The document describes an event for GraphTalks Zürich in July 2017. It includes an agenda with presentations on graph databases and Neo4j, visualizing big data sets in the pharmaceutical industry using graph databases, and an open networking session.
An Agile & Adaptive Approach to Addressing Financial Services Regulations and...Neo4j
Watch this webinar and learn how Neo4j and ICC Technology can help you remove risk from your data governance by improving the way you approach data lineage. We’ll cover some of the common approaches, driving regulations and biggest risks for banks and finances services.
-Find out how Data Lineage is becoming more complex for Banks and Financial Services companies
-Learn how a native-graph model can improve tracing data sources to targets as well as store transformations.
-Watch a demonstration on how you might approach regulations such as BCBS 239
Enterprises are faced by information overload. Big data appears as an opportunity, but has no relevance until enterprises can put it in context of their activities, processes, and organizations, Applying MDM principles to Big Data is therefore an opportunity that enterprises should target.
This presentation covers the following topics :
- what is MDM and Information Management
- what is Big Data and what are the use cases
- why and how Big Data can take advantage of MDM ? why and how MDM can take advantage of Big Data ?
This document contains an agenda for the first Tel Aviv Graph Days event hosted by Neo Technology. The agenda includes sessions on graph databases and their real-world use cases, a Neo4j hands-on demo, experiences from partners using Neo4j, and introductory training sessions. There will also be graph clinics and talks on building customer understanding, graph database architectures, and complexity in the Internet of Things using a graph model.
Implementing Data Virtualization for Data Warehouses and Master Data Manageme...Denodo
The ongoing evolution of business requirements and growth of data volumes continue to put added challenges on existing DW and MDM implementations. Challenges that in many cases cannot be met. Data Virtualization compliments existing DW, MDM and other architectures and business initiatives, providing the agility and flexibility - at a lower cost – for the enablement of Virtual MDM, self-service BI, operational BI, rapid prototyping and real-time analytics.
More information and FREE registrations for this webinar: http://goo.gl/asYztF
Landing page for the entire Packed Lunch webinar series: http://goo.gl/NATMHw
Attend & get unique insights into:
How Data Virtualization can provide a simple and low cost alternative to traditional DW and MDM solutions
How Data Virtualization can enhance and extend existing DW or MDM solutions to provide a more agile data integration architecture
Case studies that demonstrate how Data Virtualization has increased agility to meet complex information needs
What is big data - Architectures and Practical Use CasesTony Pearson
1. Big data is the analysis of large volumes of diverse data to identify trends, patterns and insights to make better business decisions. It allows companies to cost efficiently process growing data volumes and collectively analyze the broadening variety of data.
2. The document discusses architectures and practical use cases of big data. It provides examples of how companies are using big data to optimize operations, innovate new products, and gain instant awareness of fraud and risk.
3. Realizing the opportunities of big data requires thinking beyond traditional data sources to include machine, transactional, social, and enterprise content data. It also requires multiple platform capabilities like Hadoop, data warehousing, and stream computing.
Neo4j Partner Tag Berlin - Potential für System-Integratoren und Berater Neo4j
This document summarizes a Neo4j partner event. It includes an agenda with sessions on the business potential of Neo4j for system integrators and consultants, the Neo4j partner program, and a case study on using Neo4j to analyze the Panama Papers. There are also sessions on quickly gaining value from Neo4j and on modeling logistics processes with Neo4j.
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3rpr4La
Data is an insurer’s most valuable asset. Capitalizing on all of that stored and incoming data to draw valuable insights for business decisions is what ultimately makes a competitive difference.
But, insurers face challenges when it comes to modernizing and digitizing their data architectures. Most organizations rely on traditional systems and data integration processes that are time consuming and slow. In addition, as many adopt cloud strategies, these traditional approaches fill the cloud modernization process with downtime and end user frustration.
This is why insurers need a flexible and easily adaptable data integration technology that allows them to keep up with the ever-changing and growing data environment.
Data virtualization is that modern data integration technology. It can support insurers not only on their journey to digitization, but also on their future infrastructure changes and innovations, adding agility, flexibility and efficiency to data architectures. Data virtualization can help insurance companies create 360° views of deals and claims processes as well as gather quick social media or sensor data for on-the-go risk profiling.
Join this on-demand webinar to:
- Find out why data virtualization should be a part of your enterprise data strategy
- See how this technology can help you capitalize on your data
- Hear how many of your peers are already leveraging the Denodo Platform for Data Virtualization and the benefits they’re observing
This document discusses building a Hadoop capability within an organization. It recommends creating a sense of urgency around opportunities not currently possible, building a guiding coalition of potential users and partners, and formalizing use cases. It also suggests enlisting an excited volunteer team, starting small to remove barriers, generating short-term wins, sustaining acceleration through communication of successes, and instituting Hadoop as the default platform. Examples of proof of concepts include search, archival, real-time analytics, and log analysis. Challenges discussed include leveraging other teams, documenting work, building reusable solutions, using the full Hadoop stack, failing quickly and learning, and gaining developer skills.
An Agile & Adaptive Approach to Addressing Financial Services Regulations and...Neo4j
Watch this webinar and learn how Neo4j and ICC Technology can help you remove risk from your data governance by improving the way you approach data lineage. We’ll cover some of the common approaches, driving regulations and biggest risks for banks and finances services.
-Find out how Data Lineage is becoming more complex for Banks and Financial Services companies
-Learn how a native-graph model can improve tracing data sources to targets as well as store transformations.
-Watch a demonstration on how you might approach regulations such as BCBS 239
Enterprises are faced by information overload. Big data appears as an opportunity, but has no relevance until enterprises can put it in context of their activities, processes, and organizations, Applying MDM principles to Big Data is therefore an opportunity that enterprises should target.
This presentation covers the following topics :
- what is MDM and Information Management
- what is Big Data and what are the use cases
- why and how Big Data can take advantage of MDM ? why and how MDM can take advantage of Big Data ?
This document contains an agenda for the first Tel Aviv Graph Days event hosted by Neo Technology. The agenda includes sessions on graph databases and their real-world use cases, a Neo4j hands-on demo, experiences from partners using Neo4j, and introductory training sessions. There will also be graph clinics and talks on building customer understanding, graph database architectures, and complexity in the Internet of Things using a graph model.
Implementing Data Virtualization for Data Warehouses and Master Data Manageme...Denodo
The ongoing evolution of business requirements and growth of data volumes continue to put added challenges on existing DW and MDM implementations. Challenges that in many cases cannot be met. Data Virtualization compliments existing DW, MDM and other architectures and business initiatives, providing the agility and flexibility - at a lower cost – for the enablement of Virtual MDM, self-service BI, operational BI, rapid prototyping and real-time analytics.
