Janus graph lookingbackwardreachingforwardDemai Ni
JanusGraph: Looking Backward and Reaching Forward - by Jason Plurad (@pluradj):
The JanusGraph project started at the Linux Foundation earlier this year, but it is not the new kid on the block. We'll start with a look at the origins and evolution of this open source graph database through the lens of a few IBM graph use cases. We'll discuss the new features in latest release of JanusGraph, and then take a look at future directions to explore together with the open community.
The slides from my talk at the February 2011 Multipack Presents Show & Tell event. In this presentation I talked about how Big Data is a challenge to deal with, considered some of the problems and discussed how to deal with them
State of Play. Data Science on Hadoop in 2015 by SEAN OWEN at Big Data Spain ...Big Data Spain
http://www.bigdataspain.org/2014/conference/state-of-play-data-science-on-hadoop-in-2015-keynote
Machine Learning is not new. Big Machine Learning is qualitatively different: More data beats algorithm improvement, scale trumps noise and sample size effects, can brute-force manual tasks.
Session presented at Big Data Spain 2014 Conference
18th Nov 2014
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Slides: https://speakerdeck.com/bigdataspain/state-of-play-data-science-on-hadoop-in-2015-by-sean-owen-at-big-data-spain-2014
Virtualizing Analytics with Apache Spark: Keynote by Arsalan Tavakoli Spark Summit
In the race to invent multi-million dollar business opportunities with exclusive insights, data scientists and engineers are hampered by a multitude of challenges just to make one use case a reality – the need to ingest data from multiple sources, apply real-time analytics, build machine learning algorithms, and intermix different data processing models, all while navigating around their legacy data infrastructure that is just not up to the task. This need has created the demand for Virtual Analytics, where the complexities of disparate data and technology silos have been abstracted away, coupled with a powerful range of analytics and processing horsepower, all in one unified data platform. This talk describes how Databricks is powering this revolutionary new trend with Apache Spark.
My talk from Database Camp 2016 at the United Nations. I focus on how we can bridge the gap between OLTP and OLAP workloads and discuss a very promising new technology called Apache Kudu.
Janus graph lookingbackwardreachingforwardDemai Ni
JanusGraph: Looking Backward and Reaching Forward - by Jason Plurad (@pluradj):
The JanusGraph project started at the Linux Foundation earlier this year, but it is not the new kid on the block. We'll start with a look at the origins and evolution of this open source graph database through the lens of a few IBM graph use cases. We'll discuss the new features in latest release of JanusGraph, and then take a look at future directions to explore together with the open community.
The slides from my talk at the February 2011 Multipack Presents Show & Tell event. In this presentation I talked about how Big Data is a challenge to deal with, considered some of the problems and discussed how to deal with them
State of Play. Data Science on Hadoop in 2015 by SEAN OWEN at Big Data Spain ...Big Data Spain
http://www.bigdataspain.org/2014/conference/state-of-play-data-science-on-hadoop-in-2015-keynote
Machine Learning is not new. Big Machine Learning is qualitatively different: More data beats algorithm improvement, scale trumps noise and sample size effects, can brute-force manual tasks.
Session presented at Big Data Spain 2014 Conference
18th Nov 2014
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Slides: https://speakerdeck.com/bigdataspain/state-of-play-data-science-on-hadoop-in-2015-by-sean-owen-at-big-data-spain-2014
Virtualizing Analytics with Apache Spark: Keynote by Arsalan Tavakoli Spark Summit
In the race to invent multi-million dollar business opportunities with exclusive insights, data scientists and engineers are hampered by a multitude of challenges just to make one use case a reality – the need to ingest data from multiple sources, apply real-time analytics, build machine learning algorithms, and intermix different data processing models, all while navigating around their legacy data infrastructure that is just not up to the task. This need has created the demand for Virtual Analytics, where the complexities of disparate data and technology silos have been abstracted away, coupled with a powerful range of analytics and processing horsepower, all in one unified data platform. This talk describes how Databricks is powering this revolutionary new trend with Apache Spark.
My talk from Database Camp 2016 at the United Nations. I focus on how we can bridge the gap between OLTP and OLAP workloads and discuss a very promising new technology called Apache Kudu.
