Prof. Gregoris Mentzas, Director, Information Management Unit
(National Technical University of Athens) presented "Towards Proactive Enterprise Intelligence" (FInES Workshop at Aalborg)
A sample of my book "Business unIntelligence - Insight and Innovation beyond Analytics and Big Data", published by Technics Publications, 2013.
Chapter 5 shows the evolution of the Data Warehouse architecture and provides a description of some aspects of a modern Information architecture.
The book can be ordered in hard and softcopy formats at http://bit.ly/BunI-TP1
Business unIntelligence - a Whistle Stop TourBarry Devlin
The old world of business intelligence is being transformed into a new biz-tech ecosystem. Analytics is forcing the recombination of operational and informational systems in a consistent and coherent IT environment for all business activities. Big data—despite the hype—introduces two very different types of information that transform how business processes interact with the external world. Together, these directions are driving a new BI, so different to its prior form that I call it “Business unIntelligence”. This session covers:
- Business drivers and results of the biz-tech ecosystem
- Modern conceptual and logical architectures for information, process and people
- Positioning of all forms of business analytic and big data
Why Big Data Analytics Needs Business Intelligence Too Barry Devlin
Business and IT are facing the challenge of getting real and urgent value from ever-expanding information sources. Building independent silos of big data analytics is no longer enough. True progress comes only by integrating data from traditional operational and informational sources with the new sources that are becoming available, whether from social media or interconnected machines.
In this April 2014 BrightTALK webinar, Dr. Barry Devlin describes the thinking, architecture, tools and methods needed to achieve a new joined-up, comprehensive data environment.
IoT's rapid evolution marks the next stage in the innovation economy - White ...Technicolor
Like many new technology trends – such as Big Data or Cloud
Computing – that have captured the imagination of consumers
and business executives alike, the Internet of Things, or IoT,
has become a bit like a “Rorschach Test.” People see what they
want to see with the term is invoked.
To be fair, IoT lends itself to this tendency, because the concept
is so incredibly big, and its implications so deep. At its root IoT
is about devices talking to each other without human intervention
using the internet protocol. But this alone would cleanly fall into
the category of machine-to-machine (M2M) communications.
“When you look at what’s happening with IoT devices, explains
Danny Lousberg, Director of Product Management for Qeo
at Technicolor, “you will see a huge effort to create a vertical
ecosystem in which a specific device is communicating with a
specific back-end server that lives somewhere in the cloud to
tackle a specific use case for the user. And that means these
devices all are battling for a piece of mindshare and eyeballs.”
“The Internet of Things is inherently different from M2M
communication because M2M is really meant to solve large-scale
problems for a big group of devices that are all trying to work
together in a larger environment that is not necessarily controlled
by the end user.”
What makes IoT truly powerful is when M2M is linked to Mobility,
Big Data, Cloud Computing and other critical elements in today’s
modern technology infrastructure to empower and provide
options to end-users.
“From my perspectives, it will be virtually impossible to view these
technological paradigms independent of each other and from IoT,”
says Kurt Jonckheer, General Manager, Virdata, and VP, Strategic
Projects, Technicolor.
“The promise of IoT is that devices and appliances of all sorts
will, without human interference, interact with each other to
create a better experience for users by engaging in things like
self-diagnosis, harnessing event-driven actions that enhance
the human experience, or simply reduce costs in an intelligent
and automated manner.”
This combination of technologies is already generating billions
of dollars in revenue. Trillions more will be triggered as
businesses come to grips with the true potential of IoT.
Wikipedia (DBpedia): Crowdsourced Data CurationEdward Curry
Wikipedia is an open-source encyclopedia, built collaboratively by a large community of web editors. The success of Wikipedia as one of the most important sources of information available today still challenges existing models of content creation. Despite the fact that the term ‘curation’ is not commonly addressed by Wikipedia’s contributors, the task of digital curation is the central activity of Wikipedia editors, who have the responsibility for information quality standards.
Wikipedia, is already widely used as a collaborative environment inside organizations5.
The investigation of the collaboration dynamics behind Wikipedia highlights important features and good practices which can be applied to different organizations. Our analysis focuses on the curation perspective and covers two important dimensions: social organization and artifacts, tools & processes for cooperative work coordination. These are key enablers that support the creation of high quality information products in Wikipedia’s decentralized environment.