More information and FREE registrations for this webinar: http://goo.gl/asYztF
Landing page for the entire Packed Lunch webinar series: http://goo.gl/NATMHw
Attend & get unique insights into:
How Data Virtualization can provide a simple and low cost alternative to traditional DW and MDM solutions
How Data Virtualization can enhance and extend existing DW or MDM solutions to provide a more agile data integration architecture
Case studies that demonstrate how Data Virtualization has increased agility to meet complex information needs
What is big data - Architectures and Practical Use CasesTony Pearson
1. Big data is the analysis of large volumes of diverse data to identify trends, patterns and insights to make better business decisions. It allows companies to cost efficiently process growing data volumes and collectively analyze the broadening variety of data.
2. The document discusses architectures and practical use cases of big data. It provides examples of how companies are using big data to optimize operations, innovate new products, and gain instant awareness of fraud and risk.
3. Realizing the opportunities of big data requires thinking beyond traditional data sources to include machine, transactional, social, and enterprise content data. It also requires multiple platform capabilities like Hadoop, data warehousing, and stream computing.
Neo4j Partner Tag Berlin - Potential für System-Integratoren und Berater Neo4j
This document summarizes a Neo4j partner event. It includes an agenda with sessions on the business potential of Neo4j for system integrators and consultants, the Neo4j partner program, and a case study on using Neo4j to analyze the Panama Papers. There are also sessions on quickly gaining value from Neo4j and on modeling logistics processes with Neo4j.
A Successful Data Strategy for Insurers in Volatile Times (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3rpr4La
Data is an insurer’s most valuable asset. Capitalizing on all of that stored and incoming data to draw valuable insights for business decisions is what ultimately makes a competitive difference.
But, insurers face challenges when it comes to modernizing and digitizing their data architectures. Most organizations rely on traditional systems and data integration processes that are time consuming and slow. In addition, as many adopt cloud strategies, these traditional approaches fill the cloud modernization process with downtime and end user frustration.
This is why insurers need a flexible and easily adaptable data integration technology that allows them to keep up with the ever-changing and growing data environment.
Data virtualization is that modern data integration technology. It can support insurers not only on their journey to digitization, but also on their future infrastructure changes and innovations, adding agility, flexibility and efficiency to data architectures. Data virtualization can help insurance companies create 360° views of deals and claims processes as well as gather quick social media or sensor data for on-the-go risk profiling.
Join this on-demand webinar to:
- Find out why data virtualization should be a part of your enterprise data strategy
- See how this technology can help you capitalize on your data
- Hear how many of your peers are already leveraging the Denodo Platform for Data Virtualization and the benefits they’re observing
This document discusses building a Hadoop capability within an organization. It recommends creating a sense of urgency around opportunities not currently possible, building a guiding coalition of potential users and partners, and formalizing use cases. It also suggests enlisting an excited volunteer team, starting small to remove barriers, generating short-term wins, sustaining acceleration through communication of successes, and instituting Hadoop as the default platform. Examples of proof of concepts include search, archival, real-time analytics, and log analysis. Challenges discussed include leveraging other teams, documenting work, building reusable solutions, using the full Hadoop stack, failing quickly and learning, and gaining developer skills.
BAR360 open data platform presentation at DAMA, SydneySai Paravastu
Sai Paravastu discusses the benefits of using an open data platform (ODP) for enterprises. The ODP would provide a standardized core of open source Hadoop technologies like HDFS, YARN, and MapReduce. This would allow big data solution providers to build compatible solutions on a common platform, reducing costs and improving interoperability. The ODP would also simplify integration for customers and reduce fragmentation in the industry by coordinating development efforts.
Accelerate Digital Transformation with Data Virtualization in Banking, Financ...Denodo
Watch full webinar here: https://bit.ly/38uCCUB
Banking, Financial Services and Insurance (BFSI) organizations are globally accelerating their digital journey, making rapid strides with their digitization efforts, and adding key capabilities to adapt and innovate in the new normal.
Many companies find digital transformation challenging as they rely on established systems that are often not only poorly integrated, but also highly resistant to modernization without downtime. Hear how the BFSI industry is leveraging data virtualization that facilitates digital transformation via a modern data integration / data delivery approach to gain greater agility, flexibility, and efficiency.
In this joint live webinar session from Denodo and Wipro, you will learn:
- Industry key trends and challenges driving the digital transformation mandate and platform modernization initiatives
- Key concepts of Data Virtualization, and how it can enable BFSI customers to develop critical capabilities for real-time / near real-time data integration
- Success Stories on organizations who already use data virtualization to differentiate themselves from the competition
- Wipro’s role in helping enterprises define the business case, end-to-end services and operating model for the successful data virtualization implementations
Schedule a Discovery Session to learn more about Wipro and Denodo joint solutions for Banking, Financial Services, and Insurance.
The data services marketplace is enabled by a data abstraction layer that supports rapid development of operational applications and single data view portals. In this presentation yo will learn services-based reference architecture, modality, and latency of data access.
- Reference architecture for enterprise data services marketplace
- Modality and latency of data access
- Customer use cases and demo
This presentation is part of the Denodo Educational Seminar , and you can watch the video here goo.gl/vycYmZ.
Modern Integrated Data Environment - Whitepaper | QuboleVasu S
A whit-paper is about building a modern data platform for data driven organisations with using cloud data warehouse with modern data platform architecture
https://www.qubole.com/resources/white-papers/modern-integrated-data-environment
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j
The document announces a GraphTalks event in Cologne in February 2017 hosted by Neo Technology. The agenda includes an introduction to graph databases and Neo4j, a presentation on semantic data management, and an open networking session. Complex topics like the internet of things, domain modeling, and traditional vs graph approaches to data modeling will also be discussed.
New Analytic Uses of Master Data Management in the EnterpriseDATAVERSITY
William McKnight discusses new analytic uses of master data management in the enterprise. He outlines how MDM can power applications like fraud detection, call center chatbots, transportation, and marketing. MDM provides a centralized hub for core and attribute data on customers, products, suppliers and other domains that can then be used across various analytics and applications. With quality master data and attributes, organizations can improve customer profiles for personalization, manage supply chains more efficiently, and detect fraud patterns in real-time.
The document describes DynMX, a software tool that uses shortest path analysis to optimize supply chain routes by minimizing distance and transportation costs. It analyzes route data through a 4-step process to produce results including an optimized route order, distance and duration tables, and a map displaying route details. The tool is designed to help supply chain managers address routing problems and can be used in combination with other DynMX apps for additional perspectives.
This document describes the DynMX Center of Gravity supply chain analysis tool. The tool calculates the center of gravity of current distribution locations and customers served based on factors like visit frequency, distance, sales value or transport costs. It is a 4-step process where the user inputs customer and weight data, selects the number of centers, analyzes the results which indicate the best locations for warehouses, and gets insights on warehouse location and customer assignment decisions. The tool helps optimize a supply chain network by supporting decisions around opening or closing warehouses and determining which customers to serve from each location.
This document provides an introduction and overview of big data technologies. It begins with defining big data and its key characteristics of volume, variety and velocity. It discusses how data has exploded in recent years and examples of large scale data sources. It then covers popular big data tools and technologies like Hadoop and MapReduce. The document discusses how to get started with big data and learning related skills. Finally, it provides examples of big data projects and discusses the objectives and benefits of working with big data.
