This document provides an overview of the emerging commercial drone market and opportunities for software applications development. It discusses what drones are and common uses like precision agriculture, infrastructure inspection, and real estate. An example of using drones for pole inspection is described. Regulations from the FAA are limiting but expected to evolve. Big data and internet of things technologies can be leveraged to build solutions for automated data collection, analysis and decision making. While public perception and some limitations still exist, the market is growing and those that act now will be well positioned for the future.
Event Streaming Architecture for Industry 4.0 - Abdelkrim Hadjidj & Jan Kuni...Flink Forward
New use cases under the Industry 4.0 umbrella are playing a key role in improving factory operations, process optimization, cost reduction and quality improvement. We propose an event streaming architecture to streamline the information flow all the way from the factory to the main data center. Building such a streaming architecture enables a manufacturer to react faster to critical operational events. However, it presents two main challenges:
Data acquisition in real time: data should be collected regardless of its location or access challenges are. It is commonplace to ingest data from hundreds of heterogeneous data sources (ERP, MES, Sensors, maintenance systems, etc).
Event processing in real time: events collected from different parts of the organization should be combined into actionable insights in real time. This is extremely challenging in a context where events can be lost or delayed.
In this talk, we show how Apache NiFi and MiNiFi can be used to collect a wide range of datasources in real-time, connecting the industrial and information worlds. Then, we show how Apache Flink’s unique features enables us to make sense of this data. For instance, we will explain how Flink’s time management such Event Time mode, late arrival handling and watermark mechanism can be used to address the challenge of processing IoT data originating from geographically distributed plants. Finally, we demonstrate an end to end streaming architecture for Industry 4.0 based on the Cloudera DataFlow platform.
How Spark Enables the Internet of Things: Efficient Integration of Multiple ...sparktc
IBM researchers in Haifa, together with partners from the COSMOS EU-funded project, are using Spark to analyze the new wave of IoT data and solve problems in a way that is generic, integrated, and practical.
Driving Efficiency with Splunk Cloud at Gatwick AirportSplunk
Gatwick Airport, the busiest single runway airport in the world, needed to ensure a high degree of efficiency for a record-breaking 925 daily flights and 38 million annual passengers. This presentation covers how they:
- Combine historical fact with "in the moment" data and events to predict success or failure, enabling the operation to prevent issues before they occur
- Support other organisations (e.g., airlines and ground handlers) with dashboards to improve their performance
- Moved from "how did we do?" to "how are we doing?" and are on the edge of answering "How will we do?”
- Plan to expand the use of Splunk Cloud in the future: tracking travel disruption, predicting passenger flow and getting real-time feedback via social media monitoring
Also, learn why a cloud solution gives Gatwick Airport the agility and scalability to achieve what they need.
Event Streaming Architecture for Industry 4.0 - Abdelkrim Hadjidj & Jan Kuni...Flink Forward
New use cases under the Industry 4.0 umbrella are playing a key role in improving factory operations, process optimization, cost reduction and quality improvement. We propose an event streaming architecture to streamline the information flow all the way from the factory to the main data center. Building such a streaming architecture enables a manufacturer to react faster to critical operational events. However, it presents two main challenges:
Data acquisition in real time: data should be collected regardless of its location or access challenges are. It is commonplace to ingest data from hundreds of heterogeneous data sources (ERP, MES, Sensors, maintenance systems, etc).
Event processing in real time: events collected from different parts of the organization should be combined into actionable insights in real time. This is extremely challenging in a context where events can be lost or delayed.
In this talk, we show how Apache NiFi and MiNiFi can be used to collect a wide range of datasources in real-time, connecting the industrial and information worlds. Then, we show how Apache Flink’s unique features enables us to make sense of this data. For instance, we will explain how Flink’s time management such Event Time mode, late arrival handling and watermark mechanism can be used to address the challenge of processing IoT data originating from geographically distributed plants. Finally, we demonstrate an end to end streaming architecture for Industry 4.0 based on the Cloudera DataFlow platform.
How Spark Enables the Internet of Things: Efficient Integration of Multiple ...sparktc
IBM researchers in Haifa, together with partners from the COSMOS EU-funded project, are using Spark to analyze the new wave of IoT data and solve problems in a way that is generic, integrated, and practical.
Driving Efficiency with Splunk Cloud at Gatwick AirportSplunk
Gatwick Airport, the busiest single runway airport in the world, needed to ensure a high degree of efficiency for a record-breaking 925 daily flights and 38 million annual passengers. This presentation covers how they:
- Combine historical fact with "in the moment" data and events to predict success or failure, enabling the operation to prevent issues before they occur
- Support other organisations (e.g., airlines and ground handlers) with dashboards to improve their performance
- Moved from "how did we do?" to "how are we doing?" and are on the edge of answering "How will we do?”
- Plan to expand the use of Splunk Cloud in the future: tracking travel disruption, predicting passenger flow and getting real-time feedback via social media monitoring
Also, learn why a cloud solution gives Gatwick Airport the agility and scalability to achieve what they need.
IIoT + Predictive Analytics: Solving for Disruption in Oil & Gas and Energy &...DataWorks Summit
The electric grid has evolved from linear generation and delivery to a complex mix of renewables, prosumer-generated electricity, and electric vehicles (EVs). Smart meters are generating loads of data. As a result, traditional forecasting models and technologies can no longer adequately predict supply and demand. Extreme weather, an aging infrastructure, and the burgeoning worldwide population are also contributing to increased outage frequency.