Global Data Management: Governance, Security and Usefulness in a Hybrid WorldNeil Raden
With Global Data Management methodology and tools, all of your data can be accessed and used no matter where it is or where it is from: on-premises, private cloud, public cloud(s), hybrid cloud, open source, third-party data and any combination of the these, with security, privacy and governance applied as if they were a single entity. Ingenious software products and the economics of computing make it economical to do this. Not free, but feasible.
A sample of my book "Business unIntelligence - Insight and Innovation beyond Analytics and Big Data", published by Technics Publications, 2013.
Chapter 5 shows the evolution of the Data Warehouse architecture and provides a description of some aspects of a modern Information architecture.
The book can be ordered in hard and softcopy formats at http://bit.ly/BunI-TP1
Business unIntelligence - a Whistle Stop TourBarry Devlin
The old world of business intelligence is being transformed into a new biz-tech ecosystem. Analytics is forcing the recombination of operational and informational systems in a consistent and coherent IT environment for all business activities. Big data—despite the hype—introduces two very different types of information that transform how business processes interact with the external world. Together, these directions are driving a new BI, so different to its prior form that I call it “Business unIntelligence”. This session covers:
- Business drivers and results of the biz-tech ecosystem
- Modern conceptual and logical architectures for information, process and people
- Positioning of all forms of business analytic and big data
Why Big Data Analytics Needs Business Intelligence Too Barry Devlin
Business and IT are facing the challenge of getting real and urgent value from ever-expanding information sources. Building independent silos of big data analytics is no longer enough. True progress comes only by integrating data from traditional operational and informational sources with the new sources that are becoming available, whether from social media or interconnected machines.
In this April 2014 BrightTALK webinar, Dr. Barry Devlin describes the thinking, architecture, tools and methods needed to achieve a new joined-up, comprehensive data environment.
IoT's rapid evolution marks the next stage in the innovation economy - White ...Technicolor
Like many new technology trends – such as Big Data or Cloud
Computing – that have captured the imagination of consumers
and business executives alike, the Internet of Things, or IoT,
has become a bit like a “Rorschach Test.” People see what they
want to see with the term is invoked.
To be fair, IoT lends itself to this tendency, because the concept
is so incredibly big, and its implications so deep. At its root IoT
is about devices talking to each other without human intervention
using the internet protocol. But this alone would cleanly fall into
the category of machine-to-machine (M2M) communications.
“When you look at what’s happening with IoT devices, explains
Danny Lousberg, Director of Product Management for Qeo
at Technicolor, “you will see a huge effort to create a vertical
ecosystem in which a specific device is communicating with a
specific back-end server that lives somewhere in the cloud to
tackle a specific use case for the user. And that means these
devices all are battling for a piece of mindshare and eyeballs.”
“The Internet of Things is inherently different from M2M
communication because M2M is really meant to solve large-scale
problems for a big group of devices that are all trying to work
together in a larger environment that is not necessarily controlled
by the end user.”
What makes IoT truly powerful is when M2M is linked to Mobility,
Big Data, Cloud Computing and other critical elements in today’s
modern technology infrastructure to empower and provide
options to end-users.
“From my perspectives, it will be virtually impossible to view these
technological paradigms independent of each other and from IoT,”
says Kurt Jonckheer, General Manager, Virdata, and VP, Strategic
Projects, Technicolor.
“The promise of IoT is that devices and appliances of all sorts
will, without human interference, interact with each other to
create a better experience for users by engaging in things like
self-diagnosis, harnessing event-driven actions that enhance
the human experience, or simply reduce costs in an intelligent
and automated manner.”
This combination of technologies is already generating billions
of dollars in revenue. Trillions more will be triggered as
businesses come to grips with the true potential of IoT.
Wikipedia (DBpedia): Crowdsourced Data CurationEdward Curry
Wikipedia is an open-source encyclopedia, built collaboratively by a large community of web editors. The success of Wikipedia as one of the most important sources of information available today still challenges existing models of content creation. Despite the fact that the term ‘curation’ is not commonly addressed by Wikipedia’s contributors, the task of digital curation is the central activity of Wikipedia editors, who have the responsibility for information quality standards.