Usama Fayyad talk at IIT Madras on March 27, 2015: BigData, AllData, Old Dat...Usama Fayyad
Title: BigData, AllData, Old Data: Predictive Analytics in a Changing Data Landscape
Abstract:
The landscape of the platform, access methodologies, shapes, and storage representations has changed dramatically. Much of the assumptions of a structured data world dominated by relational databases have been rendered obsolete. Today’s data analyst faces big challenges and a bewildering environment of technologies and challenges involving semi-structured and unstructured data with access methodologies that have almost no relation to the past. This talk will cover issues and challenges in how to make the benefits of advanced analytics fit within the application environment. The requirement for Real-time data streaming and in situ data mining is stronger than ever. We demonstrate how many of the critical problems remain open with much opportunity for innovative solutions to play a huge enabling role. This opportunity extends equally well to Knowledge Management and several related fields.
EMC World 2014 Breakout: Move to the Business Data Lake – Not as Hard as It S...Capgemini
Rip and replace isn't a good approach to IT change. When looking at Hadoop, MPP, in-memory and predictive analytics the challenge is making them co-exist with current solutions.
Learn how Capgemini’s Pivotal CoE utilizes Cloud Foundry and PivotalOne to help businesses adopt new technologies without losing the value of current investments.
Presented by Michael Wood of Pivotal and Steve Jones, Global Director, Strategy, Big Data and Analytics, Capgemini, at EMC World 2014.
Managing the Impact of COVID-19 Using Data VirtualizationDenodo
Watch here: https://bit.ly/2UUa7K1
To help alleviate the ramifications of COVID-19, Denodo launched the Coronavirus Data Portal (CDP), a collaborative initiative that leverages data virtualization to unify critical datasets originally exposed in different formats from multiple sources and countries, and make the unified data open to everyone.
Using the CDP and the data virtualization capabilities of the Denodo Platform, pmOne created detailed reports and AI analysis, seamlessly orchestrating all of the information streams in the pmOne Share Cockpit.
Working together, Denodo and pmOne provides the global community with trustworthy, up-to-date data about COVID-19 that can be used to develop new intelligence about COVID-19 and reduce its impact.
In this webinar, we will talk about how the CDP can accelerate your organization’s efforts to build solutions for fighting this terrible disease to save lives, the livelihood of workers, and our global economy.
ADV Slides: The Data Needed to Evolve an Enterprise Artificial Intelligence S...DATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenges today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve – for example, statistical modeling, machine learning, or deep learning – and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
Neo4j is a graph database designed for connected data and relationships. It is better suited than relational databases for data that is highly connected with complex relationships. Neo4j has many customers using it for applications that require real-time recommendations, routing, and master data management by leveraging the connected relationships in their data. Examples of customers highlighted include Walmart, eBay, Cisco, and a large logistics carrier.
ADV Slides: Trends in Streaming Analytics and Message-oriented MiddlewareDATAVERSITY
Streaming and real-time data has high business value, but that value can rapidly decay if not processed quickly. If the value of the data is not realized in a certain window of time, its value is lost and the decision or action that was needed as a result never occurs. Streaming data – whether from sensors, devices, applications, or events – needs special attention because a sudden price change, a critical threshold met, a sensor reading changing rapidly, or a blip in a log file can all be of immense value, but only if the alert is in time.
¿En qué se parece el Gobierno del Dato a un parque de atracciones?Denodo
Watch full webinar here: https://bit.ly/3Ab9gYq
Imagina llegar a un parque de atracciones con tu familia y comenzar tu día sin el típico plano que te permitirá planificarte para saber qué espectáculos ver, a qué atracciones ir, donde pueden o no pueden montar los niños… Posiblemente, no podrás sacar el máximo partido a tu día y te habrás perdido muchas cosas. Hay personas que les gusta ir a la aventura e ir descubriendo poco a poco, pero cuando hablamos de negocios, ir a la aventura puede ser fatídico...
En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de esa información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos.
La virtualización de datos, herramienta estratégica para implementar y optimizar el gobierno del dato, permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos.
En este webinar aprenderás a:
- Acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información.
- Activar en toda la empresa una sola capa de acceso a los datos con medidas de protección.
- Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.
Core banking Closure bank day OSWA meetup 2018-Alexander Petrov OsloAlexander Petrov
Core Banking platform. Alexander Petrov demonstrates architecture based on In memory data grid solving the problem of closing the bank day , month, year.
This document provides an introduction and overview of big data for an organization. It begins by outlining the topics that will be covered, including what big data means beyond Hadoop, the historical forces that led to big data, whether big data is just another buzzword, how Canadian companies compare to the world in adopting big data, a reference big data architecture, big data at BMO Financial Group, and the road ahead. It then discusses the origins and definitions of big data, assessing where Canada stands in adoption compared to global leaders. Finally, it outlines challenges organizations face in adopting big data strategies and capabilities.
GraphTalks Stuttgart - Einführung in Graphdatenbanken und Neo4jNeo4j
This document provides an agenda for the Neo4j GraphTalks event. The agenda includes:
- Breakfast and networking from 09:00-09:30.
- An introduction to graph databases and Neo4j from 09:30-10:00 by Bruno Ungermann from Neo4j.
- A presentation on semantic data management from 10:00-11:00 by Dr. Andreas Weber from semantic PDM.
- A presentation on how to make graph database projects successful from 11:00-11:30 by Stefan Kolmar from Neo4j.
- An open discussion from 11:30 onward moderated by Alexander Erdl from Neo4j
GraphTalks Hamburg - Einführung in GraphdatenbankenNeo4j
The document announces a GraphTalks event in Hamburg in March 2017 hosted by Neo Technology. It includes an agenda with sessions on graph databases and Neo4j, semantic data management, and an open networking session.
BAR360 open data platform presentation at DAMA, SydneySai Paravastu
Sai Paravastu discusses the benefits of using an open data platform (ODP) for enterprises. The ODP would provide a standardized core of open source Hadoop technologies like HDFS, YARN, and MapReduce. This would allow big data solution providers to build compatible solutions on a common platform, reducing costs and improving interoperability. The ODP would also simplify integration for customers and reduce fragmentation in the industry by coordinating development efforts.
Accelerate Digital Transformation with Data Virtualization in Banking, Financ...Denodo
Watch full webinar here: https://bit.ly/38uCCUB
Banking, Financial Services and Insurance (BFSI) organizations are globally accelerating their digital journey, making rapid strides with their digitization efforts, and adding key capabilities to adapt and innovate in the new normal.
Many companies find digital transformation challenging as they rely on established systems that are often not only poorly integrated, but also highly resistant to modernization without downtime. Hear how the BFSI industry is leveraging data virtualization that facilitates digital transformation via a modern data integration / data delivery approach to gain greater agility, flexibility, and efficiency.