In oil and gas, commodity pricing pressures, resulting workforce reductions, and the need to reduce failures, automate workflows, and increase operational efficiencies are driving operators to shift analytics initiatives to advanced data-driven applications to complement physics-based tools.
While sensored equipment and legacy surveillance applications are generating massive amounts of data, just 2% is understood and being leveraged. Operationalizing it along with external datasets enables a shift from time-based to condition-based maintenance, better forecasting and dramatic reductions in unplanned downtime.
The session includes plenty of real-world anecdotes. For example, how an electric power holding company reduced the time it took to investigate energy theft from six months to less than one hour, producing theft leads in minutes and an expected multi-million dollar ROI. How a global offshore contract drilling services provider implemented an open source IIoT solution across its fleet of assets in less than a year, enabling remote monitoring, predictive analytics and maintenance.
Key takeaways:
• How are new processes for data collection, storage and democratization making it accessible and usable at scale?
• Beyond time series data, what other data types are important to assess?
• What advantage are open source technologies providing to enterprises deploying IIoT?
• Why is collaboration important across industrial verticals to increase IIoT open source adoption?
Speaker
Kenneth Smith, General Manager, Energy, Hortonworks
Real-time Streaming Analytics: Business Value, Use Cases and Architectural Co...Impetus Technologies
Impetus webcast ‘Real-time Streaming Analytics: Business Value, Use Cases and Architectural Considerations’ available at http://bit.ly/1i6OrwR
The webinar talks about-
• How business value is preserved and enhanced using Real-time Streaming Analytics with numerous use-cases in different industry verticals
• Technical considerations for IT leaders and implementation teams looking to integrate Real-time Streaming Analytics into enterprise architecture roadmap
• Recommendations for making Real-time Streaming Analytics – real – in your enterprise
• Impetus StreamAnalytix – an enterprise ready platform for Real-time Streaming Analytics
A presentation pertaining to the integration of real-time data to the cloud with significant potential in the areas of Industrial IT,Real-time sensor information processing and Smart grids applied to various vertical industries. This is related to my blog post at www.cloudshoring.in
Industrial IoT is currently transforming how businesses capitalize their big data. Changes in how business is done, combined with multiple technology drivers make geo-distributed data increasingly important for enterprises. These changes are causing serious disruption across a wide range of industries.
Platform for the Research and Analysis of Cybernetic ThreatsDataWorks Summit
This talk describes, from an architectural point of view, how to exploit the HDP + Nifi technological platform aimed at researching, exploiting and targeting events related to Cyber Security. The purpose of the system is to create a knowledge base related to the events, actors and operating methods with which the cyber attacks happened and may happen, collecting both real-time data from social networks and web pages or literature material on such episodes in batch modality. The process focuses text and graph analysis at scale thanks to Spark engine Metron and Kafka, on a complexly integrated tech stack, that enhances the capabilities of the algorithms and results to offer a flexible solution to the analysts. The system supports the user in determining the motivations and eventually the actual executors of the attacks and, hopefully, the instigators of the same, also thanks to a smart representation of data stored on a graph NoSQL database. A further aim of the system will be to determine, in a predictive way, the "symptoms" or the processes connected to the attacks.
Build and Run Streaming Applications with Apache Flink and Amazon Kinesis Dat...Flink Forward
Stream processing facilitates the collection, processing, and analysis of real-time data and enables the continuous generation of insights and quick reactions to emerging situations. Yet, despite these advantages compared to traditional batch-oriented analytics applications, streaming applications are much more challenging to operate. Some of these challenges include the ability to provide and maintain low end-to-end latency, to seamlessly recover from failure, and to deal with a varying amount of throughput.
We all know and love Flink to take on those challenges with grace. In this session, we explore an end to end example that shows how you can use Apache Flink and Amazon Kinesis Data Analytics for Java Applications to build a reliable, scalable, and highly available streaming applications. We discuss how you can leverage managed services to quickly build Flink based streaming applications and show managed services can help to substantially reduce the operational overhead that is required to run the application. We also review best practices for running streaming applications with Apache Flink on AWS.
So you will not only see how to actually build streaming applications with Apache Flink on AWS, you will also learn how leveraging managed services can help to reduce the overhead that is usually required to build and operate streaming applications to a bare minimum.
Real Time Analytics: Algorithms and SystemsArun Kejariwal
In this tutorial, an in-depth overview of streaming analytics -- applications, algorithms and platforms -- landscape is presented. We walk through how the field has evolved over the last decade and then discuss the current challenges -- the impact of the other three Vs, viz., Volume, Variety and Veracity, on Big Data streaming analytics.
Speaker: Atul Kshirsagar, GE Software
To learn more about Pivotal Cloud Foundry, visit http://www.pivotal.io/platform-as-a-service/pivotal-cloud-foundry.
Make Streaming IoT Analytics Work for YouHortonworks
Download Hortonworks DataFlow (HDF™) here - http://hortonworks.com/downloads/#dataflow. Making Streaming IoT Analytics Work For You With Apache NiFi, Storm, Raspberry Pi and more.
See how the Elastic Stack enables Postbank Systems to drive transformation from monitoring bank branches and ATMs and creating an anti-fraud system, to ensuring that the Postbank Group is GDPR compliant.