Wikipedia, is already widely used as a collaborative environment inside organizations5.
The investigation of the collaboration dynamics behind Wikipedia highlights important features and good practices which can be applied to different organizations. Our analysis focuses on the curation perspective and covers two important dimensions: social organization and artifacts, tools & processes for cooperative work coordination. These are key enablers that support the creation of high quality information products in Wikipedia’s decentralized environment.
Global Data Management: Governance, Security and Usefulness in a Hybrid WorldNeil Raden
With Global Data Management methodology and tools, all of your data can be accessed and used no matter where it is or where it is from: on-premises, private cloud, public cloud(s), hybrid cloud, open source, third-party data and any combination of the these, with security, privacy and governance applied as if they were a single entity. Ingenious software products and the economics of computing make it economical to do this. Not free, but feasible.
The Myth of Health Data Integration ComplexityShahid Shah
At Health:Refactored (San Francisco) I presented a practical and technical look at why current health IT systems integrate poorly and how we can fix it.
Collaborative Data Management: How Crowdsourcing Can Help To Manage DataEdward Curry
Data management efforts such as MDM are a popular approach for high quality enterprise data. However, MDM can be heavily centralized and labour intensive, where the cost and effort can become prohibitively high. The concentration of data management and stewardship onto a few highly skilled individuals, like developers and data experts, can be a significant bottleneck. This talk explores how to effectively involving a wider community of users within collaborative data management activities. The bottom-up approach of involving crowds in the creation and management of data has been demonstrated by projects like Freebase, Wikipedia, and DBpedia. The talk is discusses how collaborative data management can be applied within an enterprise context using platforms such as Amazon Mechanical Turk, Mobile Works, and internal enterprise human computation platforms.
Topics covered include:
- Introduction to Crowdsourcing and Human Computation for Data Management
- Crowds vs. Communities, When to use them and why
- Push vs. Pull methods of crowdsourcing data management
- Setting up and running a collaborative data management process
- Modelling the expertise of communities
8 reasons you need a strategy for managing information...before it's too lateJohn Mancini
Highlights from a keynote presentation that complements AIIM's free e-book -- 8 reasons you need a strategy for managing information...before it's too late.
E-book available at http://www.aiim.org/8things
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
The Role of Community-Driven Data Curation for EnterprisesEdward Curry
With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance. This chapter provides an overview of data curation, discusses the business motivations for curating data and investigates the role of community-based data curation, focusing on internal communities and pre-competitive data collaborations. The chapter is supported by case studies from Wikipedia, The New York Times, Thomson Reuters, Protein Data Bank and ChemSpider upon which best practices for both social and technical aspects of community-driven data curation are described.
E. Curry, A. Freitas, and S. O’Riáin, “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood, Ed. Boston, MA: Springer US, 2010, pp. 25-47.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
Presentation of the research activities of IMU (Information Management Unit) a multi-disciplinary research lab of the Institute of Communication and Computer Systems (ICCS) at the National Technical University of Athens, Greece.
See http://imu.iccs.gr
The Myth of Health Data Integration ComplexityShahid Shah
At Health:Refactored (San Francisco) I presented a practical and technical look at why current health IT systems integrate poorly and how we can fix it.
Collaborative Data Management: How Crowdsourcing Can Help To Manage DataEdward Curry
Data management efforts such as MDM are a popular approach for high quality enterprise data. However, MDM can be heavily centralized and labour intensive, where the cost and effort can become prohibitively high. The concentration of data management and stewardship onto a few highly skilled individuals, like developers and data experts, can be a significant bottleneck. This talk explores how to effectively involving a wider community of users within collaborative data management activities. The bottom-up approach of involving crowds in the creation and management of data has been demonstrated by projects like Freebase, Wikipedia, and DBpedia. The talk is discusses how collaborative data management can be applied within an enterprise context using platforms such as Amazon Mechanical Turk, Mobile Works, and internal enterprise human computation platforms.