In this joint live webinar session from Denodo and Wipro, you will learn:
- Industry key trends and challenges driving the digital transformation mandate and platform modernization initiatives
- Key concepts of Data Virtualization, and how it can enable BFSI customers to develop critical capabilities for real-time / near real-time data integration
- Success Stories on organizations who already use data virtualization to differentiate themselves from the competition
- Wipro’s role in helping enterprises define the business case, end-to-end services and operating model for the successful data virtualization implementations
Schedule a Discovery Session to learn more about Wipro and Denodo joint solutions for Banking, Financial Services, and Insurance.
The data services marketplace is enabled by a data abstraction layer that supports rapid development of operational applications and single data view portals. In this presentation yo will learn services-based reference architecture, modality, and latency of data access.
- Reference architecture for enterprise data services marketplace
- Modality and latency of data access
- Customer use cases and demo
This presentation is part of the Denodo Educational Seminar , and you can watch the video here goo.gl/vycYmZ.
Modern Integrated Data Environment - Whitepaper | QuboleVasu S
A whit-paper is about building a modern data platform for data driven organisations with using cloud data warehouse with modern data platform architecture
https://www.qubole.com/resources/white-papers/modern-integrated-data-environment
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j
The document announces a GraphTalks event in Cologne in February 2017 hosted by Neo Technology. The agenda includes an introduction to graph databases and Neo4j, a presentation on semantic data management, and an open networking session. Complex topics like the internet of things, domain modeling, and traditional vs graph approaches to data modeling will also be discussed.
New Analytic Uses of Master Data Management in the EnterpriseDATAVERSITY
William McKnight discusses new analytic uses of master data management in the enterprise. He outlines how MDM can power applications like fraud detection, call center chatbots, transportation, and marketing. MDM provides a centralized hub for core and attribute data on customers, products, suppliers and other domains that can then be used across various analytics and applications. With quality master data and attributes, organizations can improve customer profiles for personalization, manage supply chains more efficiently, and detect fraud patterns in real-time.
The document describes DynMX, a software tool that uses shortest path analysis to optimize supply chain routes by minimizing distance and transportation costs. It analyzes route data through a 4-step process to produce results including an optimized route order, distance and duration tables, and a map displaying route details. The tool is designed to help supply chain managers address routing problems and can be used in combination with other DynMX apps for additional perspectives.
This document describes the DynMX Center of Gravity supply chain analysis tool. The tool calculates the center of gravity of current distribution locations and customers served based on factors like visit frequency, distance, sales value or transport costs. It is a 4-step process where the user inputs customer and weight data, selects the number of centers, analyzes the results which indicate the best locations for warehouses, and gets insights on warehouse location and customer assignment decisions. The tool helps optimize a supply chain network by supporting decisions around opening or closing warehouses and determining which customers to serve from each location.
This document provides an introduction and overview of big data technologies. It begins with defining big data and its key characteristics of volume, variety and velocity. It discusses how data has exploded in recent years and examples of large scale data sources. It then covers popular big data tools and technologies like Hadoop and MapReduce. The document discusses how to get started with big data and learning related skills. Finally, it provides examples of big data projects and discusses the objectives and benefits of working with big data.
Usama Fayyad talk at IIT Madras on March 27, 2015: BigData, AllData, Old Dat...Usama Fayyad
Title: BigData, AllData, Old Data: Predictive Analytics in a Changing Data Landscape
Abstract:
The landscape of the platform, access methodologies, shapes, and storage representations has changed dramatically. Much of the assumptions of a structured data world dominated by relational databases have been rendered obsolete. Today’s data analyst faces big challenges and a bewildering environment of technologies and challenges involving semi-structured and unstructured data with access methodologies that have almost no relation to the past. This talk will cover issues and challenges in how to make the benefits of advanced analytics fit within the application environment. The requirement for Real-time data streaming and in situ data mining is stronger than ever. We demonstrate how many of the critical problems remain open with much opportunity for innovative solutions to play a huge enabling role. This opportunity extends equally well to Knowledge Management and several related fields.
EMC World 2014 Breakout: Move to the Business Data Lake – Not as Hard as It S...Capgemini
Rip and replace isn't a good approach to IT change. When looking at Hadoop, MPP, in-memory and predictive analytics the challenge is making them co-exist with current solutions.
Learn how Capgemini’s Pivotal CoE utilizes Cloud Foundry and PivotalOne to help businesses adopt new technologies without losing the value of current investments.
Presented by Michael Wood of Pivotal and Steve Jones, Global Director, Strategy, Big Data and Analytics, Capgemini, at EMC World 2014.
Managing the Impact of COVID-19 Using Data VirtualizationDenodo
Watch here: https://bit.ly/2UUa7K1
To help alleviate the ramifications of COVID-19, Denodo launched the Coronavirus Data Portal (CDP), a collaborative initiative that leverages data virtualization to unify critical datasets originally exposed in different formats from multiple sources and countries, and make the unified data open to everyone.
Using the CDP and the data virtualization capabilities of the Denodo Platform, pmOne created detailed reports and AI analysis, seamlessly orchestrating all of the information streams in the pmOne Share Cockpit.
Working together, Denodo and pmOne provides the global community with trustworthy, up-to-date data about COVID-19 that can be used to develop new intelligence about COVID-19 and reduce its impact.
In this webinar, we will talk about how the CDP can accelerate your organization’s efforts to build solutions for fighting this terrible disease to save lives, the livelihood of workers, and our global economy.
ADV Slides: The Data Needed to Evolve an Enterprise Artificial Intelligence S...DATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenges today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve – for example, statistical modeling, machine learning, or deep learning – and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
Neo4j is a graph database designed for connected data and relationships. It is better suited than relational databases for data that is highly connected with complex relationships. Neo4j has many customers using it for applications that require real-time recommendations, routing, and master data management by leveraging the connected relationships in their data. Examples of customers highlighted include Walmart, eBay, Cisco, and a large logistics carrier.
ADV Slides: Trends in Streaming Analytics and Message-oriented MiddlewareDATAVERSITY
Streaming and real-time data has high business value, but that value can rapidly decay if not processed quickly. If the value of the data is not realized in a certain window of time, its value is lost and the decision or action that was needed as a result never occurs. Streaming data – whether from sensors, devices, applications, or events – needs special attention because a sudden price change, a critical threshold met, a sensor reading changing rapidly, or a blip in a log file can all be of immense value, but only if the alert is in time.
¿En qué se parece el Gobierno del Dato a un parque de atracciones?Denodo
Watch full webinar here: https://bit.ly/3Ab9gYq
Imagina llegar a un parque de atracciones con tu familia y comenzar tu día sin el típico plano que te permitirá planificarte para saber qué espectáculos ver, a qué atracciones ir, donde pueden o no pueden montar los niños… Posiblemente, no podrás sacar el máximo partido a tu día y te habrás perdido muchas cosas. Hay personas que les gusta ir a la aventura e ir descubriendo poco a poco, pero cuando hablamos de negocios, ir a la aventura puede ser fatídico...
En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de esa información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos.