Watch the video: https://www.elastic.co/elasticon/tour/2019/munich/powering-postbank-groups-data-driven-strategy
How to Apply Machine Learning with R, H20, Apache Spark MLlib or PMML to Real...Kai Wähner
"Big Data" is currently a big hype. Large amounts of historical data are stored in Hadoop or other platforms. Business Intelligence tools and statistical computing are used to draw new knowledge and to find patterns from this data, for example for promotions, cross-selling or fraud detection. The key challenge is how these findings can be integrated from historical data into new transactions in real time to make customers happy, increase revenue or prevent fraud.
"Fast Data" via stream processing is the solution to embed patterns - which were obtained from analyzing historical data - into future transactions in real-time. This session uses several real world success stories to explain the concepts behind stream processing and its relation to Hadoop and other big data platforms. The session discusses how patterns and statistical models of R, Spark MLlib and other technologies can be integrated into real-time processing using open source frameworks (such as Apache Storm, Spark or Flink) or products (such as IBM InfoSphere Streams or TIBCO StreamBase). A live demo shows the complete development lifecycle combining analytics, machine learning and stream processing.
Elastic @ Adobe: Making Search Smarter with Machine Learning at ScaleElasticsearch
Hear how Adobe scales, manages multiple use cases, and puts machine learning features to work with Elastic and learn about extensions to Elasticsearch that allow them to search at scale natively.
Intelligent Production: Deploying IoT and cloud-based machine learning to opt...Amazon Web Services
Alex Robart, CEO of Ambyint, presents their AI-driven production optimization platform for the Oil and Gas Industry.
Their IoT-based innovative hardware and software solution, delivers a revolutionary approach to monitoring Oil and Gas production operations, by updating traditional SCADA-based telemetry, cloud-enabling them, and bringing in Artificial Intelligence capabilities. Presented at the AWS Oil and Gas Industry Day in Calgary, 2017.
How eStruxture Data Centers is Using ECE to Rapidly Scale Their BusinessElasticsearch
See how Elastic is helping eStruxture unify millions of divergent data points, transforming them into human readable and actionable items, and helping eStruxture build a new model for alarming and alerting. Watch video: https://www.elastic.co/elasticon/tour/2019/toronto/how-estruxture-data-centers-is-using-ece-to-rapidly-scale-their-business
Complex event processing platform handling millions of users - Krzysztof Zarz...GetInData
If you want to learn more about it, check out our webinar here: https://www.youtube.com/watch?v=EfGPY_NyYQ8&t=77s
The webinar was organized by GetinData on 2020. During the webinar, we shared our lessons learnt from building and running stream processing platform in production for over 2 years.
Watch more here: https://www.youtube.com/watch?v=EfGPY_NyYQ8
Author: Krzysztof Zarzycki
Linkedin: https://www.linkedin.com/in/kzarzycki/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Quantifying Genuine User Experience in Virtual Desktop EcosystemsData Con LA
Data Con LA 2020
When users complain about slowness in their virtual application or desktop, User Experience becomes a subjective measurement, or a feeling of how well the infrastructure is performing. This talk will focus on the objective measurement and what that looks like for your business.
Takeaways:
*Attendees will learn the method for monitoring User Experience for virtual apps and desktops.
*Attendees will learn the do's and don'ts of monitoring for User Experience in the virtual world.
*Attendees will gain a sense of importance of monitoring UX for their business cases when purchasing a monitoring solution like eG Enterprise.
Typical Audience:
Architects, engineers, managers, end-user solutions experts that work in the virtual desktop space such as Citrix, Horizon, DaaS, and more.
Speaker
Wendy Howard, Eg Innovations, Technical Consultant
IIoT + Predictive Analytics: Solving for Disruption in Oil & Gas and Energy &...DataWorks Summit
The electric grid has evolved from linear generation and delivery to a complex mix of renewables, prosumer-generated electricity, and electric vehicles (EVs). Smart meters are generating loads of data. As a result, traditional forecasting models and technologies can no longer adequately predict supply and demand. Extreme weather, an aging infrastructure, and the burgeoning worldwide population are also contributing to increased outage frequency.
In oil and gas, commodity pricing pressures, resulting workforce reductions, and the need to reduce failures, automate workflows, and increase operational efficiencies are driving operators to shift analytics initiatives to advanced data-driven applications to complement physics-based tools.
While sensored equipment and legacy surveillance applications are generating massive amounts of data, just 2% is understood and being leveraged. Operationalizing it along with external datasets enables a shift from time-based to condition-based maintenance, better forecasting and dramatic reductions in unplanned downtime.
The session includes plenty of real-world anecdotes. For example, how an electric power holding company reduced the time it took to investigate energy theft from six months to less than one hour, producing theft leads in minutes and an expected multi-million dollar ROI. How a global offshore contract drilling services provider implemented an open source IIoT solution across its fleet of assets in less than a year, enabling remote monitoring, predictive analytics and maintenance.
Key takeaways:
• How are new processes for data collection, storage and democratization making it accessible and usable at scale?
• Beyond time series data, what other data types are important to assess?
• What advantage are open source technologies providing to enterprises deploying IIoT?
• Why is collaboration important across industrial verticals to increase IIoT open source adoption?
