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.
linux device drivers: Role of Device Drivers, Splitting The Kernel, Classes of
Devices and Modules, Security Issues, Version Numbering, Building and Running Modules
Kernel Modules Vs. Applications, Compiling and Loading, Kernel Symbol Table,
Preliminaries, Interaction and Shutdown, Module Parameters, Doing It in User Space.
Kernel Recipes 2019 - Faster IO through io_uringAnne Nicolas
Since the dawn of time, Linux has had to make do with inferior IO interfaces. Native Linux AIO supports only a niche application class (O_DIRECT), and even for that use case, it’s far too slow for modern storage. This talk will detail io_uring, a modern IO interface for Linux, that’s both fully featured and performant.
Jens Axboe
Linux has become integral part of Embedded systems. This three part presentation gives deeper perspective of Linux from system programming perspective. Stating with basics of Linux it goes on till advanced aspects like thread and IPC programming.
Android Audio HAL – Audio Architecture – Audio HAL interface – Audio Policy – Audio HAL compilation & verification – Overview of Tinyalsa
Android Video HAL – Camera Architecture – Overview of camera HAL interface – Overview of V4L2 – Enabling V4l2 in kernel – Camera HAL compilation and verification
- Understanding Time Series
- What's the Fundamental Problem
- Prometheus Solution (v1.x)
- New Design of Prometheus (v2.x)
- Data Compression Algorithm
linux device drivers: Role of Device Drivers, Splitting The Kernel, Classes of
Devices and Modules, Security Issues, Version Numbering, Building and Running Modules
Kernel Modules Vs. Applications, Compiling and Loading, Kernel Symbol Table,
Preliminaries, Interaction and Shutdown, Module Parameters, Doing It in User Space.
Kernel Recipes 2019 - Faster IO through io_uringAnne Nicolas
Since the dawn of time, Linux has had to make do with inferior IO interfaces. Native Linux AIO supports only a niche application class (O_DIRECT), and even for that use case, it’s far too slow for modern storage. This talk will detail io_uring, a modern IO interface for Linux, that’s both fully featured and performant.
Jens Axboe
Linux has become integral part of Embedded systems. This three part presentation gives deeper perspective of Linux from system programming perspective. Stating with basics of Linux it goes on till advanced aspects like thread and IPC programming.
Android Audio HAL – Audio Architecture – Audio HAL interface – Audio Policy – Audio HAL compilation & verification – Overview of Tinyalsa
Android Video HAL – Camera Architecture – Overview of camera HAL interface – Overview of V4L2 – Enabling V4l2 in kernel – Camera HAL compilation and verification
- Understanding Time Series
- What's the Fundamental Problem
- Prometheus Solution (v1.x)
- New Design of Prometheus (v2.x)
- Data Compression Algorithm
There is a surge in number of sensors / devices that are getting connected under the umbrella of Internet-Of-Things (IoT). These devices need to be integrated into the Android system and accessed via applications, which is covered in the course. Our Android system development course curriculum over weekends with practicals ensures you learn all critical components to get started.
Embedded Android system development workshop is focused on integrating new device with Android framework. Our hands-on approach makes Emertxe as the best institute to learn android system development training. This workshop deep dives into Android porting, Android Hardware Abstraction Layer (HAL), Android Services and Linux device driver ecosystem. This workshop based training program will enable you to efficiently integrate new hardware with Android HAL / Framework.
The Linux Block Layer - Built for Fast StorageKernel TLV
The arrival of flash storage introduced a radical change in performance profiles of direct attached devices. At the time, it was obvious that Linux I/O stack needed to be redesigned in order to support devices capable of millions of IOPs, and with extremely low latency.
In this talk we revisit the changes the Linux block layer in the
last decade or so, that made it what it is today - a performant, scalable, robust and NUMA-aware subsystem. In addition, we cover the new NVMe over Fabrics support in Linux.
Sagi Grimberg
Sagi is Principal Architect and co-founder at LightBits Labs.
Page cache mechanism in Linux kernel.
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
This course gets you started with writing device drivers in Linux by providing real time hardware exposure. Equip you with real-time tools, debugging techniques and industry usage in a hands-on manner. Dedicated hardware by Emertxe's device driver learning kit. Special focus on character and USB device drivers.
Research Data (and Software) Management at Imperial: (Everything you need to ...Sarah Anna Stewart
A presentation on research data management tools, workflows and best practices at Imperial College London with a focus on software management. Presented at the 2017 session of the HPC Summer School (Dept. of Computing).
There is a surge in number of sensors / devices that are getting connected under the umbrella of Internet-Of-Things (IoT). These devices need to be integrated into the Android system and accessed via applications, which is covered in the course. Our Android system development course curriculum over weekends with practicals ensures you learn all critical components to get started.
