Platform based
model
Digital Twin
GridVerse
Quantum Computing
INTERNAL
10
Decoupling
layer
Business services
Microservices
Solutions
Smart
Maintenance
Network
Operations
Customer
interactions
…
Network
analysis
Architectural logic structure
Asset
Inventory
… Network
topology
… Customer
& Trader
Data
Domains
Description
 Solutions to provide new
business capabilities
Numerosity
̴ 40
 Decoupling Layer enables full
Solution access to all Data
Domains
̴10.000
14
 Domains are set of data entities
supporting a consistent set of a
business process
 Publishing services on the platform
is the Domain Platformization
 Implementing a unique global data
model is the Domain Convergence
ENEL Grids Digital Hub
GBS Program & Platformization
G
B
S
INTERNAL
Insights are related to
Q1 2023 and
compared with Q1
2022
Copyright © 2023 Enel S.p.A. All rights reserved.
ENEL Grids Digital Hub
GBS Program & Pltaformization
INTERNAL
12
Entity Access (typical SQL login).
Good performance in accesses based on
plant properties, in order to retrieve the
attributes of a node without
considering the relationships.
Need for a db that could easily represent the model of
the electrical network.The graphs represent this
infrastructure well.
Navigation of the relations of a graph (typical
graphDB access). High performance in accessing
network objects related to each other, in order to
extract entire power lines and all the elements that
compose them
ENEL Grids Topology: Neo4j graph DB
Project Needs
INTERNAL
13
3 candidates
• Neo4j
• Other graph db
• SQL DB
3 databases of
different sizes
• "Small" DB containing
the network of a country
• «Medium» DB containing
the network of 3
countries
• "Large" DB containing
the 3 country network
multiplied by 5
21 sample graphs
• Starting from the three
types of network (T1 / P2
/ S2), 21 sample graphs
representing parts of the
network were extracted,
chosen by number of
elements and depth
ENEL Grids Topology: Neo4j graph DB
Decision making process
INTERNAL
14
Features Neo4J Other graph DB SQL DB
Scalability Horizontal Vertical (no sharding) Vertical (no sharding)
Availability
- Master-Slave data replication
- Supports full / incremental
backups from the running cluster
- Monitoring and restoring
instances
- Supports up to 15 read replicas
ACID Compliance Yes [1]
Yes, except for some operations in
order to increase performance
Yes
Supported graph
models
Property graph [Cypher e Gremlin]
- Property graph [Gremlin]
- RDF [SPARQL]
None [2]
Data visualization
Neo4j Bloom, integrated and highly
customizable
Absent, but third-party solutions
that can be integrated
No graph data display support
Security
- User role management
(Enterprise ed.)
- Support external authentication
systems via LDAP (eg Kerberos)
- Access management to portions
of graphs
- Isolation in VPC
- Permissions managed through
AWS IAM
- Cryptable instances with AWS
KMS
- Automatic update management
Fine grained access rights
according to SQL-standard
Graph data
analysis
Neo4j Graph Analytics, library
composed of procedures that can be
called up by cypher (centrality,
clustering, pathfinding)
Not supported Not supported
Ability to edit Yes by modifying the vertex labels
Yes through workaround on the
creation of new vertexes with
updated labels and elimination of
the old ones
Yes
License Open Source/Commercial Commercial Open Source
neo4j Other graph
DB
SQL DB
* Features analyzed at the date of the POC(Q4 2020)
ENEL Grids Topology: Neo4j graph DB
Decision making process
INTERNAL
15
≈ 150 ms
• 2Mln queries / day
• 8 countries
8 DBs (1 per country)
• 1TB data
• 600M nodes
• 800M relations
For each environment
(Dev, UAT, Prod)
• 3 server Causal cluster
• 256GB RAM, 16 cpu
ENEL Grids Topology: Neo4j graph DB
Implementation process and results obtained
INTERNAL
16
ENEL Grids Topology: Neo4j graph DB
Use Cases
INTERNAL
ENEL Grids Topology: Neo4j graph DB
Next steps
Copyright © 2021 Enel S.p.A. All rights reserved. 17
Guarantee the
availability of the 24x7
service with dedicated
support
Support high
concurrency parallel
logins
Support parallel
massive extractions
Ensure high data
access performance
Maximize high reliability
Thank you

More Related Content

What's hot

Sopra Steria: Intelligent Network Analysis in a Telecommunications Environment
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentSopra Steria: Intelligent Network Analysis in a Telecommunications Environment
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentNeo4j
 
Modeling Cybersecurity with Neo4j, Based on Real-Life Data Insights
Modeling Cybersecurity with Neo4j, Based on Real-Life Data InsightsModeling Cybersecurity with Neo4j, Based on Real-Life Data Insights
Modeling Cybersecurity with Neo4j, Based on Real-Life Data InsightsNeo4j
 
