This document provides an overview of Revolution R Enterprise for IBM Netezza, a high-performance in-database analytics platform. It discusses how Revolution R leverages the massively parallel processing of Netezza to deliver faster analytics. Key features highlighted include running R code and advanced statistical models directly on Netezza clusters, accessing over 2,500 R packages, and integrating with front-end applications through web services. The document also demonstrates how to deploy Revolution R on Netezza through examples of predictive modeling tasks like decision trees and Naive Bayes classification.
Join CIGNEX Datamatics, Alfresco's Global Platinum Partner, as they share the case study experience of a leading supplier of auto parts, regarding their implementation of Alfresco as a Contract Lifecycle Management solution. The webinar will feature information related to the business drivers, challenges and solution architecture and also include a live demonstration.
Extending open source and hybrid cloud to drive OT transformation - Future Oi...John Archer
A look at ESG concerns and agility needed to address pressures to transform energy organizations with decarbonization. Presented to Future Oil and Gas conference November 2021
Showcasing exemplary stories of success where channel partners have gone to great lengths to implement innovative solutions. Acclaiming those partners who have risen to the challenges of the digital era and transformed their business to a solutions offering. Inspiring channel businesses to become value-added providers and trusted allies to their customers. Stories that made a Difference.
Key stories of the edition are as below:
1. FUELING GROWTH - CDW Middle East & Africa
2. NEW FRONTIERS- EmaxIT International
3. LAYING THE FOUNDATION - Innovative Incorporation
Trading
4. CRITICAL CONNECTIONS- Visiontech Systems International
5. THE BIG PICTURE - BMB Group
6. THE LAST LINE OF DEFENSE - Maxbyte Technologies
7. BANKING ON THE FUTURE - ConSol Enterprising IT
8. TOP GRADE - Cloud Box Technologies
9. EAGLE EYE - Fox Data Dubai
10.SECURE GATEWAYS - Virus Rescuers
Leveraging Digital Content Services to Increase Customer Lifetime Valuenewbaymarketing
Major industry trends such as the explosion of user generated content, access to and delivery of premium content, cloud-based storage, device innovation, ubiquitous broadband connectivity and social networking, are all converging – creating an opportunity for new digital content experiences. By taking the right approach, operators and device makers can deliver a lifetime of digital content experiences, creating compelling, digital content service offerings that extend the customer relationship beyond the handset.
During this webinar, Steve French, VP Global Marketing at NewBay, will explore:
- Convergence of industry trends and what this means for traditional telecom players like operators and device makers
- Defining the new user content ecosystem
- Understanding the various digital content services
- New players and their business models
- Monetizing user content services
This presentation helps you understand how you can setup a fast, easy and effective employee referral program using the wisestep.com platform. Use it to believe it !
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Mr Đoàn Hưng Thái
101B4 Nam Thành Công, Láng Hạ, Đống Đa
Hà Nội
094.334.1688 - 093.727.1688
Web: http://www.xenanghanghyundai.net/
Join CIGNEX Datamatics, Alfresco's Global Platinum Partner, as they share the case study experience of a leading supplier of auto parts, regarding their implementation of Alfresco as a Contract Lifecycle Management solution. The webinar will feature information related to the business drivers, challenges and solution architecture and also include a live demonstration.
Extending open source and hybrid cloud to drive OT transformation - Future Oi...John Archer
A look at ESG concerns and agility needed to address pressures to transform energy organizations with decarbonization. Presented to Future Oil and Gas conference November 2021
Showcasing exemplary stories of success where channel partners have gone to great lengths to implement innovative solutions. Acclaiming those partners who have risen to the challenges of the digital era and transformed their business to a solutions offering. Inspiring channel businesses to become value-added providers and trusted allies to their customers. Stories that made a Difference.
Key stories of the edition are as below:
1. FUELING GROWTH - CDW Middle East & Africa
2. NEW FRONTIERS- EmaxIT International
3. LAYING THE FOUNDATION - Innovative Incorporation
Trading
4. CRITICAL CONNECTIONS- Visiontech Systems International
5. THE BIG PICTURE - BMB Group
6. THE LAST LINE OF DEFENSE - Maxbyte Technologies
7. BANKING ON THE FUTURE - ConSol Enterprising IT
8. TOP GRADE - Cloud Box Technologies
9. EAGLE EYE - Fox Data Dubai
10.SECURE GATEWAYS - Virus Rescuers
Leveraging Digital Content Services to Increase Customer Lifetime Valuenewbaymarketing
Major industry trends such as the explosion of user generated content, access to and delivery of premium content, cloud-based storage, device innovation, ubiquitous broadband connectivity and social networking, are all converging – creating an opportunity for new digital content experiences. By taking the right approach, operators and device makers can deliver a lifetime of digital content experiences, creating compelling, digital content service offerings that extend the customer relationship beyond the handset.