Embedded Android system development workshop is focused on integrating new device with Android framework. Our hands-on approach makes Emertxe as the best institute to learn android system development training. This workshop deep dives into Android porting, Android Hardware Abstraction Layer (HAL), Android Services and Linux device driver ecosystem. This workshop based training program will enable you to efficiently integrate new hardware with Android HAL / Framework.
The Linux Block Layer - Built for Fast StorageKernel TLV
The arrival of flash storage introduced a radical change in performance profiles of direct attached devices. At the time, it was obvious that Linux I/O stack needed to be redesigned in order to support devices capable of millions of IOPs, and with extremely low latency.
In this talk we revisit the changes the Linux block layer in the
last decade or so, that made it what it is today - a performant, scalable, robust and NUMA-aware subsystem. In addition, we cover the new NVMe over Fabrics support in Linux.
Sagi Grimberg
Sagi is Principal Architect and co-founder at LightBits Labs.
Page cache mechanism in Linux kernel.
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
This course gets you started with writing device drivers in Linux by providing real time hardware exposure. Equip you with real-time tools, debugging techniques and industry usage in a hands-on manner. Dedicated hardware by Emertxe's device driver learning kit. Special focus on character and USB device drivers.
Research Data (and Software) Management at Imperial: (Everything you need to ...Sarah Anna Stewart
A presentation on research data management tools, workflows and best practices at Imperial College London with a focus on software management. Presented at the 2017 session of the HPC Summer School (Dept. of Computing).
Presented at useR! 2014, July 2, 2014.
The R ecosystem is in a state of near constant change. While a new version of the R engine is now released just once a year, 2-3 patches are usually released in the interim. On top of that, new versions of R packages on CRAN are released at rate of several per day (and that’s not counting packages that are part of the BioConductor project or hosted elsewhere on the Web).
While this rapid change is a boon for the advancement of R, it can cause problems for package authors[1] and also for scientists and their peers who may need to reliably reproduce the results of an R script (possibly dependent on a number of packages) months or even years down the line. In this talk we propose a downstream distribution of CRAN packages that provides for the reproducibility of R scripts and reduces the impact of dependencies for packages authors.
In-Database Analytics Deep Dive with Teradata and RevolutionRevolution Analytics
Teradata and Revolution Analytics worked together to develop in-database analytical capabilities for Teradata Database. Teradata v14.10 provides a foundation for in-database analytics in Teradata. Revolution Analytics has ported its Revolution R Enterprise (RRE) Version 7.1 to use the in-database capabilities of version 14.10. With RRE inside Teradata, users can run fully parallelized algorithms in each node of the Teradata appliance to achieve performance and data scale heretofore unavailable. We'll get past the market-ecture quickly and dive into a “how it really works” presentation, review implications for system configuration and administration, and then take questions from Teradata users who will be charged with deploying and administering Teradata systems as platforms for big data analytics inside the database engine.
A Maturing Role of Workflows in the Presence of Heterogenous Computing Archit...Ilkay Altintas, Ph.D.
cientific workflows are used by many scientific communities to capture, automate and standardize computational and data practices in science. Workflow-based automation is often achieved through a craft that combines people, process, computational and Big Data platforms, application-specific purpose and programmability, leading to provenance-aware archival and publications of the results. This talk summarizes varying and changing requirements for distributed workflows influenced by Big Data and heterogeneous computing architectures and present a methodology for workflow-driven science based on these maturing requirements.
This session covers topics related to data archiving and sharing. This includes data formats, metadata, controlled vocabularies, preservation, archiving and repositories.
Webinar: Enterprise Data Management in the Era of MongoDB and Data LakesMongoDB
With so much talk of how Big Data is revolutionizing the world and how a data lake with Hadoop and/or Spark will solve all your data problems, it is hard to tell what is hype, reality, or somewhere in-between.
In working with dozens of enterprises in varying stages of their enterprise data management (EDM) strategy, MongoDB enterprise architect, Matt Kalan, sees the same challenges and misunderstandings arise again and again.
In this session, he will explain common challenges in data management, what capabilities are necessary, and what the future state of architecture looks like. MongoDB is uniquely capable of filling common gaps in the data lake strategy.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
Hadoop meets Agile! - An Agile Big Data ModelUwe Printz
Big Data projects are a struggle, not only on the technical side but also on the organizational side. In this talk the author shares his experience and opinions from almost 5 years of Big Data projects and develops an Agile Big Data Model which reflects his ideas on how Big Data projects can be successful, even in large companies.
Talk held at the crossover meetup of the "Agile Stammtisch Rhein-Main" and the "Hadoop & Spark User Group Rhein-Main" at codecentric AG on 31.01.2017.
What is reproducible research? Why should I use it? what tools should I use? This session will show you how to use scripts, version control and markdown to do better research.