La virtualización de datos, herramienta estratégica para implementar y optimizar el gobierno del dato, permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos.
En este webinar aprenderás a:
- Acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información.
- Activar en toda la empresa una sola capa de acceso a los datos con medidas de protección.
- Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.
Core banking Closure bank day OSWA meetup 2018-Alexander Petrov OsloAlexander Petrov
Core Banking platform. Alexander Petrov demonstrates architecture based on In memory data grid solving the problem of closing the bank day , month, year.
This document provides an introduction and overview of big data for an organization. It begins by outlining the topics that will be covered, including what big data means beyond Hadoop, the historical forces that led to big data, whether big data is just another buzzword, how Canadian companies compare to the world in adopting big data, a reference big data architecture, big data at BMO Financial Group, and the road ahead. It then discusses the origins and definitions of big data, assessing where Canada stands in adoption compared to global leaders. Finally, it outlines challenges organizations face in adopting big data strategies and capabilities.
GraphTalks Stuttgart - Einführung in Graphdatenbanken und Neo4jNeo4j
This document provides an agenda for the Neo4j GraphTalks event. The agenda includes:
- Breakfast and networking from 09:00-09:30.
- An introduction to graph databases and Neo4j from 09:30-10:00 by Bruno Ungermann from Neo4j.
- A presentation on semantic data management from 10:00-11:00 by Dr. Andreas Weber from semantic PDM.
- A presentation on how to make graph database projects successful from 11:00-11:30 by Stefan Kolmar from Neo4j.
- An open discussion from 11:30 onward moderated by Alexander Erdl from Neo4j
GraphTalks Hamburg - Einführung in GraphdatenbankenNeo4j
The document announces a GraphTalks event in Hamburg in March 2017 hosted by Neo Technology. It includes an agenda with sessions on graph databases and Neo4j, semantic data management, and an open networking session.
Graphdatenbank Neo4j: Konzept, Positionierung, Status Region DACH - Bruno Un...Neo4j
This document provides an agenda for a Neo4j partner event. The agenda includes:
- Registration and networking from 9:30-10:00
- A presentation on the business potential of Neo4j for system integrators and consultants from 10:00-11:00
- A presentation on the Neo4j partner program from 11:00-11:15
- A break from 11:15-11:30
- A presentation using the example of the Panama Papers dataset to showcase the quick benefits of Neo4j from 11:30-12:30
- Lunch, networking and questions from 12:30 onward
This document contains the agenda for the Neo4j Partner Day event in Amsterdam on March 16th, 2017. The agenda includes sessions on the business potential for graph database partners, real-world Neo4j applications, an overview of the Neo4j partner program, and networking sessions.
Neo4j GraphTalks - Einführung in GraphdatenbankenNeo4j
Neo4j GraphTalks event on November 2016 included:
1) An introduction to graph databases and Neo4j by Bruno Ungermann from Neo4j.
2) Darko Krizic from PRODYNA AG presenting their experience implementing a global knowledge hub for product information using Neo4j.
3) An open networking session.
The document announces a Neo4j GraphTalks event in February 2016 focusing on semantic networks. The agenda includes an introduction to graph databases and Neo4j, a presentation on semantic product data management at Schleich, and a talk on building semantic networks quickly with Structr and Neo4j. An open discussion period will follow with additional speakers.
GraphTalk Berlin - Einführung in GraphdatenbankenNeo4j
The document describes an agenda for Neo4j GraphTalks in October 2015 in Germany. The agenda includes:
- Breakfast and networking from 09:00-09:30
- Introduction to graph databases and Neo4j from 09:30-10:00 by Bruno Ungermann from Neo4j
- Kantwert's experience using Neo4j for its first decision network in Germany from 10:00-10:30 by Tilo Walter
- e-Spirit's experience integrating Neo4j into its content management system from 10:30-11:00 by Christoph Feddersen
This document introduces Neo4j, a graph database developed by Neo Technology. It discusses how graph databases can model and query data relationships more easily than relational or NoSQL databases. The document provides an overview of Neo4j's history and growth, key features, examples of use cases, and how it helps customers like Adidas, Die Bayerische insurance, and SFR communications manage data relationships.
The document discusses MongoDB and data treatment. It covers how MongoDB can help with data integrity, confidentiality, correctness and reliability. It also discusses how MongoDB supports dynamic schemas, replication for high availability, security features and can be used as part of a modern enterprise technology stack including integration with Hadoop. MongoDB can be deployed on Azure as a fully managed service.
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
ADV Slides: What Happened of Note in 1H 2020 in Enterprise Advanced AnalyticsDATAVERSITY
Reassessing the information management marketplace for your enterprise direction on an annual basis is too infrequent. The technology is changing too fast. Data and analytic maturity levels rapidly evolve. What is advanced today may be entry-level in two years. Let’s look at the high points for 1H 2020 in information management developments and how that may change what you are doing now. This can also be a strong data point for preparing 2021 budgets.
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
- Big data refers to large volumes of data from various sources that is analyzed to reveal patterns, trends, and associations.
- The evolution of big data has seen it grow from just volume, velocity, and variety to also include veracity, variability, visualization, and value.
- Analyzing big data can provide hidden insights and competitive advantages for businesses by finding trends and patterns in large amounts of structured and unstructured data from multiple sources.
This document provides an overview and agenda for a presentation on product data management using Neo4j graph databases. The presentation will include an introduction to graph databases and Neo4j by Bruno Ungermann from Neo4j, followed by a discussion of using graph databases for product data management by Dr. Andreas Weber from semantic PDM. Examples will be provided of graph models and how they can be used for various domains including logistics, manufacturing, and customer relationships. Attendees will have an opportunity to ask questions and discuss use cases.
Data Mesh in Azure using Cloud Scale Analytics (WAF)Nathan Bijnens
This document discusses moving from a centralized data architecture to a distributed data mesh architecture. It describes how a data mesh shifts data management responsibilities to individual business domains, with each domain acting as both a provider and consumer of data products. Key aspects of the data mesh approach discussed include domain-driven design, domain zones to organize domains, treating data as products, and using this approach to enable analytics at enterprise scale on platforms like Azure.
This document discusses big data analytics reference architectures and case studies. It begins with an overview of relational vs non-relational architectures and describes challenges of big data like volume, variety and velocity of data. It then covers traditional vs big data analytics, use cases, reference architectures including relational, non-relational and hybrid models. Finally, it shares two case studies on usage analysis and clickstream analysis along with architectural decisions and solutions implemented.
3 Reasons Data Virtualization Matters in Your PortfolioDenodo
Watch the full session on-demand here: https://goo.gl/upxC5W
Real-Time Analytics for Big Data, Cloud & Self-Service BI
The world of data is only becoming distributed. Privacy, regulations, and the need for real-time decisions are challenging organizations’ legacy information strategy. This webinar will include an expert panel discussion on Logical Data Warehouse, Universal Semantic Layer, and Real-time Analytics by Paul Moxon (VP of Data Architectures), Pablo Alvarez (Director of Product Management), and Alberto Pan (CTO).