Zillow's favorite big data & machine learning toolsnjstevens
This talk covers Zillow's favorite tools for keeping track of research, cluster computing, machine learning open source, workflow management, logging, deep learning and data storage
Preview - Massive Scale Content at Re:Invent 2015John Newton
Amazon Aurora enables the Alfresco Content Management System to store, manage, and retrieve billions of documents and related information with fast and linear scalability. Using the recently launched Aurora database, Alfresco can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications.
This session addresses the use cases and challenges of scaling document repositories and using Aurora, Solr, Amazon EBS, and Amazon S3. The result are new solutions that can now be handled cost-effectively with AWS and Aurora.
Learn more at Re:Invent 2015 – Las Vegas
DAT309 10/8/15 (Thursday) 1:30 PM - San Polo 3501B
Slides for the talk at AI in Production meetup:
https://www.meetup.com/LearnDataScience/events/255723555/
Abstract: Demystifying Data Engineering
With recent progress in the fields of big data analytics and machine learning, Data Engineering is an emerging discipline which is not well-defined and often poorly understood.
In this talk, we aim to explain Data Engineering, its role in Data Science, the difference between a Data Scientist and a Data Engineer, the role of a Data Engineer and common concepts as well as commonly misunderstood ones found in Data Engineering. Toward the end of the talk, we will examine a typical Data Analytics system architecture.
(ADV303) MediaMath’s Data Revolution with Amazon Kinesis and Amazon EMR | AWS...Amazon Web Services
Collecting and processing terabytes of data per day is a challenge for any technology company. As marketers and brands become more sophisticated consumers of data, enabling granular levels of access to targeted subsets of data from outside your firewalls presents new challenges. This session discusses how to build scalable, complex, and cost-effective data processing pipelines using Amazon Kinesis, Amazon EC2 Spot Instances, Amazon EMR, and Amazon Simple Storage Service (S3). Learn how MediaMath revolutionized their data delivery platform with the help of these services to empower product teams, partners, and clients. As a result, a number of innovative products and services are delivered on top of terabytes of online user behavior. MediaMath covers their journey from legacy batch processing and vendor lock-in to a new world where the raw materials to build advanced lookalike models, optimization algorithms, or marketing attribution models are readily available to any engineering team in real time, substantially reducing the time - and cost - of innovation.
Global Knowledge Collaboration to Cure Cancer: How GPUs Impact Graph & Predictive Analytics
Brad Bebee, CEO of Blazegraph
Video of this session at the Database Camp conference at the UN is on http://www.Database.Camp
Netflix Data Engineering @ Uber Engineering MeetupBlake Irvine
People, Platform, Projects: these slides overview how Netflix works with Big Data. I share how our teams are organized, the roles we typically have on the teams, an overview of our Big Data Platform, and two example projects.
Database Camp 2016 @ United Nations, NYC - Michael Glukhovsky, Co-Founder, Re...✔ Eric David Benari, PMP
Advancing Real-Time Responses in Web Applications
Michael Glukhovsky, Co-Founder, RethinkDB
Video of this session at the Database Camp conference at the UN is on http://www.Database.Camp
I have presented on AWS Big Data Analytics technologies and discussed on how AWS provides a big data platform that allows you to collect, store, and analyze data, how to use AWS services for Data Streaming and Big Data along with some demos on how to build big data solutions using Amazon EMR and Amazon Redshift in a step-by-step manner.
Data Visualisation with Hadoop Mashups, Hive, Power BI and Excel 2013Jen Stirrup
This session focused on data visualisation using Power BI, based on big data. Some examples of Hive and HDFS file storage are given. An overview of Microsoft HDInsight is supplied.
How to boost your datamanagement with Dremio ?Vincent Terrasi
Works with any source. Relational, non-relational, 3rd party apps. 5 years ago nobody was using Hadoop, MongoDB, and 5 years from now there will be new products. You need a solution that is future proof.
Works with any BI tool. In every company multiple tools are in use. Each department has their favorite. We need to work with all of them.
No ETL, data warehouse, cubes. This would need to give you a really good alternative to these options.
Makes data self-service, collaborative. Probably most important of all, we need to change the dynamic between the business and IT. We need to make it so business users can get the data they want, in the shape they want it, without waiting on IT.
Makes Big Data feels small. It needs to make billions of rows feel like a spreadsheet on your desktop.
