Presentation done at WWW 2009 Conference in Madrid, Spain introducing our work in using Linked Open Data as a way to add semantic descriptors to those coming from low-level signal analysis.
Data Mining using NLP with R programming. Used to mine data from dataset like removing numbers, punctuations, extra words, English words, stemming worlds and also creating a word cloud
This slides I've used on talk about Semantic Web use-case. Not all know what exactly Semantic Web is about. So I've created set of slides showing this in a simple and correct way. Use-case slides are removed on this public available slides. Animated version here goo.gl/qKoF6k . Contact me for sources!
Data Mining using NLP with R programming. Used to mine data from dataset like removing numbers, punctuations, extra words, English words, stemming worlds and also creating a word cloud
This slides I've used on talk about Semantic Web use-case. Not all know what exactly Semantic Web is about. So I've created set of slides showing this in a simple and correct way. Use-case slides are removed on this public available slides. Animated version here goo.gl/qKoF6k . Contact me for sources!
Querying GrAF data in linguistic analysisPeter Bouda
The “Graph Annotation Framework” (GrAF) defines an API and an XML format to store and query linguistic annotations as annotation graphs. The format was standardized as ISO 24612 in 20121, and was explicitly developed as an underlying data model for linguistic annotations in a radical stand-off approach2 ([Ide and Suderman 2007]). The basic data structures are annotation graphs as proposed in [Bird and Liberman 2001], and are general and expressive enough to encode all known varieties of annotation in linguistics and other “annotation-based” disciplines. Although GrAF is not a TEI-compatible format, both standards share a certain technological foundation and grew in a similar ecosystem, but with slightly different applications in mind. In our talk we will show the connections between TEI and GrAF, propose an option to convert between the „two worlds“, and demonstrate a query system for GrAF data that we already use in typological analysis of annotated data from language documentation projects.
The presentation was given by Mr. Bas Kempen, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
Observability for Data Pipelines With OpenLineageDatabricks
Data is increasingly becoming core to many products. Whether to provide recommendations for users, getting insights on how they use the product, or using machine learning to improve the experience. This creates a critical need for reliable data operations and understanding how data is flowing through our systems. Data pipelines must be auditable, reliable, and run on time. This proves particularly difficult in a constantly changing, fast-paced environment.
Collecting this lineage metadata as data pipelines are running provides an understanding of dependencies between many teams consuming and producing data and how constant changes impact them. It is the underlying foundation that enables the many use cases related to data operations. The OpenLineage project is an API standardizing this metadata across the ecosystem, reducing complexity and duplicate work in collecting lineage information. It enables many projects, consumers of lineage in the ecosystem whether they focus on operations, governance or security.
Marquez is an open source project part of the LF AI & Data foundation which instruments data pipelines to collect lineage and metadata and enable those use cases. It implements the OpenLineage API and provides context by making visible dependencies across organizations and technologies as they change over time.
Paper presented at the 12th International Conference on Digital Preservation, November 2-6, 2015. University of North Carolina at Chapel Hill.
Abstract:
Memory institutions have already collected a large number of digital objects, predominantly CD-ROMs. Some of them are already inaccessible with current systems, and most of them will be soon. Emulation offers a viable strategy for long-term access to these publications. However, these collections are huge and the objects are missing technical metadata to setup a suitable emulated environment. In this paper we propose a pragmatic approach to technical metadata which we use to implement a characterization tool to suggest a suitable emulated rendering environment.
A preponderance of data from NASA's Earth Observing System (EOS) is archived in the HDF Version 4 (HDF4) format. The long-term preservation of these data is critical for climate and other scientific studies going many decades into the future. HDF4 is very effective for working with the large and complex collection of EOS data products. Unfortunately, because of the complex internal byte layout of HDF4 files, future readability of HDF4 data depends on preserving a complex software library that can interpret that layout. Having a way to access HDF4 data independent of a library could improve its viability as an archive format, and consequently give confidence that HDF4 data will be readily accessible forever, even if the HDF4 library is gone.
To address the need to simplify long-term access to EOS data stored in HDF4, a collaborative project between The HDF Group and NASA Earth Science Data Centers is implementing an approach to accessing data in HDF4 files based on the use of independent maps that describe the data in HDF4 files and tools that can use these maps to recover data from those files. With this approach, relatively simple programs will be able to extract the data from an HDF4 file, bypassing the need for the HDF4 library.