Attend and learn:
• The major challenges of legacy information strategies.
• How data virtualization can help you overcome these challenges.
• Strategies for enabling agile data management and analytics.
GraphTalk Frankfurt - Einführung in GraphdatenbankenNeo4j
This document provides an agenda for the Neo4j GraphTalks event in June 2015. The agenda includes: breakfast and networking, an introduction to graph databases and Neo4j, a presentation on digital asset management at Lufthansa, a presentation on master data management at Bayerische Versicherung, and an open discussion period. The document also includes examples of using Neo4j for applications such as logistics processing, recommendations, and network management.
Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4jNeo4j
The document outlines an agenda for the Neo4j Graph Tour in New York that included discussions on graph databases, data management trends, case studies, and the future of graphs. It also provided examples of how various organizations like Caterpillar, Comcast, and the German Center for Diabetes Research are using Neo4j graph databases for applications like equipment maintenance, smart home services, and medical genomic research.
Accelerate Cloud Migrations and Architecture with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3N46zxX
Cloud migration brings scalability and flexibility, and often reduced cost to organizations. But even after moving to the cloud, more often than not, organizational data can be found to be siloed, hard to access and lacking centralized governance. That leads to delay and often missed opportunities in value creation from enterprise data. Join Amit Mody, Senior Manager at Accenture, in this keynote session to learn why current physical data architectures are hindrance to value creation from data, what is a logical data fabric powered by data virtualization and how a logical data fabric can unlock the value creation potential for enterprises.
Similar to Neo4j GraphTalks - Einführung in Graphdatenbanken (20)
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...Neo4j
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesNeo4j
David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
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Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
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During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
2. Neo4j GraphTalks
• 09:00-09:30 Frühstück und Networking
• 09:30-10:00 Einführung in Graph-Datenbanken und Neo4j
(Bruno Ungermann, Neo Technology)
• 10:00-11:00 Visualisierung von Big Data Sets der Pharmaindustrie mittels
Graphdatenbanken
(Dr. Steffen Tomschke, Team-Lead und UX-Consultant, B-S-S Business Software Solutions GmbH )
• Open End (Dirk Möller, Alexander Erdl)
10. “We found Neo4j to be literally thousands of times faster
than our prior MySQL solution, with queries that require
10-100 times less code. Today, Neo4j provides eBay with
functionality that was previously impossible.”
- Volker Pacher, Senior Developer
“Minutes to milliseconds” performance
Queries up to 1000x faster than other tested database types
Speed
11. Discrete Data
Minimally
connected data
Neo4j is designed for data relationships
Other NoSQL Relational DBMS Neo4j Graph DB
Connected Data
Focused on
Data Relationships
Development Benefits
Easy model maintenance
Easy query
Deployment Benefits
Ultra high performance
Minimal resource usage
Use the Right Database for the Right Job
12. 2000 2003 2007 2009 2011 2013 2014 20152012
GraphConnect,
first conference for
graph DBs
First
Global 2000
Customer
Introduced
first and only
declarative query
language for
property graph
Published
O’Reilly
book
on Graph
Databases
First
native
graph DB
in 24/7
production
Invented
property
graph
model
Contributed
first graph DB
to open
source
Extended
graph data
model to
labeled
property
graph
150-200+ customers
50-60K+ monthly
downloads
500-600 graph
DB events
worldwide
Neo4j: The Graph Database Leader
2016 2017 and beyond
OpenCypher
Industry partnerships
Neo4j 3.X
250+ customers
65K+ monthly
downloads
Partner focus
15. “Forrester estimates that over 25% of enterprises will be using graph
databases by 2017”
“Neo4j is the current market leader in graph databases.”
“Graph analysis is possibly the single most effective competitive
differentiator for organizations pursuing data-driven operations and
decisions after the design of data capture.”
IT Market Clock for Database Management Systems, 2014
https://www.gartner.com/doc/2852717/it-market-clock-database-management
TechRadar™: Enterprise DBMS, Q1 2014
http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801
Graph Databases – and Their Potential to Transform How We Capture Interdependencies (Enterprise Management Associates)
http://blogs.enterprisemanagement.com/dennisdrogseth/2013/11/06/graph-databasesand-potential-transform-capture-interdependencies/
Neo4j Leads the Graph Database Revolution
20. Adidas Shared Meta Data Service
20 Knowledge Management
Background
• Global leader in sporting goods industry services
firm footware, apparel, hardware, 14.5 bln sales,
53,000 people
• Multitude of products, markets, media, assets and
audiences
Business Problem
• Beset by a wide array of information silos including
data about products, markets, social media, master
data, digital assets, brand content and more
• Provide the most compelling and relevant content to
consumers
• Offering enhanced recommendations to drive
revenue
Solution and Benefits
• Save time and cost through stadardized access to
content sharing-system with internal teams, partners,
IT units, fast, reliable, searchable avoiding
reduandancy
• Inprove customer experience and increase revenue by
providing relevant content and recommentations
21. Background
• San Jose-based communications equipment giant
ranks #91 in the Global 2000 with $44B in annual
sales
• Needed high-performance system that could
provide master-data access services 24x7 to
applications company-wide
Solution and Benefits
• New Hierarchy Management Platform (HMP)
manages master data, rules and access
• Cut access times from minutes to milliseconds
• Graphs provided flexibility for business rules
• Expanded master-data services to include product
hierarchies
Business Problem
• Sales compensation system didn’t meet needs
• Oracle RAC system had reached its limits
• Inflexible handling of complex organizational
hierarchies and mappings
• ”Real-time” queries ran for more than a minute
• P1 system must have zero downtime
Cisco COMMUNICATIONS
Master Data Management21
22. Background
• Mid-size German insurer founded in 1858
• Project executed by Delvin, a subsidiary
of die Bayerische Versicherung and an IT insurance
specialist
Business Problem
• Field sales needed easy, dynamic, 24/7 access to
policies and customer data
• Existing DB2 system unable to meet performance
and scaling demands
Solution and Benefits
• Enabled flexible searching of policies and associated
personal data
• Raised the bar on industry practices
• Delivered high performance and scalability
• Ported existing metadata easily
Die Bayerische Versicherung INSURANCE
Knowledge Management22
23. Background
• Large global bank
• Deploying Reference Data to users and systems
• 12 data domains, 18 datasets, 400+ integrations
• Complex data management infrastructure
Business Problem
• Master data silos were inflexible and hard to
consume
• Needed simplification to reduce redundancy
• Reduce risk when data is in consumers’ hands
• Dramatically improve efficiency
Solution and Benefits
• Data distribution flows improved dramatically
• Knowledge Base improves consumer access
• Ad-hoc analytics improved
• Governance, lineage and trust improved
• Better service level from IT to data consumers
UBS FINANCIAL SERVICES
Master Data Management / Metadata23
CE Customer since 2
24. Background
• 5 year long drug discovery research
• Parse & Navigate over 25 Million scientific papers
• Sourcedfrom National Library of Research and tagging
of “Medical Subject Headers” (MeSH tags)
Business Problem
• Seeking to automate phenotype, compound and
protein cell behavior research by using previously
documented research more effectively
• Text mining for research elements like DNA strings,
proteins, RNA, chemicals and diseases
Solution and Benefits
• Found ways to identify compound interaction
behavior from millions of research documents
• Relations between biological entities can be
identified and validated by biologic experts
• Still very challenging to keep up-to-date, add
genomics data, and find a breakthrough
Novartis PHARMACEUTICAL RESEARCH
Content Management / Biomedical Research24
25. Background
• SF-based C2C rental platform
• Dataportal democratizes data access for
growing number of employees while improving
discoverability and trust
• Data strewn everywhere—in silos, in segmented
departments, nothing was universally accessible
Business Problem
• Data-driven culture hampered by variety and
dependability of data, tribal knowledge and word-of-
mouth distribution
• Needed visibility into information usage, context,
lineage and popularity across company of 3,000+
Solution and Benefits
• Offers search with context & metadata, user & team-
centric pages for origin & lineage
• Nodes are resources: data tables, dashboards,
reports, users, teams, business outcomes, etc.