Open source. It’s 2017, so we think this has to be open source.
Zillow's favorite big data & machine learning toolsnjstevens
This talk covers Zillow's favorite tools for keeping track of research, cluster computing, machine learning open source, workflow management, logging, deep learning and data storage
Preview - Massive Scale Content at Re:Invent 2015John Newton
Amazon Aurora enables the Alfresco Content Management System to store, manage, and retrieve billions of documents and related information with fast and linear scalability. Using the recently launched Aurora database, Alfresco can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications.
This session addresses the use cases and challenges of scaling document repositories and using Aurora, Solr, Amazon EBS, and Amazon S3. The result are new solutions that can now be handled cost-effectively with AWS and Aurora.
Learn more at Re:Invent 2015 – Las Vegas
DAT309 10/8/15 (Thursday) 1:30 PM - San Polo 3501B
Slides for the talk at AI in Production meetup:
https://www.meetup.com/LearnDataScience/events/255723555/
Abstract: Demystifying Data Engineering
With recent progress in the fields of big data analytics and machine learning, Data Engineering is an emerging discipline which is not well-defined and often poorly understood.
In this talk, we aim to explain Data Engineering, its role in Data Science, the difference between a Data Scientist and a Data Engineer, the role of a Data Engineer and common concepts as well as commonly misunderstood ones found in Data Engineering. Toward the end of the talk, we will examine a typical Data Analytics system architecture.
(ADV303) MediaMath’s Data Revolution with Amazon Kinesis and Amazon EMR | AWS...Amazon Web Services
Collecting and processing terabytes of data per day is a challenge for any technology company. As marketers and brands become more sophisticated consumers of data, enabling granular levels of access to targeted subsets of data from outside your firewalls presents new challenges. This session discusses how to build scalable, complex, and cost-effective data processing pipelines using Amazon Kinesis, Amazon EC2 Spot Instances, Amazon EMR, and Amazon Simple Storage Service (S3). Learn how MediaMath revolutionized their data delivery platform with the help of these services to empower product teams, partners, and clients. As a result, a number of innovative products and services are delivered on top of terabytes of online user behavior. MediaMath covers their journey from legacy batch processing and vendor lock-in to a new world where the raw materials to build advanced lookalike models, optimization algorithms, or marketing attribution models are readily available to any engineering team in real time, substantially reducing the time - and cost - of innovation.
Global Knowledge Collaboration to Cure Cancer: How GPUs Impact Graph & Predictive Analytics
Brad Bebee, CEO of Blazegraph
Video of this session at the Database Camp conference at the UN is on http://www.Database.Camp
Netflix Data Engineering @ Uber Engineering MeetupBlake Irvine
People, Platform, Projects: these slides overview how Netflix works with Big Data. I share how our teams are organized, the roles we typically have on the teams, an overview of our Big Data Platform, and two example projects.
Database Camp 2016 @ United Nations, NYC - Michael Glukhovsky, Co-Founder, Re...✔ Eric David Benari, PMP
Advancing Real-Time Responses in Web Applications
Michael Glukhovsky, Co-Founder, RethinkDB
Video of this session at the Database Camp conference at the UN is on http://www.Database.Camp
I have presented on AWS Big Data Analytics technologies and discussed on how AWS provides a big data platform that allows you to collect, store, and analyze data, how to use AWS services for Data Streaming and Big Data along with some demos on how to build big data solutions using Amazon EMR and Amazon Redshift in a step-by-step manner.
Data Visualisation with Hadoop Mashups, Hive, Power BI and Excel 2013Jen Stirrup
This session focused on data visualisation using Power BI, based on big data. Some examples of Hive and HDFS file storage are given. An overview of Microsoft HDInsight is supplied.
How to boost your datamanagement with Dremio ?Vincent Terrasi
Works with any source. Relational, non-relational, 3rd party apps. 5 years ago nobody was using Hadoop, MongoDB, and 5 years from now there will be new products. You need a solution that is future proof.
Works with any BI tool. In every company multiple tools are in use. Each department has their favorite. We need to work with all of them.
No ETL, data warehouse, cubes. This would need to give you a really good alternative to these options.
Makes data self-service, collaborative. Probably most important of all, we need to change the dynamic between the business and IT. We need to make it so business users can get the data they want, in the shape they want it, without waiting on IT.