During this webinar, Steve French, VP Global Marketing at NewBay, will explore:
- Convergence of industry trends and what this means for traditional telecom players like operators and device makers
- Defining the new user content ecosystem
- Understanding the various digital content services
- New players and their business models
- Monetizing user content services
This presentation helps you understand how you can setup a fast, easy and effective employee referral program using the wisestep.com platform. Use it to believe it !
xe nâng Hyundai động cơ xăng LPG tải trọng 2,5 tới 3 tấn model 25LC/30LC - 7A
Mr Đoàn Hưng Thái
101B4 Nam Thành Công, Láng Hạ, Đống Đa
Hà Nội
094.334.1688 - 093.727.1688
Web: http://www.xenanghanghyundai.net/
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In this presentation from Revolution Analytics, Bill Jacobs presents: Are You Ready for Big Data Analytics?
"Revolution Analytics delivers advanced analytics software at half the cost of existing solutions. By building on open source R—the world's most powerful statistics software—with innovations in big data analysis, integration and user experience, Revolution Analytics meets the demands and requirements of modern data-driven businesses."
Learn more: http://www.revolutionanalytics.com
Watch the presentation video: http://wp.me/p3RLEV-12S
100% R and More: Plus What's New in Revolution R Enterprise 6.0Revolution Analytics
R users already know why the R language is the lingua franca of statisticians today: because it's the most powerful statistical language in the world. Revolution Analytics builds on the power of open source R, and adds performance, productivity and integration features to create Revolution R Enterprise. In this webinar, author and blogger David Smith will introduce the additional capabilities of Revolution R Enterprise.
VP of Product Development, Dr. Sue Ranney will also provide an overview of the features introduced in Revolution R Enterprise 6.0 including:
1. Big Data Generalized Linear Model, the new RevoScaleR function that provides a fast, scalable, distributable implementation of generalized linear models, offering impressive speed-ups relative to glm on in-memory data frames
2. Platform LSF Cluster Support, which allows you to create a distributed compute context for the Platform LSF workload manager
3. Azure Burst support added to RxHpcServer
4. Updated R engine (R 2.14.2)
5. Ability to use RevoScaleR analysis functions with non-xdf data sources such as SAS, SPSS or text
6. New methods for RxXdfData data sources including head, tail, names, dim, colnames, length, str, and formula
7. New function rxRoc for generating ROC curves
Learn about IBM's Hadoop offering called BigInsights. We will look at the new features in version 4 (including a discussion on the Open Data Platform), review a couple of customer examples, talk about the overall offering and differentiators, and then provide a brief demonstration on how to get started quickly by creating a new cloud instance, uploading data, and generating a visualization using the built-in spreadsheet tooling called BigSheets.
Big data analytics on teradata with revolution r enterprise bill jacobsBill Jacobs
Revolution Analytics brings big data analytics to Teradata database. Presentation from Teradata Partners, October 2013 overviewing Revolution R Enterprise for Teradata by Bill Jacobs, Director, Product Marketing, Revolution Analytics.
About ActuateOne for Utility Analytics
Water and Energy Utilities are under tremendous pressure to demonstrate progress in asset optimization, grid optimization and performance gains across traditional business drivers such as customers, revenue protection, utility regulatory compliance and financials. ActuateOne for Utility Analytics provides a comprehensive portfolio of software and utility analytics industry expertise to ensure today’s utility leaders and customers always have access to the right information, insight and collaborative capabilities for accurate and informed decisions. Delivered through a single platform, ActuateOne for Utility Analytics ignites any utility or grid Analytics initiative with integrated asset optimization dashboards, grid optimization dashboards, utility compliance reports as well as Transformer Management Scorecards, Substation & Equipment Management Scorecards and Utility KPI Dashboards which help today’s Utility enhance performance and maximize grid performance.