• Relationships reflect consumption, production,
association, etc.
• Neo4j, Elasticsearch, Python
Airbnb Dataportal TRAVEL TECHNOLOGY
Knowledge Graph, Metadata Management25
30. Business Problem
• Optimize walmart.com user experience
• Connect complex buyer and product data to gain
super-fast insight into customer needs and product
trends
• RDBMS couldn’t handle complex queries
Solution and Benefits
• Replaced complex batch process real-time online
recommendations
• Built simple, real-time recommendation system with
low-latency queries
• Serve better and faster recommendations by
combining historical and session data
Background
• Founded in 1962 and based in Arkansas
• 11,000+ stores in 27 countries with walmart.com
online store
• 2M+ employees and $470 billion in annual
revenues
Walmart RETAIL
Real-Time Recommendations30
31. Background
• One of the world’s largest logistics carriers
• Projected to outgrow capacity of old system
• New parcel routing system
Single source of truth for entire network
B2C and B2B parcel tracking
Real-time routing: up to 7M parcels per day
Business Problem
• Needed 365x24x7 availability
• Peak loads of 3000+ parcels per second
• Complex and diverse software stack
• Need predictable performance, linear scalability
• Daily changes to logistics network: route from any
point to any point
Solution and Benefits
• Ideal domain fit: a logistics network is a graph
• Extreme availability, performance via clustering
• Greatly simplified routing queries vs. relational
• Flexible data model reflect real-world data variance
much better than relational
• Whiteboard-friendly model easy to understand
Accenture LOGISTICS
31 Real-Time Routing Recommendations
32. Business Problem
• Provide the right room & price at the right time
• Extremly complex individual pricing calculations
• Moved from per month to per day calculation
• Former system too slow, too inflexible
Solution and Benefits
• Huge performance increase through replacement of legacy
system
• 4 Core Laptop, 6% CPU usage provides better performance
than 3 server 96 Core config with 80% CPU usage „mind-
blowing“, 50 decrease infrastructure costs
• Overcame internal hurdles by using embedded, application
internal cache vs new database system
Background
• World‘s largest hospitality / hotel company
• 1.5 M hotel rooms offered online by 2018
• 15 Bln eCommerce Sales 2015, #7 IDC rating
internet sales
Marriott Hospitality
Real-Time Recommendations32
33. Background
• San Jose-based communications equipment giant
ranks #91 in the Global 2000 with $44B in annual
sales
• Needed real-time recommendations to encourage
knowledge base use on company’s support portal
Solution and Benefits
• Faster problem resolution for customers and
decreased reliance on support teams
• Scrape cases, solutions, articles et al continuously for
cross-reference links
• Provide real-time reading recommendations
• Uses Neo4j Enterprise HA cluster
Business Problem
• Reduce call-center volumes and costs via improved
online self-service quality
• Leverage large amounts of knowledge stored in
service cases, solutions, articles, forums, etc.
• Reduce resolution times and support costs
Cisco COMMUNICATIONS
Real-Time Recommendations
Solution
Support
Case
Support
Case
Knowledge
Base Article
Message
Knowledge
Base Article
Knowledge
Base Article
33
36. Background
• Second largest communications company
in France
• Based in Paris, part of Vivendi Group, partnering
with Vodafone
Solution and Benefits
• Flexible inventory management supports modeling,
aggregation, troubleshooting
• Single source of truth for entire network
• New apps model network via near-1:1 mapping
between graph and real world
• Schema adapts to changing needs
Network and IT Operations
SFR COMMUNICATIONS
Business Problem
• Infrastructure maintenance took week to plan due
to need to model network impacts
• Needed what-if to model unplanned outages
• Identify network weaknesses to uncover need for
additional redundancy
• Info lived on 30+ systems, with daily changes
LINKED
LINKED
DEPENDS_ON
Router Service
Switch Switch
Router
Fiber Link Fiber Link
Fiber Link
Oceanfloor
Cable
36
37. Business Problem
• Original RDBMS solution could handle only 5,000
servers
• Improve net performance company-wide
• Leverage M&A legacy systems with no room
for error
Solution and Benefits
• Store UNIX server and network config in Neo4j
• Combine Splunk log data into an application
that visualizes events on the network
• Neo4j vastly improved app performance
• New apps built much faster with Neo4j than SQL
Large Investment Bank FINANCIAL SERVICES
Network and IT Operations37
Background
• One of the world’s oldest and largest banks
• 100+ year-old bank with more than 1000
predecessor institutions
• 500,000 employees and contractors
• Needed to manage and visualize ~50,000 Unix
servers in its network
38. Background
• World’s largest provider of IT infrastructure,
software and services
• Unified Correlation Analyzer (UCA) helps comms
operators manage large networks
with carrier-class resource and service
management, root cause and impact analysis
Business Problem
• Use network topology to identify root problems
causes on the network
• Simplify and speed alarm handling by operators
• Automate handling of certain types of alarms
• Filter/group/eliminate redundant alarms via event
correlation
Solution and Benefits
• Accelerated product development time
• Extremely fast network-topology queries
• Graph representation a perfect domain fit
• 24x7 carrier-grade reliability with Neo4j
High Availability clustering
• Met objective in under six months
Hewlett Packard WEB/ISV COMMUNICATIONS
Network and IT Operations38
39. Identity Relationship ManagementIdentity Access Management
Applications
and data
Endpoints
People
Customers
(millions)
Partners and
Suppliers
Workforce
(thousands)
PCs Tablets
On-premises Private Cloud Public Cloud
Things
(Tens of
millions)
WearablesPhones
PCs
Customers
(millions)
On-premises
Applications
and data
Endpoints
People
40. Background
• Oslo-based telcom provider is #1 in Nordic
countries and #10 in world
• Online, mission-critical, self-serve system lets
users manage subscriptions and plans
• availability and responsiveness is critical to
customer satisfaction
Business Problem
• Logins took minutes to retrieve relational
access rights
• Massive joins across millions of plans,
customers, admins, groups
• Nightly batch production required 9 hours and
produced stale data
Solution and Benefits
• Shifted authentication from Sybase to Neo4j
• Moved resource graph to Neo4j
• Replaced batch process with real-time login response
measured in milliseconds that delivers real-time data,
vw yday’s snapshot
• Mitigated customer retention risks
Identity and Access Management
Telenor COMMUNICATIONS
SUBSCRIBED_BY
CONTROLLED_BY
PART_O
F
USER_ACCESS
Account
Customer
CustomerUser
Subscription
40
41. Background
• Top investment bank with $1+ trillion in assets
• Using a relational database and Gemfire to manage
employee permissions to research document and
application-service resources
• Permissions for new investment managers and
traders provisioned manually
Business Problem
• Lost an average of 5 days per new hire while they
waited to be granted access to hundreds of
resources, each with its own permissions
• Replace an unsuccessful onboarding process
implemented by a competitor
• Regulations left no room for error
Solution and Benefits
• Store models, groups and entitlements in Neo4j