A demonstration project has shown that this approach is feasible. This involved an assessment of NASA�s HDF4 data holdings, and development of a prototype XML-based layout mapping language and tools to read layout maps and read HDF4 files using layout maps. Future plans call for a second phase of the project, in which the mapping tools and XML schema are made production quality, the mapping schema are integrated with existing XML metadata files in several data centers, and outreach activities are carried out to encourage and facilitate acceptance of the technology.
Paper presented at the 12th International Conference on Digital Preservation, November 2-6, 2015. University of North Carolina at Chapel Hill.
Abstract:
In this paper, we describe an OAIS aligned data model and architectural design that enables us to archive digital information with a single core preservation workflow. The data model allows for normalization of metadata from widely varied domains to ingest and manage the submitted information utilizing only one generalized toolchain and be able to create access platforms that are tailored to designated data consumer communities. The design of the preservation system is not dependent on its components to continue to exist over its lifetime, as we anticipate changes both of technology and environment. The initial implementation depends mainly on the open-source tools Archivematica, Fedora/Islandora, and iRODS.
This short text will get you up to speed in no time on creating visualizations using R's ggplot2 package. It was developed as part of a training to those who had no prior experience in R and had limited knowledge on general programming concepts. It's a must have initial guide for those exploring the field of Data Science
Adbms 22 dynamic multi level index using b and b+ treeVaibhav Khanna
A single-level index is an auxiliary file that makes it more efficient to search for a record in the data file.
The index is usually specified on one field of the file (although it could be specified on several fields)
One form of an index is a file of entries <field value, pointer to record>, which is ordered by field value
The index is called an access path on the field
Querying GrAF data in linguistic analysisPeter Bouda
The “Graph Annotation Framework” (GrAF) defines an API and an XML format to store and query linguistic annotations as annotation graphs. The format was standardized as ISO 24612 in 20121, and was explicitly developed as an underlying data model for linguistic annotations in a radical stand-off approach2 ([Ide and Suderman 2007]). The basic data structures are annotation graphs as proposed in [Bird and Liberman 2001], and are general and expressive enough to encode all known varieties of annotation in linguistics and other “annotation-based” disciplines. Although GrAF is not a TEI-compatible format, both standards share a certain technological foundation and grew in a similar ecosystem, but with slightly different applications in mind. In our talk we will show the connections between TEI and GrAF, propose an option to convert between the „two worlds“, and demonstrate a query system for GrAF data that we already use in typological analysis of annotated data from language documentation projects.
The presentation was given by Mr. Bas Kempen, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
Observability for Data Pipelines With OpenLineageDatabricks
Data is increasingly becoming core to many products. Whether to provide recommendations for users, getting insights on how they use the product, or using machine learning to improve the experience. This creates a critical need for reliable data operations and understanding how data is flowing through our systems. Data pipelines must be auditable, reliable, and run on time. This proves particularly difficult in a constantly changing, fast-paced environment.
Collecting this lineage metadata as data pipelines are running provides an understanding of dependencies between many teams consuming and producing data and how constant changes impact them. It is the underlying foundation that enables the many use cases related to data operations. The OpenLineage project is an API standardizing this metadata across the ecosystem, reducing complexity and duplicate work in collecting lineage information. It enables many projects, consumers of lineage in the ecosystem whether they focus on operations, governance or security.
Marquez is an open source project part of the LF AI & Data foundation which instruments data pipelines to collect lineage and metadata and enable those use cases. It implements the OpenLineage API and provides context by making visible dependencies across organizations and technologies as they change over time.
Paper presented at the 12th International Conference on Digital Preservation, November 2-6, 2015. University of North Carolina at Chapel Hill.
Abstract:
Memory institutions have already collected a large number of digital objects, predominantly CD-ROMs. Some of them are already inaccessible with current systems, and most of them will be soon. Emulation offers a viable strategy for long-term access to these publications. However, these collections are huge and the objects are missing technical metadata to setup a suitable emulated environment. In this paper we propose a pragmatic approach to technical metadata which we use to implement a characterization tool to suggest a suitable emulated rendering environment.
A preponderance of data from NASA's Earth Observing System (EOS) is archived in the HDF Version 4 (HDF4) format. The long-term preservation of these data is critical for climate and other scientific studies going many decades into the future. HDF4 is very effective for working with the large and complex collection of EOS data products. Unfortunately, because of the complex internal byte layout of HDF4 files, future readability of HDF4 data depends on preserving a complex software library that can interpret that layout. Having a way to access HDF4 data independent of a library could improve its viability as an archive format, and consequently give confidence that HDF4 data will be readily accessible forever, even if the HDF4 library is gone.