Topics covered include:
- Introduction to Crowdsourcing and Human Computation for Data Management
- Crowds vs. Communities, When to use them and why
- Push vs. Pull methods of crowdsourcing data management
- Setting up and running a collaborative data management process
- Modelling the expertise of communities
8 reasons you need a strategy for managing information...before it's too lateJohn Mancini
Highlights from a keynote presentation that complements AIIM's free e-book -- 8 reasons you need a strategy for managing information...before it's too late.
E-book available at http://www.aiim.org/8things
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
The Role of Community-Driven Data Curation for EnterprisesEdward Curry
With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance. This chapter provides an overview of data curation, discusses the business motivations for curating data and investigates the role of community-based data curation, focusing on internal communities and pre-competitive data collaborations. The chapter is supported by case studies from Wikipedia, The New York Times, Thomson Reuters, Protein Data Bank and ChemSpider upon which best practices for both social and technical aspects of community-driven data curation are described.
E. Curry, A. Freitas, and S. O’Riáin, “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood, Ed. Boston, MA: Springer US, 2010, pp. 25-47.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
Presentation of the research activities of IMU (Information Management Unit) a multi-disciplinary research lab of the Institute of Communication and Computer Systems (ICCS) at the National Technical University of Athens, Greece.
See http://imu.iccs.gr
Data Pioneers - Roland Haeve (Atos Nederland) - Big data in organisatiesMultiscope
Roland Haeve is cross competence manager Big Data voor Atos Nederland. Roland heeft ruim 18 jaar ICT-ervaring in het aanbieden van complete oplossingen binnen onder andere Business Intelligence (BI) en Big Data (Analytics). Big Data is voor veel bedrijven nog pionieren en uitzoeken wat de mogelijkheden zijn. In zijn presentatie zal Roland ingaan op succesvolle Big Data cases. Hij zal hierbij niet enkel inzoomen op Nederland, maar ook bredere, Europese voorbeelden meenemen.
EDF2013: Invited Talk Julie Marguerite: Big data: a new world of opportunitie...European Data Forum
Invited Talk Julie Marguerite, THALES, at the European Data Forum 2013, 9 April 2013 in Dublin, Ireland: Big data: a new world of opportunities for software services
Go from data to decision in one unified platform.pdfwebmaster553228
According to IDC’s January 2022 Worldwide CEO Survey, 65% of organizations are using at least 10 different data engineering and intelligence tools to integrate data.
Analytics Unleashed_ Navigating the World of Data Science.pdfkhushnuma khan
The 21st century has witnessed an unprecedented explosion in the volume, variety, and velocity of data. This deluge of information, often referred to as “Big Data,” has spurred the emergence of Data Science as a crucial discipline. Data Science integrates statistical methodologies, advanced programming, and domain expertise to analyze and interpret complex datasets. Its applications span diverse sectors, including business, healthcare, finance, and technology.
Beginning to understand the world of data demands the evolution of procedures and skillsets in tune with the rewarding trends. As the excerpts from the Fortune Business Insight article state; the market for data analytics is estimated to expand by 25% between 2021-2030. Data scientists are predicted to leverage the highest possible benefits for industries such as banking, finance, insurance, entertainment, telecommunication, automobile, etc.
Pace up with the fastest-evolving industries of all time. Make informed decisions in the world of Data Science by mastering the emerging trends in diversified realms of data. Bring in the change with the following Data Science trends set in place in time:
1. Blockchain technology
2. Natural Language Processing
3. Internet of Things
4. Auto Machine Learning
5. Immersive experiences
6. Robotic Process Automation
7. TinyML and Small Data
8. AI-powered Virtual Assistants
9. Graph Analytics
10. Cloyd computing
11. Image processing
12. Data Visualization
13. Augmented Analytics
14. Predictive Analytics
15. Scalable Artificial Intelligence
As is evident, there will be more data in the coming years. This is a clear indication of an escalated need for staying upbeat with the proposed data science industry trends for years to follow. Make the most of the opportunity by enrolling with top-ranking data science certifications from globally renowned data credentials providers.
Download your copy & boost your chances at landing your dream Data Science Jobs with USDSI®
Cloud-Based IoT Analytics and Machine LearningSatyaKVivek
Among the IT developments that have made it to the forefront in recent times, machine learning and IoT certainly stand out. As with most such technologies, integrating the two can help develop powerful IoT solutions and tackle complex challenges. More specifically speaking, machine learning can be leveraged in cloud based IoT analytics.