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...Neo4j
 
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...Neo4j
 
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptx
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptxNeo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptx
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptxNeo4j
 
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...Neo4j
 
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data ScienceGet Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data ScienceNeo4j
 
The Path To Success With Graph Database and Analytics
The Path To Success With Graph Database and AnalyticsThe Path To Success With Graph Database and Analytics
The Path To Success With Graph Database and AnalyticsNeo4j
 
Neo4j Graph Use Cases, Bruno Ungermann, Neo4j
Neo4j Graph Use Cases, Bruno Ungermann, Neo4jNeo4j Graph Use Cases, Bruno Ungermann, Neo4j
Neo4j Graph Use Cases, Bruno Ungermann, Neo4jNeo4j
 
Amsterdam - The Neo4j Graph Data Platform Today & Tomorrow
Amsterdam - The Neo4j Graph Data Platform Today & TomorrowAmsterdam - The Neo4j Graph Data Platform Today & Tomorrow
Amsterdam - The Neo4j Graph Data Platform Today & TomorrowNeo4j
 
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...Neo4j
 
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptxThe art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptxNeo4j
 
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...Neo4j
 
How the Neanex digital twin solution delivers on both speed and scale to the ...
How the Neanex digital twin solution delivers on both speed and scale to the ...How the Neanex digital twin solution delivers on both speed and scale to the ...
How the Neanex digital twin solution delivers on both speed and scale to the ...Neo4j
 
The Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsThe Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsNeo4j
 
Workshop - Neo4j Graph Data Science
Workshop - Neo4j Graph Data ScienceWorkshop - Neo4j Graph Data Science
Workshop - Neo4j Graph Data ScienceNeo4j
 
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...Neo4j
 
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...Neo4j
 
Supply Chain Twin Demo - Companion Deck
Supply Chain Twin Demo - Companion DeckSupply Chain Twin Demo - Companion Deck
Supply Chain Twin Demo - Companion DeckNeo4j
 
Technip Energies Italy: Planning is a graph matter
Technip Energies Italy: Planning is a graph matterTechnip Energies Italy: Planning is a graph matter
Technip Energies Italy: Planning is a graph matterNeo4j
 

What's hot (20)

Sopra Steria: Intelligent Network Analysis in a Telecommunications Environment
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentSopra Steria: Intelligent Network Analysis in a Telecommunications Environment
Sopra Steria: Intelligent Network Analysis in a Telecommunications Environment
 
Modeling Cybersecurity with Neo4j, Based on Real-Life Data Insights
Modeling Cybersecurity with Neo4j, Based on Real-Life Data InsightsModeling Cybersecurity with Neo4j, Based on Real-Life Data Insights
Modeling Cybersecurity with Neo4j, Based on Real-Life Data Insights
 
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...
Neo4j Demo: Using Knowledge Graphs to Classify Diabetes Patients (GlaxoSmithK...
 
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...
The Art of the Possible with Graph - Sudhir Hasbe - GraphSummit London 14 Nov...
 
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptx
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptxNeo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptx
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptx
 
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
 
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data ScienceGet Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
 
The Path To Success With Graph Database and Analytics
The Path To Success With Graph Database and AnalyticsThe Path To Success With Graph Database and Analytics
The Path To Success With Graph Database and Analytics
 
Neo4j Graph Use Cases, Bruno Ungermann, Neo4j
Neo4j Graph Use Cases, Bruno Ungermann, Neo4jNeo4j Graph Use Cases, Bruno Ungermann, Neo4j
Neo4j Graph Use Cases, Bruno Ungermann, Neo4j
 
Amsterdam - The Neo4j Graph Data Platform Today & Tomorrow
Amsterdam - The Neo4j Graph Data Platform Today & TomorrowAmsterdam - The Neo4j Graph Data Platform Today & Tomorrow
Amsterdam - The Neo4j Graph Data Platform Today & Tomorrow
 
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...
 
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptxThe art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
 
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...
Knowledge Graphs and Graph Data Science: More Context, Better Predictions (Ne...
 
How the Neanex digital twin solution delivers on both speed and scale to the ...
How the Neanex digital twin solution delivers on both speed and scale to the ...How the Neanex digital twin solution delivers on both speed and scale to the ...
How the Neanex digital twin solution delivers on both speed and scale to the ...
 
The Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsThe Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent Applications
 
Workshop - Neo4j Graph Data Science
Workshop - Neo4j Graph Data ScienceWorkshop - Neo4j Graph Data Science
Workshop - Neo4j Graph Data Science
 
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...
Larus: Il forte impatto della Graph Technology: l'esperienza di LARUS e numer...
 
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...
 