Speaker
Kenneth Smith, General Manager, Energy, Hortonworks
Real-time Streaming Analytics: Business Value, Use Cases and Architectural Co...Impetus Technologies
Impetus webcast ‘Real-time Streaming Analytics: Business Value, Use Cases and Architectural Considerations’ available at http://bit.ly/1i6OrwR
The webinar talks about-
• How business value is preserved and enhanced using Real-time Streaming Analytics with numerous use-cases in different industry verticals
• Technical considerations for IT leaders and implementation teams looking to integrate Real-time Streaming Analytics into enterprise architecture roadmap
• Recommendations for making Real-time Streaming Analytics – real – in your enterprise
• Impetus StreamAnalytix – an enterprise ready platform for Real-time Streaming Analytics
A presentation pertaining to the integration of real-time data to the cloud with significant potential in the areas of Industrial IT,Real-time sensor information processing and Smart grids applied to various vertical industries. This is related to my blog post at www.cloudshoring.in
Industrial IoT is currently transforming how businesses capitalize their big data. Changes in how business is done, combined with multiple technology drivers make geo-distributed data increasingly important for enterprises. These changes are causing serious disruption across a wide range of industries.
Platform for the Research and Analysis of Cybernetic ThreatsDataWorks Summit
This talk describes, from an architectural point of view, how to exploit the HDP + Nifi technological platform aimed at researching, exploiting and targeting events related to Cyber Security. The purpose of the system is to create a knowledge base related to the events, actors and operating methods with which the cyber attacks happened and may happen, collecting both real-time data from social networks and web pages or literature material on such episodes in batch modality. The process focuses text and graph analysis at scale thanks to Spark engine Metron and Kafka, on a complexly integrated tech stack, that enhances the capabilities of the algorithms and results to offer a flexible solution to the analysts. The system supports the user in determining the motivations and eventually the actual executors of the attacks and, hopefully, the instigators of the same, also thanks to a smart representation of data stored on a graph NoSQL database. A further aim of the system will be to determine, in a predictive way, the "symptoms" or the processes connected to the attacks.
Build and Run Streaming Applications with Apache Flink and Amazon Kinesis Dat...Flink Forward
Stream processing facilitates the collection, processing, and analysis of real-time data and enables the continuous generation of insights and quick reactions to emerging situations. Yet, despite these advantages compared to traditional batch-oriented analytics applications, streaming applications are much more challenging to operate. Some of these challenges include the ability to provide and maintain low end-to-end latency, to seamlessly recover from failure, and to deal with a varying amount of throughput.
We all know and love Flink to take on those challenges with grace. In this session, we explore an end to end example that shows how you can use Apache Flink and Amazon Kinesis Data Analytics for Java Applications to build a reliable, scalable, and highly available streaming applications. We discuss how you can leverage managed services to quickly build Flink based streaming applications and show managed services can help to substantially reduce the operational overhead that is required to run the application. We also review best practices for running streaming applications with Apache Flink on AWS.
So you will not only see how to actually build streaming applications with Apache Flink on AWS, you will also learn how leveraging managed services can help to reduce the overhead that is usually required to build and operate streaming applications to a bare minimum.
Real Time Analytics: Algorithms and SystemsArun Kejariwal
In this tutorial, an in-depth overview of streaming analytics -- applications, algorithms and platforms -- landscape is presented. We walk through how the field has evolved over the last decade and then discuss the current challenges -- the impact of the other three Vs, viz., Volume, Variety and Veracity, on Big Data streaming analytics.
Speaker: Atul Kshirsagar, GE Software
To learn more about Pivotal Cloud Foundry, visit http://www.pivotal.io/platform-as-a-service/pivotal-cloud-foundry.
Make Streaming IoT Analytics Work for YouHortonworks
Download Hortonworks DataFlow (HDF™) here - http://hortonworks.com/downloads/#dataflow. Making Streaming IoT Analytics Work For You With Apache NiFi, Storm, Raspberry Pi and more.
See how the Elastic Stack enables Postbank Systems to drive transformation from monitoring bank branches and ATMs and creating an anti-fraud system, to ensuring that the Postbank Group is GDPR compliant.
Watch the video: https://www.elastic.co/elasticon/tour/2019/munich/powering-postbank-groups-data-driven-strategy
How to Apply Machine Learning with R, H20, Apache Spark MLlib or PMML to Real...Kai Wähner
"Big Data" is currently a big hype. Large amounts of historical data are stored in Hadoop or other platforms. Business Intelligence tools and statistical computing are used to draw new knowledge and to find patterns from this data, for example for promotions, cross-selling or fraud detection. The key challenge is how these findings can be integrated from historical data into new transactions in real time to make customers happy, increase revenue or prevent fraud.
"Fast Data" via stream processing is the solution to embed patterns - which were obtained from analyzing historical data - into future transactions in real-time. This session uses several real world success stories to explain the concepts behind stream processing and its relation to Hadoop and other big data platforms. The session discusses how patterns and statistical models of R, Spark MLlib and other technologies can be integrated into real-time processing using open source frameworks (such as Apache Storm, Spark or Flink) or products (such as IBM InfoSphere Streams or TIBCO StreamBase). A live demo shows the complete development lifecycle combining analytics, machine learning and stream processing.
Elastic @ Adobe: Making Search Smarter with Machine Learning at ScaleElasticsearch
Hear how Adobe scales, manages multiple use cases, and puts machine learning features to work with Elastic and learn about extensions to Elasticsearch that allow them to search at scale natively.
Intelligent Production: Deploying IoT and cloud-based machine learning to opt...Amazon Web Services
Alex Robart, CEO of Ambyint, presents their AI-driven production optimization platform for the Oil and Gas Industry.
Their IoT-based innovative hardware and software solution, delivers a revolutionary approach to monitoring Oil and Gas production operations, by updating traditional SCADA-based telemetry, cloud-enabling them, and bringing in Artificial Intelligence capabilities. Presented at the AWS Oil and Gas Industry Day in Calgary, 2017.