Makes Big Data feels small. It needs to make billions of rows feel like a spreadsheet on your desktop.
Open source. It’s 2017, so we think this has to be open source.
5 Things that Make Hadoop a Game Changer
Webinar by Elliott Cordo, Caserta Concepts
There is much hype and mystery surrounding Hadoop's role in analytic architecture. In this webinar, Elliott presented, in detail, the services and concepts that makes Hadoop a truly unique solution - a game changer for the enterprise. He talked about the real benefits of a distributed file system, the multi workload processing capabilities enabled by YARN, and the 3 other important things you need to know about Hadoop.
To access the recorded webinar, visit the event site: https://www.brighttalk.com/webcast/9061/131029
For more information the services and solutions that Caserta Concepts offers, please visit http://casertaconcepts.com/
Big Data Open Source Tools and Trends: Enable Real-Time Business Intelligence...Perficient, Inc.
Most organizations still rely on batch and offline processing of data streams to gain meaningful analysis and insight into their business. However, in our instant gratification world, real-time computation and analysis of streaming data is crucial in gaining insight into patterns and threats. A trend is emerging for real-time and instant analysis from live data streams, promoting the value of logs and a move toward functional programming.
This shift in technology is not about what and how to store the data, but what we can do with it to see emerging patterns and trends across multiple resources, applications, services and environments. Log data represents a wealth of information, yet is often sporadic, unstructured, scattered across the enterprise and difficult to track.
These slides provide insights into some of the most helpful Big Data tools used by the largest social media and data-centric organizations for competitive trends, instant analysis and feedback from large volume data streams. We show how how using Big Data tools Storm, ElasticSearch and an elastic UI can turn application logs into real-time analytical views.
You will also learn how Big Data:
Contains data that is elastic, minimally structured, flexible and scalable
Helps process live streams into meaningful data
Promotes a move toward functional programming
Effects the enterprise data architecture
Works with real-time CEP tools like Storm for functional programming
Assessing New Databases– Translytical Use CasesDATAVERSITY
Organizations run their day-in-and-day-out businesses with transactional applications and databases. On the other hand, organizations glean insights and make critical decisions using analytical databases and business intelligence tools.
The transactional workloads are relegated to database engines designed and tuned for transactional high throughput. Meanwhile, the big data generated by all the transactions require analytics platforms to load, store, and analyze volumes of data at high speed, providing timely insights to businesses.
Thus, in conventional information architectures, this requires two different database architectures and platforms: online transactional processing (OLTP) platforms to handle transactional workloads and online analytical processing (OLAP) engines to perform analytics and reporting.
Today, a particular focus and interest of operational analytics includes streaming data ingest and analysis in real time. Some refer to operational analytics as hybrid transaction/analytical processing (HTAP), translytical, or hybrid operational analytic processing (HOAP). We’ll address if this model is a way to create efficiencies in our environments.
The Data Lake and Getting Buisnesses the Big Data Insights They NeedDunn Solutions Group
Do terms like "Data Lake" confuse you? You’re not alone. With all of the technology buzzwords flying around today, it can become a task to keep up with and clearly understand each of them. However a data lake is definitely something to dedicate the time to understand. Leveraging data lake technology, companies are finally able to keep all of their disparate information and streams of data in one secure location ready for consumption at any time – this includes structured, unstructured, and semi-structured data. For more information on our Big Data Consulting Services, don’t hesitate to visit us online at: http://bit.ly/2fvV5rR
Lessons learnt - building a data lake with redshift, emr, and athena - aws co...AWSCOMSUM
We’ve been running a mix of Redshift, EMR, Glue and Athena for data processing and analysis for several years, and have learnt a lot along the way. In this talk, I’ll cover some of the highlights and lowlights of running data warehouses on AWS, and where we’ve found the right tool for each task.
See the full talk on here:
https://youtu.be/RsPWfAGVGF8
Big Data with Hadoop and HDInsight. This is an intro to the technology. If you are new to BigData or just heard of it. This presentation help you to know just little bit more about the technology.