Supply Chain Twin Demo - Companion Deck
Supply Chain Twin Demo - Companion DeckSupply Chain Twin Demo - Companion Deck
Supply Chain Twin Demo - Companion Deck
 
Technip Energies Italy: Planning is a graph matter
Technip Energies Italy: Planning is a graph matterTechnip Energies Italy: Planning is a graph matter
Technip Energies Italy: Planning is a graph matter
 

Similar to ENEL Electricity Grids on Neo4j Graph DB

ENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBNeo4j
 
ENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBNeo4j
 
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...Edwin Poot
 
Peek into Neo4j Product Strategy and Roadmap
Peek into Neo4j Product Strategy and RoadmapPeek into Neo4j Product Strategy and Roadmap
Peek into Neo4j Product Strategy and RoadmapNeo4j
 
Gtechnology / GElectric
Gtechnology / GElectricGtechnology / GElectric
Gtechnology / GElectricGilbert Madrid
 
YugabyteDB - Distributed SQL Database on Kubernetes
YugabyteDB - Distributed SQL Database on KubernetesYugabyteDB - Distributed SQL Database on Kubernetes
YugabyteDB - Distributed SQL Database on KubernetesDoKC
 
GREEN CLOUD COMPUTING
GREEN CLOUD COMPUTINGGREEN CLOUD COMPUTING
GREEN CLOUD COMPUTINGJauwadSyed
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudDataWorks Summit
 
g-Eclipse Made Cloud Easy
g-Eclipse Made Cloud Easyg-Eclipse Made Cloud Easy
g-Eclipse Made Cloud Easygueste98511
 
g-Eclipse made Cloud Easy!
g-Eclipse made Cloud Easy!g-Eclipse made Cloud Easy!
g-Eclipse made Cloud Easy!Vyshnavi Chandu
 
Google Cloud Platform.docx
Google Cloud Platform.docxGoogle Cloud Platform.docx
Google Cloud Platform.docxgcpmastersin
 
Green cloud computing
Green cloud computingGreen cloud computing
Green cloud computingNalini Mehta
 
Lift Your Legacy UNIX Applications & Databases into the Cloud
Lift Your Legacy UNIX Applications & Databases into the Cloud Lift Your Legacy UNIX Applications & Databases into the Cloud
Lift Your Legacy UNIX Applications & Databases into the Cloud Fadi Semaan
 
Optimizing Your Supply Chain with Neo4j
Optimizing Your Supply Chain with Neo4jOptimizing Your Supply Chain with Neo4j
Optimizing Your Supply Chain with Neo4jNeo4j
 
2018 08-13-ib ms-latest-buzz-share-final
2018 08-13-ib ms-latest-buzz-share-final2018 08-13-ib ms-latest-buzz-share-final
2018 08-13-ib ms-latest-buzz-share-finalDavid Morlitz
 
Extending twitter's data platform to google cloud
Extending twitter's data platform to google cloud Extending twitter's data platform to google cloud
Extending twitter's data platform to google cloud Vrushali Channapattan
 
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready Enterprise
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready EnterpriseRe-Architect Your Legacy Environment To Enable An Agile, Future-Ready Enterprise
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready EnterpriseDell World
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud lohitvijayarenu
 

Similar to ENEL Electricity Grids on Neo4j Graph DB (20)

ENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DB
 
ENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DBENEL Electricity Topology Network on Neo4j Graph DB
ENEL Electricity Topology Network on Neo4j Graph DB
 
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...
Analyzing petabytes of smartmeter data using Cloud Bigtable, Cloud Dataflow, ...
 
Peek into Neo4j Product Strategy and Roadmap
Peek into Neo4j Product Strategy and RoadmapPeek into Neo4j Product Strategy and Roadmap
Peek into Neo4j Product Strategy and Roadmap
 
Gtechnology / GElectric
Gtechnology / GElectricGtechnology / GElectric
Gtechnology / GElectric
 
YugabyteDB - Distributed SQL Database on Kubernetes
YugabyteDB - Distributed SQL Database on KubernetesYugabyteDB - Distributed SQL Database on Kubernetes
YugabyteDB - Distributed SQL Database on Kubernetes
 
Cloud & Data Center Networking
Cloud & Data Center NetworkingCloud & Data Center Networking
Cloud & Data Center Networking
 
GREEN CLOUD COMPUTING
GREEN CLOUD COMPUTINGGREEN CLOUD COMPUTING
GREEN CLOUD COMPUTING
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud
 
g-Eclipse Made Cloud Easy
g-Eclipse Made Cloud Easyg-Eclipse Made Cloud Easy
g-Eclipse Made Cloud Easy
 
g-Eclipse made Cloud Easy!
g-Eclipse made Cloud Easy!g-Eclipse made Cloud Easy!
g-Eclipse made Cloud Easy!
 