Open source Apache Hadoop is a great framework for distributed processing of large data sets. But there’s a difference between “playing” with big data versus solving real problems. The reality is that Hadoop alone is not enough. In fact, almost every organization that plans to use Hadoop for production use quickly discovers that it lacks the required features for enterprise use. And, fewer still have the Hadoop specialists on hand to navigate through the complexity to build reliable, robust applications. As a result, many Hadoop projects never make it to production as executives say, “we just don’t have the skills.” In this session, we will discuss these enterprise capabilities and why they’re important: analytics, visualization, security, enterprise integration, developer/admin tools, and more. Additionally, we will share several real-world client examples who have found it necessary to use an enterprise-grade Hadoop platform to tackle some of the most interesting and challenging business problems.
In this slidecast, Richard Treadway and Rich Seger from NetApp discuss the company's storage solutions for Big Data and HPC. The company's HPC solutions for Lustre support massive performance and storage density without sacrificing efficiency.
Presented to eRum (Budapest), May 2018
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe the doAzureParallel package, a backend to the "foreach" package that automates the process of spawning a cluster of virtual machines in the Azure cloud to process iterations in parallel. This will include an example of optimizing hyperparameters for a predictive model using the "caret" package.
By David Smith. Presented at Microsoft Build (Seattle), May 7 2018.
Your data scientists have created predictive models using open-source tools, proprietary software, or some combination of both, and now you are interested in lifting and shifting those models to the cloud. In this talk, I'll describe how data scientists can transition their existing workflows — while using mostly the same tools and processes — to train and deploy machine learning models based on open source frameworks to Azure. I'll provide guidance on keeping connections to data sources up-to-date, evaluating and monitoring models, and deploying applications that make use of those models.
Presentation delivered by David Smith to NY R Conference https://www.rstats.nyc/, April 2018:
Minecraft is an open-world creativity game, and a hit with kids. To get kids interested in learning to program with R, we created the "miner" package. This package is a collection of simple functions that allow you to connect with a Minecraft instance, manipulate the world within by creating blocks and controlling the player, and to detect events within the world and react accordingly.
The miner package is intended mainly for kids, to inspire them to learn R while playing Minecraft. But the development of the package also provides some useful insights into how to build an R package to interface with a persistent API, and how to instruct others on its use. In this talk I'll describe how to set up your own Minecraft server, and how to use and extend the package. I'll also provide a few examples of the package in action in a live Minecraft session.
While Python is a widely-used tool for AI development, in this talk I'll make the case for considering R as a platform for developing models for intelligent applications. Firstly, R provides a first-class experience working deep learning frameworks with its keras integration. Equally importantly, it provides the most comprehensive suite of statistical data analysis tools, which are extremely useful for many intelligent applications such as transfer learning. I'll give a few high-level examples in this talk, and we'll go into further detail in the accompanying interactive code lab.
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe several techniques available in R to speed up workloads like these, by running multiple iterations simultaneously, in parallel.
Many of these techniques require the use of a cluster of machines running R, and I'll provide examples of using cloud-based services to provision clusters for parallel computations. In particular, I will describe how you can use the SparklyR package to distribute data manipulations using the dplyr syntax, on a cluster of servers provisioned in the Azure cloud.
Presented by David Smith at Data Day Texas in Austin, January 27 2018.
A look at the changing perceptions of R, from the early days of the R project to today. Microsoft sponsor talk, presented by David Smith to the useR!2017 conference in Brussels, July 5 2017.
Predicting Loan Delinquency at One Million Transactions per SecondRevolution Analytics
Real-time applications of predictive models must be able to generate predictions at the rate that transactions are generated. Previously, such applications of models trained using R needed to be converted to other languages like C++ or Java to achieve the required throughput. In this talk, I’ll describe how to use the in-database R processing capabilities of Microsoft R Server to detect fraud in a SQL Server database of loan records at a rate exceeding one million transactions per second. I will also show the process of training the underlying gradient-boosted tree model on a large training set using the out-of-memory algorithms of Microsoft R.
Presented by David Smith at The Data Science Summit, Chicago, April 20 2017.
The ability to independently reproduce results is a critical issue within the scientific community today, and is equally important for collaboration and compliance in business. In this talk, I'll introduce several features available in R that help you make reproducibility a standard part of your data science workflow. The talk will include tips on working with data and files, combining code and output, and managing R's changing package ecosystem.
Presented by David Smith, R Community Lead (Microsoft), at Monktoberfest October 2016.