• Exceeded performance requirements
• Major productivity advantage due to domain fit
• Graph visualization ease permissioning process
• Fewer compromises than with relational
• Expanded Neo4j solution to online brokerage
UBS FINANCIAL SERVICES
Identity and Access Management41
43. Revolving Debt
Number of Accounts
Normal behavior
Fraud Detection With Connected Analysis
Fraudulent pattern
44. Background
• Global financial services firm with trillions of dollars
in assets
• Varying compliance and governance
considerations
• Incredibly complex transaction systems, with ever-
growing opportunities for fraud
Business Problem
• Needed to spot and prevent fraud detection in real
time, especially in payments that fall within “normal”
behavior metrics
• Needed more accurate and faster credit risk analysis
for payment transactions
• Needed to dramatically reduce chargebacks
Solution and Benefits
• Lowered TCO by simplifying credit risk analysis and
fraud detection processes
• Identify entities and connections uniquely
• Saved billions by reducing chargebacks and fraud
• Enabled building real-time apps with non-uniform data
and no sparse tables or schema changes
London and New York Financial FINANCIAL SERVICES
Fraud Detection
s
44
45. Background
• Panama based lawyers Mossack & Fonseca do
business in hosting “letterbox companies”
• Suspected to support tax saving and organized
crime
• Altogether: 2.6 TB, 11 milo files, 214.000 letter box
companies
Business Problem
• Goal to unravel chains Bank-Person–Client–
Address–Intermediaries – M&F
• Earlier cases: spreadsheet based analysis (back-
and-forth) & pencil to extract such connections
• This case: sheer amount of data & arbitrarily chain
length condemn such approaches to fail
Solution and Benefits
• 400 journalists, investigate/update/share, 2 people
with IT background
• Identify connections quickly and easily
• Fast Results wouldn‘t be possible without GraphDB
Panama Papers Fraud Detection
Fraud Detection45
More concrete and closer to reality
Flexible
, no Fixed Schema
And deriving value from data-relationships is exactly what some of the most successful companies in the world have done.
Google created perhaps the most valuable advertising system of all time on top of their search-enginge, which is based on relationships between webpages.
Linkedin created perhaps the most valuable HR-tool ever based on relationships amongst professional
And this is also what pay-pal did, creating a peer-to-peer transaction service, based on relationships.
When it comes to shopping online, probably the most important feature is the product recommendations you make, because they will have a direct impact on your sales.
Off course, we all know Amazon has set the standard for how online-recommendations work. In this example we see a user who’s looking to buy a “Kitchen Aid”. And normally you would see recommendations based on “Related Products” or something like “People who bought product X also bought product Y”.
This would be a classical retail recommendation. This is also very easy to model with a graph.
The question here is though, if this is a limited way of looking at recommendations? – because you risk leaving out a lot of information about your user that actually affects what a good recommendation is.
…Smart TV’s.
The important thing to remember is, the more you know about your consumer, the more relevant your recommendations will be, the better the chance is that you’ll actually be able to make a sale. And this is a numbers game – and once you start doing this on scale…
When we say that networks are graphs, we mean that networks by default are entities that are connected. If you do a quick search on “network topology” you basically end up with a display of a bunch of graphs…
And if we zoom in on one of them, which seems to be a mesh network of some sort, with routers, gateways — this would be very easy to translate and model into a graph in Neo4j.
OSS = Operations Support Systems. Systems used by telecommunications service providers to administer and maintain network systems.
So let’s see what’s happening in the the world of IAM.
Access Management used to be pretty straight forward. And the IAM-processes used to represent a pretty simplistic world of what access meant. People accessed applications hosted on-premiss, through specific devices. And in a scenario like this one, access management isn’t really that complicated.
Today, this is simply not a reality. As we discussed previously, 1) people take on several different roles, 2) and (even if you don’t think about it) they will be connected and require secure access to millions of things, they will use different types of devices with different types of dependencies, 3) and all of these individuals and roles will expect to access and use services and applications in a very granular and personalized way.
So all of this is, of course, highly interconnected.
And all these relationships have tremendous value. and your IAM-processes has an enormously important role to play, and from many different perspectives.
…And I think this picture show you that what’s emerging are the incredibly rich data-relationships between people and things, and the different personas of people and things, and the job of IAM is going to be to use these relationships to manage who gets access to what — whether it is about accessing data coming from an IOT device or whether it’s about access to control devices remotely, or whether a device should have access to a cloud API or whether a person could share information with another person, etc… In all these different scenarios you can provide a richer experience by leveraging these relationships between all these people and things and be able to play out these different scenarios and ask those questions in real-time.
This is what the world looks like, and it’s scaling rapidly. We’re going to reach an environment where we’ll see connected devices and people by the billions, so just imagine how many data-relationships that have to be in place to make sense of all this, knowing that when devices are being connected, if they’re not properly secured, it’s a huge risk from a privacy and cyber security point of view.
So data-relationships are going to be a key part of the future when we build IAM-systems and when managing digital identity.
And, an enterprise who doesn’t appreciate and understand the full complexity of who the customers are in an environment like this, will probably start faltering quite quickly.
So it’s very exciting times for IAM, and especially for graph databases within IAM. I think how we securely manage these billions of relationships between users and things, and collaborators, employees, customers and consumers is going to be one of the epic undertakings of the future.
[In this simple fraud detection approach to detect credit card fraud, it is relatively easy to spot outliers. But what if the fraudster commits fraud while still exhibiting normal behavior. Well - this is exactly how fraud rings operate]
[A fraud ring rarely strays outside the normal behavior band. Instead they operate within normal limits and commit widespread fraud. This is very hard to detect by systems that are looking for outliers or activities outside the normal band.]
When we say that networks are graphs, we mean that networks by default are entities that are connected. If you do a quick search on “network topology” you basically end up with a display of a bunch of graphs…