Google Cloud Platform.docx
Google Cloud Platform.docxGoogle Cloud Platform.docx
Google Cloud Platform.docx
 
Green cloud computing
Green cloud computingGreen cloud computing
Green cloud computing
 
Lift Your Legacy UNIX Applications & Databases into the Cloud
Lift Your Legacy UNIX Applications & Databases into the Cloud Lift Your Legacy UNIX Applications & Databases into the Cloud
Lift Your Legacy UNIX Applications & Databases into the Cloud
 
Optimizing Your Supply Chain with Neo4j
Optimizing Your Supply Chain with Neo4jOptimizing Your Supply Chain with Neo4j
Optimizing Your Supply Chain with Neo4j
 
Green cloud computing
Green  cloud computingGreen  cloud computing
Green cloud computing
 
2018 08-13-ib ms-latest-buzz-share-final
2018 08-13-ib ms-latest-buzz-share-final2018 08-13-ib ms-latest-buzz-share-final
2018 08-13-ib ms-latest-buzz-share-final
 
Extending twitter's data platform to google cloud
Extending twitter's data platform to google cloud Extending twitter's data platform to google cloud
Extending twitter's data platform to google cloud
 
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready Enterprise
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready EnterpriseRe-Architect Your Legacy Environment To Enable An Agile, Future-Ready Enterprise
Re-Architect Your Legacy Environment To Enable An Agile, Future-Ready Enterprise
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud
 

More from Neo4j

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansQIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansNeo4j
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityNeo4j
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Neo4j
 
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
 

More from Neo4j (20)

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansQIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024
 
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
 

Recently uploaded

Smarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxSmarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxolyaivanovalion
 
Introduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxIntroduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxfirstjob4
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfLars Albertsson
 
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptxEMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptxthyngster
 
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiLow Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiSuhani Kapoor
 
BabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxBabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxolyaivanovalion
 
Industrialised data - the key to AI success.pdf
Industrialised data - the key to AI success.pdfIndustrialised data - the key to AI success.pdf
Industrialised data - the key to AI success.pdfLars Albertsson
 
Unveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystUnveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystSamantha Rae Coolbeth
 
Generative AI on Enterprise Cloud with NiFi and Milvus
Generative AI on Enterprise Cloud with NiFi and MilvusGenerative AI on Enterprise Cloud with NiFi and Milvus
Generative AI on Enterprise Cloud with NiFi and MilvusTimothy Spann
 
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...Suhani Kapoor
 
VidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxVidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxolyaivanovalion
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfMarinCaroMartnezBerg
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionfulawalesam
 
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130Suhani Kapoor
 
BigBuy dropshipping via API with DroFx.pptx
BigBuy dropshipping via API with DroFx.pptxBigBuy dropshipping via API with DroFx.pptx
BigBuy dropshipping via API with DroFx.pptxolyaivanovalion
 
Dubai Call Girls Wifey O52&786472 Call Girls Dubai
Dubai Call Girls Wifey O52&786472 Call Girls DubaiDubai Call Girls Wifey O52&786472 Call Girls Dubai
Dubai Call Girls Wifey O52&786472 Call Girls Dubaihf8803863
 
Beautiful Sapna Vip Call Girls Hauz Khas 9711199012 Call /Whatsapps
Beautiful Sapna Vip  Call Girls Hauz Khas 9711199012 Call /WhatsappsBeautiful Sapna Vip  Call Girls Hauz Khas 9711199012 Call /Whatsapps
Beautiful Sapna Vip Call Girls Hauz Khas 9711199012 Call /Whatsappssapnasaifi408
 
Ukraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSUkraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSAishani27
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxolyaivanovalion
 

Recently uploaded (20)

Smarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxSmarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptx
 
Introduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxIntroduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptx
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdf
 
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptxEMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
 
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiLow Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
 
BabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxBabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptx
 
Industrialised data - the key to AI success.pdf
Industrialised data - the key to AI success.pdfIndustrialised data - the key to AI success.pdf
Industrialised data - the key to AI success.pdf
 
Unveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystUnveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data Analyst
 
Generative AI on Enterprise Cloud with NiFi and Milvus
Generative AI on Enterprise Cloud with NiFi and MilvusGenerative AI on Enterprise Cloud with NiFi and Milvus
Generative AI on Enterprise Cloud with NiFi and Milvus
 
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Jamshedpur Anushka 8250192130 Independent Escort Se...
 
VidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxVidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptx
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdf
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interaction
 
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130
VIP Call Girls Service Miyapur Hyderabad Call +91-8250192130
 
BigBuy dropshipping via API with DroFx.pptx
BigBuy dropshipping via API with DroFx.pptxBigBuy dropshipping via API with DroFx.pptx
BigBuy dropshipping via API with DroFx.pptx
 
Dubai Call Girls Wifey O52&786472 Call Girls Dubai
Dubai Call Girls Wifey O52&786472 Call Girls DubaiDubai Call Girls Wifey O52&786472 Call Girls Dubai
Dubai Call Girls Wifey O52&786472 Call Girls Dubai
 
E-Commerce Order PredictionShraddha Kamble.pptx
E-Commerce Order PredictionShraddha Kamble.pptxE-Commerce Order PredictionShraddha Kamble.pptx
E-Commerce Order PredictionShraddha Kamble.pptx
 
Beautiful Sapna Vip Call Girls Hauz Khas 9711199012 Call /Whatsapps
Beautiful Sapna Vip  Call Girls Hauz Khas 9711199012 Call /WhatsappsBeautiful Sapna Vip  Call Girls Hauz Khas 9711199012 Call /Whatsapps
Beautiful Sapna Vip Call Girls Hauz Khas 9711199012 Call /Whatsapps
 
Ukraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSUkraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICS
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptx
 

ENEL Electricity Grids on Neo4j Graph DB

  • 1. ENEL Electricity Grids on Neo4j Graph DB Andrea Bielli Solution Architect Topology Domain Enel Grids Digital Hub
  • 2. Agenda 01 ENEL GROUP 02 ENEL Grids 03 Enel Grids Digital Hub 04 ENEL Grids Topology: Neo4j graph DB 05 ENEL Grids Topology: Neo4j graph DB Use Cases 06 Next Step Copyright © 2021 Enel S.p.A. All rights reserved. 2
  • 3. INTERNAL ENEL Group Enel's leadership Copyright © 2023 Enel S.p.A. All rights reserved. 3 The largest private operator in renewables2 The operator with the largest customer base in the world3 1° operator in distribution networks1 ~76 mln # Users ~59 GW Renewables ~70 mln # Customers Capital Markets Day 2022 Data 1. By number of users. Public operators excluded 2. By installed capacity. Includes managed capacity of 3.3 GW 3. Including customers on the free energy and gas marketPublic operators excluded
  • 4. INTERNAL ENEL Group The companies Copyright © 2023 Enel S.p.A. All rights reserved. 4 Enel Green Power & Thermal Generation Enel Grids Enel X Global retail Global Energy and Commodity Management Enel X Way
  • 5. INTERNAL ENEL Group The transformation of the Group Copyright © 2023 Enel S.p.A. All rights reserved. 5 Renewable capacities (GW) Users (mln) 2021 2024 2030 SAIDI (min) Renewable production (TWh | share%) Zero emissions production (incl. nuclear) RAB (Mld€) Demand Response (GW) Electric Bus (k) Battery Storage1 (MW) Charging points (mln) Electricity sold 2 (TWh) 1. Behind the meter 2. Includes power customers - free and regulated market 53,4 118 | 51% 62% 75,2 243 43 ~186 | 67% 77% 81 216 ~77 49 ~340 | 80% >85% 86 ~ 100 65 ~154 309 7,7 >3 80 0,32 ~13 13 ~300 1,1 ~353 ~550 >20 >20 >1.000 >5
  • 6. INTERNAL ENEL Group Enel Grids overview Copyright © 2023 Enel S.p.A. All rights reserved. 6
  • 7. INTERNAL Copyright © 2021 Enel S.p.A. All rights reserved. 7
  • 8. INTERNAL ENEL Group The energy transition is driven by … Copyright © 2021 Enel S.p.A. All rights reserved. 8 8 Urbanization New customers’ needs Digitalization Electrification Decarbonization Energy Transition is not a new trend, it is just happening faster
  • 9. INTERNAL ENEL Group Digitization: a journey through innovation Copyright © 2023 Enel S.p.A. All rights reserved. 9 Full Cloud Platform based model Digital Twin GridVerse Quantum Computing