The value of open source isn’t just in the software itself. The communities that form around open source software provide just as much value and sometimes even more: in ongoing development, in documentation, in support, in marketing, and as a supply of ready-trained employees. Companies who build on open source tend to focus on the software, but neglect communities at their peril.
In this talk, I share some of my experiences in building community for an open-source software company, Revolution Analytics, and perspectives since the acquisition by Microsoft in 2015.
R is more than just a language. Many of the reasons why R has become such a popular tool for data science come from the ecosystem surrounding the R project. R users benefit from the many resources and packages created by the community, while commercial companies (including Microsoft) provide tools to extend and support R, and services to help people use R.
In this talk, I will give an overview of the R Ecosystem and describe how it has been a critical component of R’s success, and include several examples of Microsoft’s contributions to the ecosystem.
(Presented to EARL London, September 2016)
(Presented by David Smith at useR!2016, June 2016. Recording: https://channel9.msdn.com/Events/useR-international-R-User-conference/useR2016/R-at-Microsoft )
Since the acquisition of Revolution Analytics in April 2015, Microsoft has embarked upon a project to build R technology into many Microsoft products, so that developers and data scientists can use the R language and R packages to analyze data in their data centers and in cloud environments.
In this talk I will give an overview (and a demo or two) of how R has been integrated into various Microsoft products. Microsoft data scientists are also big users of R, and I'll describe a couple of examples of R being used to analyze operational data at Microsoft. I'll also share some of my experiences in working with open source projects at Microsoft, and my thoughts on how Microsoft works with open source communities including the R Project.
Hadoop is famously scalable. Cloud Computing is famously scalable. R – the thriving and extensible open source Data Science software – not so much. But what if we seamlessly combined Hadoop, Cloud Computing, and R to create a scalable Data Science platform? Imagine exploring, transforming, modeling, and scoring data at any scale from the comfort of your favorite R environment. Now, imagine calling a simple R function to operationalize your predictive model as a scalable, cloud-based Web Service. Learn how to leverage the magic of Hadoop on-premises or in the cloud to run your R code, thousands of open source R extension packages, and distributed implementations of the most popular machine learning algorithms at scale.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...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.
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/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
5. Revolution Confidential
Most advanced statistical
analysis software available
The professor who invented analytic software for
Half the cost of the experts now wants to take it to the masses
commercial alternatives
2M+ Users
Power
2,500+ Applications
Finance
Statistics
Life Sciences
Predictive Manufacturing
Analytics Productivity
Retail
Data Mining Telecom Enterprise
Social Media Readiness
Visualization
Government
5
6. R evolution R E nterpris e has the Open-
S ourc e R E ngine at the c ore Revolution Confidential
2,500 community packages and growing exponentially
Multi-Threaded Technology Web Services Big Data Parallel
Math Libraries Partners API Analysis Tools
Revolution
Technical Productivity
Support Environment
Open Source R Build
Packages R Engine Assurance
Language Libraries
6
22. Revolution Confidential
Turbo-C harge Your
A nalytic s with IB M
Netezza and R evolution
R E nterpris e
P res ented by:
Derek M Norton, S enior S ales E ngineer
23. Us e C as e – C redit R is k Revolution Confidential
We have a dataset comprised of individuals
and their credit risk
stored on the Netezza Appliance
The goal is to model if someone is
“approvable” for a loan.
This use case will follow a modeling process
(though condensed) from start to finish.
I will discuss each of the parts and at the end
there will be a demo of the code
24. Modeling E xerc is e Revolution Confidential
1. Learning more about the data
2. Prepare the data for modeling
3. Fit models to the data
4. Model Performance
25. 1. L earning more about the data Revolution Confidential
Connect to the IBM Netezza appliance
Summarize the data
Visualize the data
Continuous Variable Discrete Varible
300
300
250
250
Frequency
200
200
150
150
100
100
50
50
0
0
0 5 10 15 20 25 High School Diploma Bachelors Degree Masters Degree Professional Degree PhD
x
26. 2. P repare the data for modeling Revolution Confidential
Split the data in to 70/30 Training/Test sets
Transform some variables
Discretize numeric variables for later use
27. 3. F it models to the data Revolution Confidential
Build two different models to predict if an
individual is “approvable”
Decision Tree
Naïve Bayes
28. 4. Model P erformanc e Revolution Confidential
Examine confusion matrices to determine:
Training performance
Test performance