Investing in AI: Moving Along the Digital Maturity CurveCognizant
Digitally mature businesses are more likely to consider themselves at an advanced stage of AI adoption, according to our recent study, enabling them to turn data into insights at the scale and precision required today.
What happens in the Innovation of Things?Kim Escherich
From the ComputerWorld Internet of Things conference in Copenhagen October 27 2015. On definitions, markets, trends, needed capabilities and how to implement using IBM BlueMix.
IDC Portugal | Como Libertar os Seus Dados com Virtualização de DadosDenodo
Watch full webinar here: https://bit.ly/3w1LoDi
Os dados se tornaram o ativo mais crítico para qualquer empresa ter sucesso nesta era de transformação digital.
Nesta sessão, Paul Moxon da Denodo irá explicar como funciona a virtualização de dados e como pode ajudar as organizações a responder melhor às necessidades de negócios, integrando dados de várias fontes de dados, também minimizando custos e tempo, e aumentando a quantidade de dados disponibilizados em geral.
Para melhor compreensão, Mariana Pinto da Passio Consulting apresentará uma demonstração ao vivo da Plataforma Denodo.
WHITE PAPER discussion on:
Governance, Policy, Standards: Support for Complexity in the Real World
EU Research – Integrating our way out of silos: purposeful Federation
Complexity Science & Society; EU Calls: CAPS; FI Science/FInES/FIRE; Global Systems;
(also COSI‐ICT; DyM‐CS; FOCAS; FuturICT)
Society: people, purpose & complex behaviour modelling (simulation & dissimulation)
The Peoples' Toolkit: Computational Socio‐Geonomics/Metaloger (CSG/M)
ICT ‐ A new Kondratiev Shift: On Computable Society
SOCIO‐TECHNOLOGY
FASyS: Personalised and Proactive Health and Safety for Aging Workforces in the Future Sensing Enterprise Working Environments
Dr Oscar Lazaro – Innovalia Association
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
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P3 4-gregoris mentzas
1. Towards Proactive Enterprise Intelligence
Prof. Gregoris Mentzas
Director, Information Management Unit
National Technical University of Athens
www.imu.ntua.gr
gmentzas@mail.ntua.gr
twitter: gmentzas
FInES Workshop, Future Internet Assembly
Aalborg, Denmark, 9th May, 2012
2. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Everything generates data
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 2
4. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Enterprise ‘Big Data’
Source: McKinsey
Global Institute (2011)
A 2011 study by MIT found that effective use of data and analytics correlated
with a 5 to 6 percent improvement in productivity, profitability & market value.
Erik Brynjolfsson, Lorin M. Hitt, and Heekyung Hellen Kim, “Strength in numbers: How does data-driven decision making
affect firm performance?” Social Science Research Network (SSRN), April 2011.
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 4
5. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Proactive enterprise capabilities
Ability for early recognition and exploitation of
opportunities.
ability to act agilely to changes in demand for a product
respond to an emerging customer need
Ability to alter the likelihood that negative
outcomes will occur by intervening prior to their
occurrence
prevent the loss of a customer to a competitor
initiate measures to mitigate costs of interruptions in
processes
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 5
6. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Challenges for Proactive Enterprise Intelligence
Fuzzy
Predictive
Decision-
Analytics
making
Process
Agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 6
7. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Challenges for Proactive Enterprise Intelligence
Fuzzy
Predictive
Decision-
Analytics
making
Process
Agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 7
8. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
From Business Analytics to Predictive Analytics
Next generation analytics will expand beyond measuring and
describing the past to predicting what is likely to happen, and
optimizing what should happen
Need for analytic tools that are self-directed
Unlike services triggered by a person, a device or software application
and implement continuous intelligence
they run nonstop and incorporate mobile, social and collaborative consumer
interactions
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 8
9. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Source: Gartner (2012) “Advanced Analytics: Predictive, Collaborative and Pervasive” Feb. 2012
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 9
10. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Research Challenges for Predictive Analytics
Future Internet Enterprises need to
be able to adopt data-driven processes in order to comprehend and
predict changes in their business environment.