  • 10. INTERNAL 10 Decoupling layer Business services Microservices Solutions Smart Maintenance Network Operations Customer interactions … Network analysis Architectural logic structure Asset Inventory … Network topology … Customer & Trader Data Domains Description  Solutions to provide new business capabilities Numerosity ̴ 40  Decoupling Layer enables full Solution access to all Data Domains ̴10.000 14  Domains are set of data entities supporting a consistent set of a business process  Publishing services on the platform is the Domain Platformization  Implementing a unique global data model is the Domain Convergence ENEL Grids Digital Hub GBS Program & Platformization G B S
  • 11. INTERNAL Insights are related to Q1 2023 and compared with Q1 2022 Copyright © 2023 Enel S.p.A. All rights reserved. ENEL Grids Digital Hub GBS Program & Pltaformization
  • 12. INTERNAL 12 Entity Access (typical SQL login). Good performance in accesses based on plant properties, in order to retrieve the attributes of a node without considering the relationships. Need for a db that could easily represent the model of the electrical network.The graphs represent this infrastructure well. Navigation of the relations of a graph (typical graphDB access). High performance in accessing network objects related to each other, in order to extract entire power lines and all the elements that compose them ENEL Grids Topology: Neo4j graph DB Project Needs
  • 13. INTERNAL 13 3 candidates • Neo4j • Other graph db • SQL DB 3 databases of different sizes • "Small" DB containing the network of a country • «Medium» DB containing the network of 3 countries • "Large" DB containing the 3 country network multiplied by 5 21 sample graphs • Starting from the three types of network (T1 / P2 / S2), 21 sample graphs representing parts of the network were extracted, chosen by number of elements and depth ENEL Grids Topology: Neo4j graph DB Decision making process
  • 14. INTERNAL 14 Features Neo4J Other graph DB SQL DB Scalability Horizontal Vertical (no sharding) Vertical (no sharding) Availability - Master-Slave data replication - Supports full / incremental backups from the running cluster - Monitoring and restoring instances - Supports up to 15 read replicas ACID Compliance Yes [1] Yes, except for some operations in order to increase performance Yes Supported graph models Property graph [Cypher e Gremlin] - Property graph [Gremlin] - RDF [SPARQL] None [2] Data visualization Neo4j Bloom, integrated and highly customizable Absent, but third-party solutions that can be integrated No graph data display support Security - User role management (Enterprise ed.) - Support external authentication systems via LDAP (eg Kerberos) - Access management to portions of graphs - Isolation in VPC - Permissions managed through AWS IAM - Cryptable instances with AWS KMS - Automatic update management Fine grained access rights according to SQL-standard Graph data analysis Neo4j Graph Analytics, library composed of procedures that can be called up by cypher (centrality, clustering, pathfinding) Not supported Not supported Ability to edit Yes by modifying the vertex labels Yes through workaround on the creation of new vertexes with updated labels and elimination of the old ones Yes License Open Source/Commercial Commercial Open Source neo4j Other graph DB SQL DB * Features analyzed at the date of the POC(Q4 2020) ENEL Grids Topology: Neo4j graph DB Decision making process
  • 15. INTERNAL 15 ≈ 150 ms • 2Mln queries / day • 8 countries 8 DBs (1 per country) • 1TB data • 600M nodes • 800M relations For each environment (Dev, UAT, Prod) • 3 server Causal cluster • 256GB RAM, 16 cpu ENEL Grids Topology: Neo4j graph DB Implementation process and results obtained
  • 16. INTERNAL 16 ENEL Grids Topology: Neo4j graph DB Use Cases
  • 17. INTERNAL ENEL Grids Topology: Neo4j graph DB Next steps Copyright © 2021 Enel S.p.A. All rights reserved. 17 Guarantee the availability of the 24x7 service with dedicated support Support high concurrency parallel logins Support parallel massive extractions Ensure high data access performance Maximize high reliability