Structure 2014 - The strategic value of the cloud - Joe WeinmanGigaom
Presentation from Gigaom's Structure 2014 conference, June 21-22 in San Francisco
The strategic value of the cloud
Joe Weinman, Author, Cloudonomics
Chairman, IEEE Intercloud Testbed Executive Committee
#gigaomlive
More at http://events.gigaom.com/structure-2014/
Structure 2014 - The right and wrong way to scale - RackspaceGigaom
Presentation from Gigaom's Structure 2014 conference, June 21-22 in San Francisco
The right and wrong way to scale
Taylor Rhodes, CEO, Rackspace
#gigaomlive
More at http://events.gigaom.com/structure-2014/
Structure 2014 - The future of cloud computing survey resultsGigaom
Presentation from Gigaom's Structure 2014 conference, June 21-22 in San Francisco
The future of cloud computing survey results
#gigaomlive
More at http://events.gigaom.com/structure-2014/
Gigaom's Structure 2014 conference, June 21-22 in San Francisco Launchpad company profiles
#gigaomlive
More at http://events.gigaom.com/structure-2014/
Structure 2014 - Disrupting the data center - Intel sponsor workshopGigaom
Presentation from Gigaom's Structure 2014 conference, June 21-22 in San Francisco
Intel sponsor workshop: Disrupting the data center
#gigaomlive
More at http://events.gigaom.com/structure-2014/
Presentation from Gigaom's Structure 2014 conference, June 21-22 in San Francisco
Quantifying the iot
Craig Labovitz, Co-Founder and CEO, DeepField
#gigaomlive
More at http://events.gigaom.com/structure-2014/
25 Favorite Experiences in Tech - from Roadmap 2013Gigaom
Presentation from
Shoshana Berger, IDEO
Josh Brewer, Twitter
Ryan Freitas, about.me
Julie Horvath, GitHub
Braden Kowitz, Google Ventures
#roadmap2013
More at http://events.gigaom.com/roadmap-2013/
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.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
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.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
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
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/
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
4. Eventbrite by the Numbers
1.5 million events
80 million tickets sold
$1 billion in gross ticket sales
Events in 179 countries
Monday, April 1, 13
5. Who am I?
Director of Data Engineering at Eventbrite
Infrastructure, Data Science, Analytics, Spam and Fraud
linkedin.com/in/vipulsharma3
@vipulsharma
vipul@eventbrite.com
Monday, April 1, 13
6. Real Time
• Definition of real time varies with use case
• Real time at scale is a challenge
• Active learning requires real time data processing
• Spam/Fraud
• Discovery
• Search
• Analytics
• Real time analytics
• Data Changes
• Changes in inventory, user settings etc
Monday, April 1, 13
7. Scaling for Growth
• Decouple Services
• Decouple services based on CAP, Size and Growth
• NoSQL attractive for out of the box sharding, replication and multi data
center support along with high write speeds
• Multiple data stores pose a challenges of data flow between services in real
time
• Batch Processing
• Batch processing for big data e.g. data science, analytics etc
• MapReduce is not built for real time
• Data locality requires data to be stored on HDFS
• Data Sync to Hadoop in real time is a challenge
Monday, April 1, 13
9. Challenges with Real Time
• Data Flow
• How to transfer data captured in logs to services in real
time
• How to transfer data captured in database to services in
real time
• Data Processing
• How to process significant data in real time
• Distributed data processing for real time
Monday, April 1, 13
10. Data Flow
• Database polling
• Rather than each application polling build a single polling service
• Downstream applications polls from this service
• Built for consistency and read scalability
• Example: Event Cache
• Excited about Linkedin’s Databus - http://data.linkedin.com/projects/
databus
• Persisted Queues
• Transfer logs via a distributed persisted message queue
• Downstream applications subscribe to these queues getting a stream of
data
• Example: Firehose
• Excited about Linkedin’s Kafka - http://kafka.apache.org/index.html
Monday, April 1, 13
11. Data Processing
• Denormalization
• Write data ready to serve
• NoSQL built for Denormalization
• Example: See who’s visiting
• Distributed Data Processing
• Complex business logic needs more than de-normalization
• Example: API stats using Storm
• http://storm-project.net/
Monday, April 1, 13
12. Questions?
See it in action. Download our app:
eventbrite.com/eventbriteapp
Monday, April 1, 13
13. Thank You!
@vipulsharma/ vipul@eventbrite.com
Monday, April 1, 13