To address the need to simplify long-term access to EOS data stored in HDF4, a collaborative project between The HDF Group and NASA Earth Science Data Centers is implementing an approach to accessing data in HDF4 files based on the use of independent maps that describe the data in HDF4 files and tools that can use these maps to recover data from those files. With this approach, relatively simple programs will be able to extract the data from an HDF4 file, bypassing the need for the HDF4 library.
A demonstration project has shown that this approach is feasible. This involved an assessment of NASA�s HDF4 data holdings, and development of a prototype XML-based layout mapping language and tools to read layout maps and read HDF4 files using layout maps. Future plans call for a second phase of the project, in which the mapping tools and XML schema are made production quality, the mapping schema are integrated with existing XML metadata files in several data centers, and outreach activities are carried out to encourage and facilitate acceptance of the technology.
Paper presented at the 12th International Conference on Digital Preservation, November 2-6, 2015. University of North Carolina at Chapel Hill.
Abstract:
In this paper, we describe an OAIS aligned data model and architectural design that enables us to archive digital information with a single core preservation workflow. The data model allows for normalization of metadata from widely varied domains to ingest and manage the submitted information utilizing only one generalized toolchain and be able to create access platforms that are tailored to designated data consumer communities. The design of the preservation system is not dependent on its components to continue to exist over its lifetime, as we anticipate changes both of technology and environment. The initial implementation depends mainly on the open-source tools Archivematica, Fedora/Islandora, and iRODS.
This short text will get you up to speed in no time on creating visualizations using R's ggplot2 package. It was developed as part of a training to those who had no prior experience in R and had limited knowledge on general programming concepts. It's a must have initial guide for those exploring the field of Data Science
Adbms 22 dynamic multi level index using b and b+ treeVaibhav Khanna
A single-level index is an auxiliary file that makes it more efficient to search for a record in the data file.
The index is usually specified on one field of the file (although it could be specified on several fields)
One form of an index is a file of entries <field value, pointer to record>, which is ordered by field value
The index is called an access path on the field
Present and future of unified, portable and efficient data processing with Ap...DataWorks Summit
The world of big data involves an ever-changing field of players. Much as SQL stands as a lingua franca for declarative data analysis, Apache Beam aims to provide a portable standard for expressing robust, out-of-order data processing pipelines in a variety of languages across a variety of platforms. In a way, Apache Beam is a glue that can connect the big data ecosystem together; it enables users to "run any data processing pipeline anywhere."
This talk will briefly cover the capabilities of the Beam model for data processing and discuss its architecture, including the portability model. We’ll focus on the present state of the community and the current status of the Beam ecosystem. We’ll cover the state of the art in data processing and discuss where Beam is going next, including completion of the portability framework and the Streaming SQL. Finally, we’ll discuss areas of improvement and how anybody can join us on the path of creating the glue that interconnects the big data ecosystem.
Speaker
Davor Bonaci, V.P. of Apache Beam; Founder/CEO at Operiant
Realizing the promise of portable data processing with Apache BeamDataWorks Summit
The world of big data involves an ever changing field of players. Much as SQL stands as a lingua franca for declarative data analysis, Apache Beam aims to provide a portable standard for expressing robust, out-of-order data processing pipelines in a variety of languages across a variety of platforms. In a way, Apache Beam is a glue that can connect the Big Data ecosystem together; it enables users to "run-anything-anywhere".
This talk will briefly cover the capabilities of the Beam model for data processing, as well as the current state of the Beam ecosystem. We'll discuss Beam architecture and dive into the portability layer. We'll offer a technical analysis of the Beam's powerful primitive operations that enable true and reliable portability across diverse environments. Finally, we'll demonstrate a complex pipeline running on multiple runners in multiple deployment scenarios (e.g. Apache Spark on Amazon Web Services, Apache Flink on Google Cloud, Apache Apex on-premise), and give a glimpse at some of the challenges Beam aims to address in the future.
Source-to-source transformations: Supporting tools and infrastructurekaveirious
Introduction to source-to-source transformation. Concept and overview. Basics of existing tools (TXL, ROSE, Cetus, EDG, C-to-C, Memphis); pros and cons. Part of an internal evaluation for selecting a source-to-source transformation tool.
Eclipse Con Europe 2014 How to use DAWN Science ProjectMatthew Gerring
This is a talk given at Eclipse Con Europe 2014 on how to use the open source project DAWN, Data Analysis Workbench. This project has two papers with more than three hundred citations of using the software.
DDS Advanced Tutorial - OMG June 2013 Berlin MeetingJaime Martin Losa
An extended, in-depth tutorial explaining how to fully exploit the standard's unique communication capabilities.Presented at the OMG June 2013 Berlin Meeting.