Editor's Notes

  1. Oggi parleremo di come Enel ha adottato la tecnologia dei db a grafo con neo4j nella gestione delle reti elettriche in 8 paesi nel mondo. Con l'obiettivo di ottimizzare gli algoritmi di percorrenza della rete elettrica, in modo da rendere le reti sempre più efficienti e resilienti. per garantire gli obiettivi del gruppo: la transizione energetica e l'elettrificazione dei paesi in cui opera, verso l'obiettivo Net Zero, relativo alla riduzione delle emissioni nella produzione e distribuzione dell'energia elettrica.
  2. Iniziamo introducendo un po’ cos’è Enel non è solo L’Ente nazionale dell’energia elettrica. Ma è una multinazionale presente in oltre 20 paesi in tutti i continenti. È il più grande operatore di distribuzione al mondo (esclusi operatori pubblici es Cina) È il più grande operatore privato nelle rinnovabili E l’operatore con il maggior numero di clienti al mondo Quindi Enel porta la sua capacità di produrre, e distribuire energia in tutto il mondo ed è quindi leader e trainante nelle sfide della transizione energetica che stiamo vivendo
  3. Enel è presente in tutto il mondo non solo come produttore e distributore di energia. Con le sue società offre numerosi servizi. Queste sono le società di Enel: Global Power Generation (green power + thermal power) Enel X way per i servizi legati alla elettrificazione e alle smart cities Enel Grids gestisce le reti di distribuzione dalle centrali fino alla consegna
  4. Come dicevamo prima, Enel ha un ruolo determinante nei processi di trasformazione, e transizione energetica che il mondo si sta predisponendo a fare. Questo si ripercuote su obiettivi estremamente sfidanti per Enel, che ci portano a fare continuamente innovazione e grandi investimenti per riuscire in un obiettivo cosi importante. Ognuna delle società con le sue peculiarità ha posto obiettivi enormi, semplicemente se confontiamo la crescita tra il 21 e il 24 e quella con il 30. Ovviamente tutti questi obiettivi contribuiscono al più grande che è quello del Net Zero, ovvero la riduzione fino a zero delle emizssioni nella produzione di energia. Una elettrificazione cosi forte passa da una componente estremamente importante, una rete di grande qualità che riduce gli sprechi e arriva ovunque. Che è l’obiettivo di Enel Grids
  5. In particolare è all’interno della società Enel Grids, in cui io lavoro, che è stato scelto di utilizzare neo4j. Proprio per gestire la topologia e il grafo della rete elettrica. Enel Grids gestisce e distribuisce energia su 2Mln di km di line elettriche in 8 paesi (alcuni di questi sono usciti da poco dalla strategia e sono in vendita) In ognuno di questi paese è primo o secondo distributore, proprio perché l’obiettivo è migliorare drasticamente la qualità del servizio nei paesi in cui si trova, non si tratta semplicemente di entrare in un mercato.
  6. E come dicevamo prima Enel Grids è in una posizione centrale e determinante in quel processo di elettrificazione e trasizione energetica. Sostanzialmente perché è l’infrastruttura abilitante, che permette di distribuire energia al meglio, senza sprechi e con grande qualità l’energia. Rendendo efficiente la produzione e raggiungendo i clienti ovunque Questo si traduce in linee elettriche sempre più smart, telecontrollate e resilienti.
  7. Il processo di transizione che Enel sta facendo si basa su questi pillar: Decarbonizzazione (che è anche l’obiettivo principale del gruppo) Digitalizzazione Centralità dei clienti Elettrificazione (che va di pari passo con la decarbonizzazione e la digitalizzazione) Urbanizzazione (per rendere sempre più smart le grandi città e renderle più efficienti energeticamente) Come vedete la digitalizzazione è uno dei pillar fondamentali ed è al centro. Anche se enel è una società di energia, utilities, perché mette al digitalizzazione al centro? Enel è una delle pochissime aziende nel suo campo, ma anche in altri, ad aver messo al centro la digitalizzazione. Nel processo di trasformazione digitale ha avuto il coraggio di digitalizzare l’intera azienda. Non ha fatto come molte che hanno creato degli spinoff totalmente digitali. Questo denota la forte propensione dell’azienda all’innovazione dedicando Grandi investimenti nel piano strategico comunicato qualche anno fa.
  8. In ambito Grids l’approccio all’innovazione è estremamente importante e lo si può vedere nei temi riportati in questa slide. Grids sta intraprendendo un viaggio estremamente veloce e sempre in anticipo, andando a credere e sviluppare sulle tecnologie più moderne. L’esempio più eclatante è che Enel ha deciso di migrare tutto in cloud tutto dal 2015, completando la migraazione nel 2019. Nel 2015 solo le startup erano in cloud e negli ambienti delle grande imprese, soprattutto italiane, se ne parlava solamente. Full Cloud We are the world’s first large utility company to fully embrace the cloud model. From 2015, in april 2019 Enel became “full cloud” Un secondo grande passo è stato il cambio totale di modello, sia in ambito tecnologico che di business. L’implementazione della platform, di cui parlo nella prossima slide, traforma totalemnte l’approccio allo sviluppo. E’ un totale passaggio verso applicazioni a microservizi. In questo ambito orami in enel si parla di sistemi legacy riferendosi a quelli in IaaS Platform based model The Enel Digital Platform is a set of infrastructure, tools, manual and automated procedures that allow a faster, more reliable and more efficient management and development of digital solutions. La platform è lo strumento che ci sta aiutando a definire un vero e proprio Digital twin della rete elettrica. Stiamo testando e sviluppando nuove tecnologie come il Quantum Computing per migliorare la pianificazione delle attività in campo, il Quantum Edge Device per la digitalizzazione delle cabine secondarie, o il Network Digital Twin con i suoi modelli di analisi dei dati ottimizzare la pianificazione della rete, per rendere i lavori più