How eStruxture Data Centers is Using ECE to Rapidly Scale Their BusinessElasticsearch
See how Elastic is helping eStruxture unify millions of divergent data points, transforming them into human readable and actionable items, and helping eStruxture build a new model for alarming and alerting. Watch video: https://www.elastic.co/elasticon/tour/2019/toronto/how-estruxture-data-centers-is-using-ece-to-rapidly-scale-their-business
Complex event processing platform handling millions of users - Krzysztof Zarz...GetInData
If you want to learn more about it, check out our webinar here: https://www.youtube.com/watch?v=EfGPY_NyYQ8&t=77s
The webinar was organized by GetinData on 2020. During the webinar, we shared our lessons learnt from building and running stream processing platform in production for over 2 years.
Watch more here: https://www.youtube.com/watch?v=EfGPY_NyYQ8
Author: Krzysztof Zarzycki
Linkedin: https://www.linkedin.com/in/kzarzycki/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Quantifying Genuine User Experience in Virtual Desktop EcosystemsData Con LA
Data Con LA 2020
When users complain about slowness in their virtual application or desktop, User Experience becomes a subjective measurement, or a feeling of how well the infrastructure is performing. This talk will focus on the objective measurement and what that looks like for your business.
Takeaways:
*Attendees will learn the method for monitoring User Experience for virtual apps and desktops.
*Attendees will learn the do's and don'ts of monitoring for User Experience in the virtual world.
*Attendees will gain a sense of importance of monitoring UX for their business cases when purchasing a monitoring solution like eG Enterprise.
Typical Audience:
Architects, engineers, managers, end-user solutions experts that work in the virtual desktop space such as Citrix, Horizon, DaaS, and more.
Speaker
Wendy Howard, Eg Innovations, Technical Consultant
This presentation gives several examples of how commercial drones are used in industry. Originally presented at the Day of Drones, Hiller Museum of Aviation, San Carlos, California, August 27, 2016
Drones are a different kind of new technology from what we’re used to. They offer something else: the conquest of physical space, the extension of society’s compass, the ability to be anywhere and see anything.
For the past few years, one of the most exciting class of gadgets on display has been drones. They got cheaper, lighter, and easier to use even as they became more powerful.
We believe 2015 is an important year for drones as they will change how brands interact with consumers in both advertising and events, and here's everything you need to know about the drone technology.
Black Hat USA 2016 - Highway to the Danger Drone - 03Aug2016 - Slides - UPDAT...Bishop Fox
Do you feel the need… the need for speed? Then check out our brand new penetration testing drone. This Raspberry Pi based copter is both cheap and easy to create on your own, making it the first practical drone solution for your pentesting needs.
For more info, see the project page at:
https://www.bishopfox.com/resources/tools/drones-penetration-testers/attack-tools/
QAT Global is a global information technology (IT) services company providing Agile-based software development, IT consulting, technology and distributed development services. We pride ourselves in being a leader in the delivery of enterprise business solutions through the innovative use of technologies such as Enterprise Java and .NET as well as Open Source components.
QAT Global focuses on delivering business results by helping clients find ways to capitalize on change, leverage emerging technologies effectively, and out innovate competitors through collaborative engagements. The company leverages an enhanced global delivery model, innovative enterprise development framework for distributed environments, repeatable process methodology based in Agile and Scrum, multimedia communication tools, and deep industry expertise to provide high-value IT services. This approach enables its clients to improve their end user’s experience, expand market reach, improve time to market, and reduce operating costs and risks.
QAT Global serves government agencies, companies ranging from early stage startups to Global 2000 companies, and leading software vendors in Banking & Financial Services, Transportation, Insurance, Manufacturing, Utilities, Telecommunications, Information & Entertainment industries, Human Resource Management, Benefits Administration, Government, E-Commerce, and Communications & Technology.
QAT Global has extensive experience and in-depth expertise in application modernization, Business Process Management, rich internet applications, and distributed software development. The company’s service offerings include technology consulting, custom software application development and maintenance, software product engineering, systems integration, application modernization, web and mobile application development, big data and analytics, and testing services.
Founded in 1995, and headquartered in Omaha, Nebraska, QAT Global has operations in the United States and Brazil.
Verticals - Banking & Financial Services, Transportation, Insurance, Manufacturing, Utilities, Telecommunications, Software Publishing, Information & Entertainment industries, Human Resource Management, Benefits Administration, Government, E-Commerce & Ebusiness, and Communications & Technology
Clients - QAT Global serves companies ranging from early stage startups to Global 2000 companies and leading software vendors.
Offices - QAT Global is headquartered in Omaha, Nebraska. The QAT Global offshore development center is located in Uberaba, MG, Brazil.
Businesses can leverage Big Data to enhance market share and ROI with valuable insights, accelerated time-to-market and new revenue streams. Learn how TCS transforms business by leveraging Big Data for accurate business insights
Drones and the Internet of Things: realising the potential of airborne comput...Prayukth K V
This paper focuses on services and applications provided to mobile users using airborne computing infrastructure. Concepts such as drones-as-a-service and flyin,fly-out
infrastructure, and note data management and system
design issues that arise in these scenarios are discussed. Issues of Big Data arising from such applications, optimising the configuration of airborne and ground infrastructure to provide the best QoS and QoE, situation-awareness, scalability, reliability, scheduling for efficiency, interaction with users and drones using physical annotations are outlined.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-talluri
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Raj Talluri, Senior Vice President of Product Management at Qualcomm Technologies, presents the "Is Vision the New Wireless?" tutorial at the May 2016 Embedded Vision Summit.