Users upgrading to DDS from a homegrown solution or a legacy-messaging infrastructure often limit themselves to using its most basic publish-subscribe features. This allows applications to take advantage of reliable multicast and other performance and scalability features of the DDS wire protocol, as well as the enhanced robustness of the DDS peer-to-peer architecture. However, applications that do not use DDS's data-centricity do not take advantage of many of its QoS-related, scalability and availability features, such as the KeepLast History Cache, Instance Ownership and Deadline Monitoring. As a consequence some developers duplicate these features in custom application code, resulting in increased costs, lower performance, and compromised portability and interoperability.
This tutorial will formally define the data-centric publish-subscribe model as specified in the OMG DDS specification and define a set of best-practice guidelines and patterns for the design and implementation of systems based on DDS.
Data/AI driven product development: from video streaming to telehealthXavier Amatriain
Healthcare is different from any other application domain, or is it not? While it is true that there are specific aspects, such as high stakes decisions and a complex regulatory framework, that make healthcare somewhat different, it is also the case that many of the lessons learned from building data-driven products in other domains translate remarcably well into healthcare. This is particularly so because healthcare is also a user facing domain, where users can be both patients or healthcare professionals. Given that data has shown to improve user experience while ensuring quality and scalability, few would argue that healthcare cannot benefit from being much more data-driven than it has traditionally been.
In this talk, I described how this experience building impactful data and AI solutions into user facing products for decades can be leveraged to revolutionize telehealth. At Curai, we combine approaches such as state-of-the-art large language models with expert systems in areas such as NLP, vision, and automated diagnosis to augment and scale doctors, and to improve user experience and healthcare outcomes. We will see some of those applications while analyzing the role of data and ML algorithms in making them possible.
AI-driven product innovation: from Recommender Systems to COVID-19Xavier Amatriain
AI/Machine Learning has become an integral part of many household tech products, from Netflix to our phones. In this talk I will draw from my experience driving AI teams at some of those companies to showcase how AI can positively impact products as different as Netflix and Curai, an online telehealth service.
With half of the world’s population lacking access to healthcare services, and 30% of the adult population in the US having inadequate health insurance coverage to get even basic access to services, it should have been clear that a pandemic like COVID-19 would strain the global healthcare system way over its maximum capacity. In this context, many are trying to embrace and encourage the use of telehealth as a way to provide safe and convenient access to care. However, telehealth in itself can not scale to cover all our needs unless we improve scalability and efficiency through AI and automation.
In this talk, we will describe how our work on combining latest AI advances with medical experts and online access has the potential to change the landscape in healthcare access and provide 24/7 quality healthcare. Combining areas such as NLP, vision, and automatic diagnosis we can augment and scale doctors. We will describe our work on combining expert systems with deep learning to build state-of-the-art medical diagnostic models that are also able to model the unknowns. We will also show our work on using language models for medical Q&A . More importantly, we will describe how those approaches have been used to address the urgent and immediate needs of the current pandemic.
AI for COVID-19: An online virtual care approachXavier Amatriain
Slides for the talk I gave at the AI and COVID-19 virtual conference at Stanford. Video here: https://hai.stanford.edu/events/covid-19-and-ai-virtual-conference/video-archive
From one to zero: Going smaller as a growth strategyXavier Amatriain
This talk was designed for Engineering managers. Having been at companies of all sizes, I recommend managers who want to grow to go smaller. At the same time I reflect on what are the important things that remain constant regardless the size and context and which ones don't.
Deep learning has accomplished impressive feats in areas such as voice recognition, image processing, and natural language processing. Deep learning enthusiasts have rushed to predict that this family of algorithms is likely to take over most other applications in the near future. This focus on deep architectures seems to have cast a shadow over more “traditional” machine learning and data science approaches, leaving researchers and practitioners alike wondering whether there is any point in investing in feature engineering or simpler models.
In this talk, I will go over what deep learning can and cannot do for you, both now and in the near future. I will also describe how different approaches will continue to be needed, and why their demand will likely grow despite the rise of deep learning. I will support my claims not only by looking at recent publications, but also by using practical examples drawn from my experience at companies at the forefront of machine learning applications, such as Quora.
Past, present, and future of Recommender Systems: an industry perspectiveXavier Amatriain
Keynote for the ACM Intelligent User Interface conference in 2016 in Sonoma, CA. I start with the past by talking about the Recommender Problem, and the Netflix Prize. Then I go into the Present and the Future by talking about approaches that go beyond rating prediction and ranking and by finishing with some of the most important lessons learned over the years. Throughout my talk I put special emphasis on the relation between algorithms and the User Interface.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
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.