Data Visibility and Protection at the Scale of Life SciencesAdam Marko
Data generation in the life sciences continues at a rapid pace. There are always risks of data loss, including hardware failures, inability of staff to access data centers, and user error. During challenging times like these, understanding and protecting your data can save lives. Join us to see how you can protect and visualize your files at the scale of Life Sciences, with integrated search, restore, and visibility.
microsoft r server for distributed computingBAINIDA
microsoft r server for distributed computing กฤษฏิ์ คำตื้อ,
Technical Evangelist,
Microsoft (Thailand)
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
OSA Con 2022 - Scaling your Pandas Analytics with Modin - Doris Lee - Ponder.pdfAltinity Ltd
OSA Con 2022: Scaling your Pandas Analytics with Modin
Doris Lee - Ponder
Pandas is one of the most commonly used data science libraries in Python, with a convenient set of APIs for data cleaning, visualization, analysis, and exploration. However, despite its widespread adoption, Pandas suffers from severe scalability issues on large datasets. We developed the open-source project Modin, which is a fast, scalable drop-in replacement for pandas. Modin has been downloaded more than 4 million times and is used by leading data science teams, including Fortune 100 companies.
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, 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.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
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https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
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✅More than 85 AI features are included in the AI pilot.
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See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
2. What is reproducibility?
“Two honest researchers would
get the same result”
– John Mount
• Transparent data sourcing and availability
• Fully automated analysis pipeline (code provided)
• Traceability from published results back to data
2
3. Why Reproducibility?
• Save time
• Better science
• More authoritative research
• Reduce risk of errors
• Facilitate collaboration
3
4. Why Reproducibility?
• Save time
• Better science
• More authoritative research
• Reduce risk of errors
• Facilitate collaboration
4
5. Why Reproducibility?
• Save time
• Better science
• More authoritative research
• Reduce risk of errors
• Facilitate collaboration
5
6. Why Reproducibility?
• Save time
• Better science
• More authoritative research
• Reduce risk of errors
• Facilitate collaboration
6
7. Why Reproducibility?
• Save time
• Better science
• More authoritative research
• Reduce risk of errors
• Facilitate collaboration
7
8. Accessing Data
• Data sources
– databases, sensor logs, spreadsheets, file download, APIs, …
– Remember, these are sources: don’t modify them!
• Snapshot data into local static files (text is good)
– You will likely include some ETL steps here
– Record a timestamp of when data was extracted: Sys.time()
– With big data, sample during development, scale up to finalize
– Document how this was all done, preferably with code (source file)!
• Import text files using R functions
– Recommended package: readr (avoids issues with locale, dates, etc)
8
9. Analysis process
• Interactively explore data & develop analyses as usual
• Capture the entire process in an R script
– library(tidyverse) is helpful for cleaning, feature generation, etc.
– Re-usable components can be shared as (private) packages
• Generate artifacts using scripts
– Graphics (please, no JPGs!)
– Tables
– Documents
• Include timestamps in output: Sys.time()
9
10. A reproducible analysis environment
• Operating system and R version
– For most purposes, not the biggest cause of issues
• But do document your R session info: sessionInfo()
– For production, consider VM / container
• A clean R environment
– Organize work into independent projects (directories)
– Use relative paths in scripts
– Avoid use of .Rprofile
– Set explicit random seeds
– Do not save R workspace
10
11. Managing a changing R package ecosystem
• One command to lock package versions to a specific date:
checkpoint("2017-04-11")
(For collaborators, same command downloads required package versions)
• Applies just to this project
– Global package upgrades won’t break reproducibility in other projects
• checkpoint package avail on CRAN, included with Microsoft R
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12. Presenting results
• Eliminate manual processes
(as far as possible)
– Annotations (graphs / tables)
– Cut-and-paste into documents
• Notebooks
– Combines code, output and
narrative
– Good for collaboration with
other researchers
• Document Generation
– Best for automating reports
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13. knitr / Rmarkdown
• Generate HTML, Word,
or PDF reports
– Or books, blogs, slides, …
• Combine narrative and
R code in a single
document
• Human-readable, easy
to edit
• Single-click update!
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14. Collaboration and sharing
• Just share R project folder
• Publish on Github
– Happy Git and GitHub for the
useR, Jenny Bryan
http://happygitwithr.com/
– Version retention and tracking
– Collaboration (code and
comments)
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15. Take-Aways
Reproducibility is Beneficial
• Saves time
• Produces better science
• More trusted research
• Reduced risk of errors
• Encourages collaboration
Reproducibility is Simple
• Document and automate processes
with R scripts
• Read and clean data with tidyverse
• Use checkpoint to manage package
versions
• Generate documents with knitr
• Share reproducible projects with
Github
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