Research challenges include:
Big Data and Text Analytics
Social Network mining
Predictive modelling
Machine learning techniques
Processing of structured and unstructured data
Semantic services based on big and linked data
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 10
11. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Bothos, E., D. Apostolou, G. Mentzas (2010) Using Social Media to Predict Future Events with Agent-based
Markets, IEEE Intelligent Systems, November-December, 2010,May,50-58
Future Internet Assembly, Aalborg, Denmark 9th pp. 2012 11
12. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Challenges for Proactive Enterprise Intelligence
Fuzzy
Predictive
Decision-
Analytics
making
Process
Agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 12
13. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
The inherent uncertainty of proactive business
Predicting business issues cannot lead to exact solutions
Uncertainty whether a business situation actually occurred or on
the predicted value of a specific information item, increases the
need for adopting probabilistic approaches
Augmenting decision-making processes
with fuzzy and linguistic approaches
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 13
14. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Research Challenge III: Fuzzy Decision Making
Research challenges to augment decision-making:
Uncertain data management
Fuzzy Multiple-Criteria Evaluation
Probabilistic multi-criteria decision making
e.g. Hidden Markov processes, Bayesian Belief Networks etc
Statistical inference and learning approaches
e.g. Markov Decision Processes, Markov Learning Networks
Fuzzy Semantic Web techniques
Linguistic modeling techniques
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 14
15. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Fuzzy linguistic approaches in service selection
Patiniotakis, I., D. Apostolou, G. Mentzas (2011) Fuzzy UTASTAR: A method for discovering utility
functions from fuzzy data, Expert Systems with Applications, Vol. 38, 12, Nov-Dec 2011, 15463-15474
Patiniotakis, I., D. et al (2012) Linguistic Multi-criteria Decision Making for Web service Selection, ICCS
working paper, 2012
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 15
16. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Challenges for Proactive Enterprise Intelligence
Fuzzy
Predictive
Decision-
Analytics
making
Process
Agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 16
17. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Integrating analytics for agile process flows
Predictive capability as a mode of operation used to rapidly
produce analytical information based on event data from
business processes in order to support decision making
Businesses aim to use analytics for business process innovation and
differentiation
Organizations effective in the integration of predictive analytic
capabilities and fuzzy decision making within business
processes will be seeing lower costs and greater business
impact
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 17
18. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Research Challenges for Process Agility
Process agility represents a set of techniques and technologies
that incorporate BPM, Complex Event Processing, and
Artificial Intelligence
Research challenges include:
Semantics in event-driven processing
Event stream processing in business processes
Events in human-oriented tasks
Event-driven business process management
Context perception and situational awareness
Situation-driven process adaptation
Goal-oriented event-driven process agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 18
19. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Process agility in logistics
Logistics managers are tapping early capabilities to get knowledge of changing
conditions and increase their ability to make proactive route adjustments
Patiniotiakis, I., et al (2011) A Framework for Situation-Aware Adaptation of Service-Based Applications, 4th
European ServiceWave Conference, Poznan, 26-28 /10/11
Magoutas, B. D. Apostolou, G. Mentzas (2012) An event-driven Framework for Business Awareness
Management, ICCS working paper, February 2012
20. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Challenges for Proactive Enterprise Intelligence
Fuzzy
Predictive Decision-
Analytics making
Process
Agility
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 20
21. Information Management Unit / ICCS of NTUA www.imu.iccs.gr
Capabilities of Proactive Enterprise Intelligence
Capability to reveal insights and extract -
previously hidden – meaningful patterns from
structured and unstructured ‘big data’ from a
multitude of sources
sensors and actuators embedded in objects
customer transactions
social interactions, GPS trails, etc.
Capability to be proactive, i.e. to be able to
develop predictions and implement
respective actions
recognize possible opportunities or threats
before these actually happen and
trigger appropriate actions
Future Internet Assembly, Aalborg, Denmark 9th May, 2012 21
22. Thank you for your attention!
http://www.imu.ntua.gr
Contact
Prof. Gregoris Mentzas
Director, Information Management Unit
National Technical University of Athens
W: www.imu.ntua.gr
E: gmentzas@mail.ntua.gr