Over the past 20 years, digital wireless communications has become an essential technology for many industries, and a primary driver for the electronics industry. Today, computer vision is showing signs of following a similar trajectory. Once used only in low-volume applications such as manufacturing inspection, vision is now becoming an essential technology for a wide range of mass-market devices, from cars to drones to mobile phones. In this presentation, Talluri examines the motivations for incorporating vision into diverse products, presents case studies that illuminate the current state of vision technology in high-volume products, and explores critical challenges to ubiquitous deployment of visual intelligence.
Drones Collaboration and IoT enabling digitalization of sensors - Angelo Fien...Codemotion
What if your surveillance drone could wake you up via a SMS in the middle of the night ? What if an interactive assistant could speak you the next CodeMotion session and give you directions ? Join this session to experience how to turn your data into engaging interactions. We'll show case an Innovative Drone demo, and an interactive Voice & Chat assistant for the CodeMotion event, then present the Cisco Spark & Tropo Cloud APIs. Want to try these by yourself ? pass by the codelabs where our technical mentors will help you ramp up and build your first Text to Speech and Bot prototypes.
Marlabs Capabilities Overview: DWBI, Analytics and Big Data ServicesMarlabs
Marlabs’ Business Intelligence and Analytics practice can support customers’ needs throughout the information management lifecycle. As a vendor-agnostic and holistic service provider with expertise in a range of tools and technologies, we can help clients make informed decisions to employ the right technologies that align with their business needs.
Serene 2015
Davide Scaramuzza
Abstract: With drones becoming more and more popular, safety is a big concern. A critical situation occurs when a drone temporarily loses its GPS position information, which might lead it to crash. This can happen, for instance, when flying close to buildings where GPS signal is lost. In such situations, it is desirable that the drone can rely on fall-back systems and regain stable flight as soon as possible. In this talk, I will present novel methods to automatically recover and stabilize a quadrotor from any initial condition or execute emergency landing. On the one hand, this new technology will allow quadrotors to be launched by simply tossing them in the air, like a “baseball ball”. On the other hand, it will allow them to recover back into stable flight or land on a safe area after a system failure. Since this technology does not rely on any external infrastructure, such as GPS, it enables the safe use of drones in both indoor and outdoor environments. Thus, it can become relevant for commercial use of drones, such as parcel delivery.
Recent videos:
Automatic failure recovery without GPS: https://youtu.be/pGU1s6Y55JI
Autonomous Landing-site detection and landing: https://youtu.be/phaBKFwfcJ4
IoT Business Disruption leading to Artifical Intelligence - IoT Evolution 2016Sudha Jamthe
Sudha Jamthe's keynote from IoT Evolution Las Vegas July 2016.
How IoT Business Disruption is leading us to the innovation from AI. She covers landscape of all AI and drills down on Machine Learning leading to Robots, Drones and Bots
Business junction of IoT and AI ebusiness 2016 thailand 17 nov 2016Sudha Jamthe
Sudha Jamthe's Talk at eBusiness 2016 at Siam Technology College, Thailand. Nov 2016. This talk will cover the business junction of IoT and AI and help you understand how to go past Machine Learning algorithms to answer questions about Algorithmic accuracy, Data Governance, Business risk buried in ownership of Intelligent Machines and Bots.
This presentation shows how drones have been used successfully in construction and infrastructure asset management as aerial image and data capture devices thus far, review competitive and traditional approaches using incumbent technology, discuss the opportunities and challenges posed by the technology itself, outline the lessons learned, and discuss what’s next for drones in civil engineering.
An APM webinar, held on 27 October 2020, presented by Tim Whitaker, Andy Huggett and Peter Brown
https://www.apm.org.uk/news/drones-in-project-management-webinar/
https://youtu.be/cZNVyG5aOrk
This brief was given to Industry by Terry Martin at Nova Systems, during the UTM Trials held in May 2017. The brief includes a selection of the slides describing the trial management activities that Nova was responsible for
Commercial Drone Best Practices: How to Incorporate Data and Job SpecsColin Snow
Drones are an exciting platform that is now emerging as a competitive technology in a number of professional surveying data collection scenarios - including mobile and airborne LiDAR. This presentation presents an overview of what to consider when adding a remotely piloted airborne photogrammetry or laser scanning system to your practice.
UAVs are a disruptive technology bringing new geographic data and information to many application domains. UASs are similar to other geographic imagery systems so existing frameworks are applicable. But the diversity of UAVs as platforms along with the diversity of available sensors are presenting challenges in the processing and creation of geospatial products. Efficient processing and dissemination of the data is achieved using software and systems that implement open standards. The challenges identified point to the need for use of existing standards and extending standards. Results from the use of the OGC Sensor Web Enablement set of standards are presented. Next steps in the progress of UAVs and UASs may follow the path of open data, open source and open standards.
A Drone project planned for implementation in an Urban environment for delivering parcels in an area using Autonomous drones which can carry upto 2Kg weight and 30 KM's flight time. This project could not move forward due to restrictions posed by the Authority in urban areas.
Drone Insights 2021, and its Impact on other sectors in IndiaKaushik Biswas
The Booming Drone Industry and its prospect by 2025. What are the sectors in which Drones can be used in India, the regulatory frameworks comparing World Vs India, What are the Top 3 companies we can do business with, who are the other players in the industry?