efficienti o per la formazione sulla sicurezza. La prossima milestone del percorso di digitalizzazione delle reti di Enel, in effetti, deriva dall'intersezione di diverse tecnologie ormai mature: il modello di piattaforma digitale, l'ecosistema dei social network e il sistema Network Digital Twin. Le opportunità che possono scaturire dalla combinazione di queste tre tecnologie si materializzano in quello che viene chiamato il Metaverso, un articolato ecosistema di tecnologie che possono essere combinate in modo originale per fornire un’esperienza di collaborazione e interazione immersiva e in tempo reale sia con altre persone che con oggetti in uno spazio virtuale che simula il contesto reale. Per le reti il GridVerse sarà una delle tante istanze interoperabili del Metaverso che ospiterà casi d’uso relativi alla progettazione collaborativa, all’addestramento virtuale, all’assistenza remota e alla simulazione del comportamento delle reti.
  9. IT Platformization represents a new way of developing IT Systems and revolves around a common denominator to enable new platform businesses and operating models. Evolving towards an IT Platform Model means: Moving away from the development of applications based on vertical systems to the development of solutions. Being able to integrate with what is being done, and this requires introducing a decoupling layer separating data from solutions. Sharing and democratizing data. The adoption of an IT Platform model means: More Speed, thanks to re-use and shared services. Unleashed Data Potential, thanks to systems integration by design. Enable New Business Models & Platform Operating Models, thanks to a new way of developing IT systems. Enable Decoupling Democratize Data Support Productivity Guarantee Sustainability Build a Community Plan For Growth
  10. Enel Grids crede moltissimo in questo nuovo approccio allo sviluppo e sta migrando tutte le applicazioni verso le solution in platform. L’investimento è enorme ma i risultati si vedono e qui vediamo come sta crescendo l’utilizzo della platform
  11. Nell’ambito di Enel Grids, il dominio Topology, forse il più importante perché contiene i dati relativi alla topologia della rete elettrica, le connessioni tra i vari elementi e la configurazione della rete in tutte le country gestite. 3 anni fa, quando è stato deciso di fare questa migrazione alla platform, ci si è chiesti quale fosse il modo migliore di descrivere al topologia della rete. Fino a quel momento la rete e le relative relazioni tra i nodi erano definiti su un db sql Oracle. Ora ci si prospettava la possibilità di scegliere un db che possa rappresentare al meglio una infrastruttura come la rete elettrica, che appunto è proprio un grafo (come vedete nell’immagine). Una serie di elementi collegati tra loro da connessioni elettriche e gerarchiche. Inoltre c’era l’esigenza di rendere il più veloce, performante e efficiente la percorrenza della rete. Ovvero fare delle estrazioni da una cabina primaria fino ai clienti alimentati, o verificare la presenza di magliature o controalimentazioni. Questi campi di applicazione sono estremamamente importanti per garantire una rete efficiente, sicura e resiliente. Per fare calcoli di rete, curve di carico, analisi sulla qualità del servizio ecc. La terza esigenza importante era che il nuovo db doveva garantire al tempo stesso ottime performance nel caso di accessi sql like. Ovvero non basarsi solo su etichette e relazioni, ma ricerche di entità sugli attributi e sugli indici.
  12. Nel processo di scelta del db abbiamo fatto dei test di comparazione tra 3 differenti prodotti e tecnologie per vedere come si comportavano con le nostre esigenze. Neo4j Un altro graphdb (di un altro produttore) E un sql db Abbiamo identificato 3 set di dati di grandezza differente per eseguire i test con carichi differenti Successivamente abbiamo definito 21 tipologie di estrazione di rete da eseguire sui 3 db e sui 3 differenti set di dati
  13. I risultati dei test hanno evidenziato neo4j come la miglior scelta. Come vedete ci sono stati casi di test in cui le alter tecnologie sono state più performanti, ma in generale neo4j si è rivelato più adattabile a tutti I casi e vincendo nella maggior parte dei confronti. Inoltre anche le features offerte dai prodotti risultavano migliori per neo4j
  14. Ad oggi neo4j è quindi il db ufficiale della topologia delle rete, e su cui si stanno migrando tutte le applicazioni (solution) Il tasso di utilizzo è in costante aumento e ogni giorno riceve più query e il carico aumenta Questa è la sfida su cui lo stiamo mettendo alla prova, stiamo cercando di renderlo sempre più efficente all’aumentare del carico che non riusciamo ancora a stimare ma sarà di diversi ordini di grandezza superiori a quello attuale
  15. Ora vediamo dei casi d’uso in cui l’utilizzo di neo4j ha abilitato funzioni molto important per enel e su cui stiamo anche cercando di fare innovazione. Nel primo caso vediamo il pannello cartografico su cui la rete viene progettata e pianificata. Il secondo caso è un po’ un’anteprima, e rappresenta il GridVerse. Ovvero il metaverso della rete. Che permetterà ai nostri colleghi che lavorano sul campo, e che progettano la rete, di avere una versione, un digital twin della rete, il più realistico possibile. Permettendo un giorno di lavorare anche a distanza. Offrendo anche una realtà aumentata che facilita il lavoro e lo rende più sicuro.
  16. I prossimi passi, come dicevo prima saranno quelli di rendere la nostra architettura sempre più resiliente e meglio gestita. Visto che il carico è in continuo aumento. Per questo stiamo pensando di andare verso una soluzione ibrida, dal momento che aura db non è ancora adatto alle nostre esigenze in cui abbiamo molte apoc custom sviluppate per migliorare la percorrenza di rete. Ma andremo verso una soluzione in cui I servizi di neo4j, il CMS prenderà in carico la nostra infrastruttura e gestirà I nostril ambienti 24x7