I have also done a small survey on what Indians think about the drone industry overall, and finally a conclusion on where we are vs the world
Presentation by Cascadian Aerial Robotics LLC about how drones are helping Construction firms with aerial inspections, Mapping, virtual walk-throughs , BIM and VDC. For more information, head to https://www.cascadianaerialrobotics.com
Raj Singh talks about the history of OGC standards such as Sensor Web Enablement Suite -- Sensor Planning Service, Sensor Observation Service, SensorML, Observation & Measurements -- and its IoT companion -- SWEforIoT, and how the geospatial industry is uniquely positioned to take leadership in the emerging Internet of Things space.
Drones and Fog Computing - New Frontiers of IoT and Digital Transformation -...Biren Gandhi
Technology is considered one of the biggest drivers of Digital Transformation and Digital Disruption. Out of many frontiers of recent technological advancements, this talk focused on IoT, Drones and Fog Computing as key innovation accelerators for Digital Strategy.
The Need for Drone Forensic Investigation Standardisation (Evangelos Mantas) ...DroneSec
Evangelos Mantas (Infili Intelligence)
Talk Recording: https://www.youtube.com/watch?v=W0ZNpj7QZtM
The Global Drone Security Network (GDSN) is the only event of its kind focusing on Cyber-UAV security, Drone Threat Intelligence, Counter-UAS, and UTM security. Watch the full recording here: https://www.youtube.com/watch?v=vZ6sRr65cSk
Speaker: https://www.linkedin.com/in/evangelos-mantas-0aa82619a/
DroneSec is a cyber-uav security and threat intelligence company who hosted this second series of the GDSN community event.
https://dronesec.com/
Commercial Drones - Technology & Industry AnalysisSudhir Manchanda
Unmanned Aerial Vehicles have long been used in armed forces. Now that they are at the cusp of commercial applications, let's get a sense of the technology, industry, leading startups and business applications that they are trying to build for!
Cloud computing is being adopted rapidly today, fueled by the explosion in mobile devices. The car is the third-fastest-growing mobile 'device'. Mandated use of the Cloud by the American government is pushing even faster growth. The shift to electric vehicles adds even more urgency. Here is a view of how the car is becoming a moving information transceiver for the Cloud...a mobile sensor that feeds the Cloud. See also some work on a First Responder Test-Bed in Canada
Many Organizations are currently processing various types of data and in different formats. Most often this data will be in free form, As the consumers of this data growing it’s imperative that this free-flowing data needs to adhere to a schema. It will help data consumers to have an expectation of about the type of data they are getting and also they will be able to avoid immediate impact if the upstream source changes its format. Having a uniform schema representation also gives the Data Pipeline a really easy way to integrate and support various systems that use different data formats.
SchemaRegistry is a central repository for storing, evolving schemas. It provides an API & tooling to help developers and users to register a schema and consume that schema without having any impact if the schema changed. Users can tag different schemas and versions, register for notifications of schema changes with versions etc.
In this talk, we will go through the need for a schema registry and schema evolution and showcase the integration with Apache NiFi, Apache Kafka, Apache Storm.
There is increasing need for large-scale recommendation systems. Typical solutions rely on periodically retrained batch algorithms, but for massive amounts of data, training a new model could take hours. This is a problem when the model needs to be more up-to-date. For example, when recommending TV programs while they are being transmitted the model should take into consideration users who watch a program at that time.
The promise of online recommendation systems is fast adaptation to changes, but methods of online machine learning from streams is commonly believed to be more restricted and hence less accurate than batch trained models. Combining batch and online learning could lead to a quickly adapting recommendation system with increased accuracy. However, designing a scalable data system for uniting batch and online recommendation algorithms is a challenging task. In this talk we present our experiences in creating such a recommendation engine with Apache Flink and Apache Spark.
DeepLearning is not just a hype - it outperforms state-of-the-art ML algorithms. One by one. In this talk we will show how DeepLearning can be used for detecting anomalies on IoT sensor data streams at high speed using DeepLearning4J on top of different BigData engines like ApacheSpark and ApacheFlink. Key in this talk is the absence of any large training corpus since we are using unsupervised machine learning - a domain current DL research threats step-motherly. As we can see in this demo LSTM networks can learn very complex system behavior - in this case data coming from a physical model simulating bearing vibration data. Once draw back of DeepLearning is that normally a very large labaled training data set is required. This is particularly interesting since we can show how unsupervised machine learning can be used in conjunction with DeepLearning - no labeled data set is necessary. We are able to detect anomalies and predict braking bearings with 10 fold confidence. All examples and all code will be made publicly available and open sources. Only open source components are used.
QE automation for large systems is a great step forward in increasing system reliability. In the big-data world, multiple components have to come together to provide end-users with business outcomes. This means, that QE Automations scenarios need to be detailed around actual use cases, cross-cutting components. The system tests potentially generate large amounts of data on a recurring basis, verifying which is a tedious job. Given the multiple levels of indirection, the false positives of actual defects are higher, and are generally wasteful.
At Hortonworks, we’ve designed and implemented Automated Log Analysis System - Mool, using Statistical Data Science and ML. Currently the work in progress has a batch data pipeline with a following ensemble ML pipeline which feeds into the recommendation engine. The system identifies the root cause of test failures, by correlating the failing test cases, with current and historical error records, to identify root cause of errors across multiple components. The system works in unsupervised mode with no perfect model/stable builds/source-code version to refer to. In addition the system provides limited recommendations to file/open past tickets and compares run-profiles with past runs.
Improving business performance is never easy! The Natixis Pack is like Rugby. Working together is key to scrum success. Our data journey would undoubtedly have been so much more difficult if we had not made the move together.
This session is the story of how ‘The Natixis Pack’ has driven change in its current IT architecture so that legacy systems can leverage some of the many components in Hortonworks Data Platform in order to improve the performance of business applications. During this session, you will hear:
• How and why the business and IT requirements originated
• How we leverage the platform to fulfill security and production requirements
• How we organize a community to:
o Guard all the players, no one gets left on the ground!
o Us the platform appropriately (Not every problem is eligible for Big Data and standard databases are not dead)
• What are the most usable, the most interesting and the most promising technologies in the Apache Hadoop community
We will finish the story of a successful rugby team with insight into the special skills needed from each player to win the match!
DETAILS
This session is part business, part technical. We will talk about infrastructure, security and project management as well as the industrial usage of Hive, HBase, Kafka, and Spark within an industrial Corporate and Investment Bank environment, framed by regulatory constraints.
HBase hast established itself as the backend for many operational and interactive use-cases, powering well-known services that support millions of users and thousands of concurrent requests. In terms of features HBase has come a long way, overing advanced options such as multi-level caching on- and off-heap, pluggable request handling, fast recovery options such as region replicas, table snapshots for data governance, tuneable write-ahead logging and so on. This talk is based on the research for the an upcoming second release of the speakers HBase book, correlated with the practical experience in medium to large HBase projects around the world. You will learn how to plan for HBase, starting with the selection of the matching use-cases, to determining the number of servers needed, leading into performance tuning options. There is no reason to be afraid of using HBase, but knowing its basic premises and technical choices will make using it much more successful. You will also learn about many of the new features of HBase up to version 1.3, and where they are applicable.
There has been an explosion of data digitising our physical world – from cameras, environmental sensors and embedded devices, right down to the phones in our pockets. Which means that, now, companies have new ways to transform their businesses – both operationally, and through their products and services – by leveraging this data and applying fresh analytical techniques to make sense of it. But are they ready? The answer is “no” in most cases.
In this session, we’ll be discussing the challenges facing companies trying to embrace the Analytics of Things, and how Teradata has helped customers work through and turn those challenges to their advantage.
In this talk, we will present a new distribution of Hadoop, Hops, that can scale the Hadoop Filesystem (HDFS) by 16X, from 70K ops/s to 1.2 million ops/s on Spotiy's industrial Hadoop workload. Hops is an open-source distribution of Apache Hadoop that supports distributed metadata for HSFS (HopsFS) and the ResourceManager in Apache YARN. HopsFS is the first production-grade distributed hierarchical filesystem to store its metadata normalized in an in-memory, shared nothing database. For YARN, we will discuss optimizations that enable 2X throughput increases for the Capacity scheduler, enabling scalability to clusters with >20K nodes. We will discuss the journey of how we reached this milestone, discussing some of the challenges involved in efficiently and safely mapping hierarchical filesystem metadata state and operations onto a shared-nothing, in-memory database. We will also discuss the key database features needed for extreme scaling, such as multi-partition transactions, partition-pruned index scans, distribution-aware transactions, and the streaming changelog API. Hops (www.hops.io) is Apache-licensed open-source and supports a pluggable database backend for distributed metadata, although it currently only support MySQL Cluster as a backend. Hops opens up the potential for new directions for Hadoop when metadata is available for tinkering in a mature relational database.
In high-risk manufacturing industries, regulatory bodies stipulate continuous monitoring and documentation of critical product attributes and process parameters. On the other hand, sensor data coming from production processes can be used to gain deeper insights into optimization potentials. By establishing a central production data lake based on Hadoop and using Talend Data Fabric as a basis for a unified architecture, the German pharmaceutical company HERMES Arzneimittel was able to cater to compliance requirements as well as unlock new business opportunities, enabling use cases like predictive maintenance, predictive quality assurance or open world analytics. Learn how the Talend Data Fabric enabled HERMES Arzneimittel to become data-driven and transform Big Data projects from challenging, hard to maintain hand-coding jobs to repeatable, future-proof integration designs.
Talend Data Fabric combines Talend products into a common set of powerful, easy-to-use tools for any integration style: real-time or batch, big data or master data management, on-premises or in the cloud.
While you could be tempted assuming data is already safe in a single Hadoop cluster, in practice you have to plan for more. Questions like: "What happens if the entire datacenter fails?, or "How do I recover into a consistent state of data, so that applications can continue to run?" are not a all trivial to answer for Hadoop. Did you know that HDFS snapshots are handling open files not as immutable? Or that HBase snapshots are executed asynchronously across servers and therefore cannot guarantee atomicity for cross region updates (which includes tables)? There is no unified and coherent data backup strategy, nor is there tooling available for many of the included components to build such a strategy. The Hadoop distributions largely avoid this topic as most customers are still in the "single use-case" or PoC phase, where data governance as far as backup and disaster recovery (BDR) is concerned are not (yet) important. This talk first is introducing you to the overarching issue and difficulties of backup and data safety, looking at each of the many components in Hadoop, including HDFS, HBase, YARN, Oozie, the management components and so on, to finally show you a viable approach using built-in tools. You will also learn not to take this topic lightheartedly and what is needed to implement and guarantee a continuous operation of Hadoop cluster based solutions.
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.
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.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
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/
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.
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.
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
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
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/
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.