A case study on our (Sears Holdings Corporation, Israel, a.k.a. Delver) use of GigaSpaces as a key part of our social commerce infrastructure. I presented this at the GigaSpaces Roadshow 2011 in Paris, France.
Here is a slidedeck we use to help immerse clients in what blockchains are beyond just bitcoin and allow them to begin to make connections to their worlds.
O'Reilly eBook: Creating a Data-Driven Enterprise in Media | eubolrVasu S
An O'Reilly eBook about Creating a Data-Driven Enterprise in Media DataOps Insights from Comcast, Sling TV, and Turner Broadcasting.
https://www.qubole.com/resources/ebooks/ebook-creating-a-data-driven-enterprise-in-media
Thank you for your interest in the recent NY Outthink breakfast on July 19th at the Rainbow Room. Presentations shared highlighted how cognitive computing is being applied today in a variety of business situations, in many industries, and across multiple business functions. Presentation by Jason Kelley
Keynote talk at Financial Times Forum - BigData and Advanced Analytics at SIB...Usama Fayyad
BigData in financial services and banking - a view from the on-line advanced analytics with case studies from Yahoo! and others. This is a shortened presentation, and the longer version available. Includes commentary on Hadoop and Map-Reduce grid and where appropriate to use.
6 Commonly Asked Questions from Customers Building on AWSRackspace
This session is ideal for IT/Infrastructure Manager, Application Developers, System Architects/Administrators and anyone who is growing their AWS footprint. We will uncover recent customer experiences at every stage while you can network with peers that face similar challenges.
Here is a slidedeck we use to help immerse clients in what blockchains are beyond just bitcoin and allow them to begin to make connections to their worlds.
O'Reilly eBook: Creating a Data-Driven Enterprise in Media | eubolrVasu S
An O'Reilly eBook about Creating a Data-Driven Enterprise in Media DataOps Insights from Comcast, Sling TV, and Turner Broadcasting.
https://www.qubole.com/resources/ebooks/ebook-creating-a-data-driven-enterprise-in-media
Thank you for your interest in the recent NY Outthink breakfast on July 19th at the Rainbow Room. Presentations shared highlighted how cognitive computing is being applied today in a variety of business situations, in many industries, and across multiple business functions. Presentation by Jason Kelley
Keynote talk at Financial Times Forum - BigData and Advanced Analytics at SIB...Usama Fayyad
BigData in financial services and banking - a view from the on-line advanced analytics with case studies from Yahoo! and others. This is a shortened presentation, and the longer version available. Includes commentary on Hadoop and Map-Reduce grid and where appropriate to use.
6 Commonly Asked Questions from Customers Building on AWSRackspace
This session is ideal for IT/Infrastructure Manager, Application Developers, System Architects/Administrators and anyone who is growing their AWS footprint. We will uncover recent customer experiences at every stage while you can network with peers that face similar challenges.
5 Big Data Visualization Maps that Will Make Your HEAD EXPLODEBI Brainz
From BI Brainz Analytics on Fire
Original Blog Post: http://bit.ly/1Dab2JG
Written by Ryan Goodman - @rmgoodm
Posted on Analytics on Fire - @analyticsonfire
Not all data visualizations can be simplified to a speedometer or bar chart. Big data visualizations require more sophisticated visualization tools and more brainpower. Here are some big data visualizations examples that will blow your mind!
Notes from the Observation Deck // A Data Revolution gngeorge
Notes from the Observation Deck will provide you with an examined look at the interesting phenomena and trends taking place around us today. We present them to you with the hope of sparking broader conversations, debates and ideas. Please use this as a resource for knowledge, inspiration and enjoyment.
Big MDM Part 2: Using a Graph Database for MDM and Relationship ManagementCaserta
During this Big Data Warehousing Meetup, we discussed how graph databases work, shared some real world use cases, and showed a live demo of the world’s leading graph database, Neo4J. Pitney Bowes demonstrated their new MDM product developed on a graph database.
For more information, check out the other slides from this meetup or visit our website at www.casertaconcepts.com
IBM Governed data lake is a value-driven big data platform journey. The journey starts by ingesting wide variety of data, governing it, applying data science and machine learning on it to produce actionable insights.
How AI will impact Web and Social Media Intelligence - Uljan Sharka (Crystal.io)Data Driven Innovation
Data is the new oil. With more channels and KPIs on the rise it’s becoming more and more difficult to get value from Digital Data. Artificial Intelligence will change the status quo through Natural Language Processing, Machine Deep Learning, Voice Recognition and Computer Vision by saving time, providing real time processed KPIs and by driving operations through predictions and actionable insights.
This deck talks about the basic overview of NoSQL technologies, implementation vendors/products, case studies, and some of the core implementation algorithms. The presentation also describes a quick overview of "Polyglot Persistency", "NewSQL" like emerging trends.
The deck is targeted to beginners who wants to get an overview of NoSQL databases.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
5 Big Data Visualization Maps that Will Make Your HEAD EXPLODEBI Brainz
From BI Brainz Analytics on Fire
Original Blog Post: http://bit.ly/1Dab2JG
Written by Ryan Goodman - @rmgoodm
Posted on Analytics on Fire - @analyticsonfire
Not all data visualizations can be simplified to a speedometer or bar chart. Big data visualizations require more sophisticated visualization tools and more brainpower. Here are some big data visualizations examples that will blow your mind!
Notes from the Observation Deck // A Data Revolution gngeorge
Notes from the Observation Deck will provide you with an examined look at the interesting phenomena and trends taking place around us today. We present them to you with the hope of sparking broader conversations, debates and ideas. Please use this as a resource for knowledge, inspiration and enjoyment.
Big MDM Part 2: Using a Graph Database for MDM and Relationship ManagementCaserta
During this Big Data Warehousing Meetup, we discussed how graph databases work, shared some real world use cases, and showed a live demo of the world’s leading graph database, Neo4J. Pitney Bowes demonstrated their new MDM product developed on a graph database.
For more information, check out the other slides from this meetup or visit our website at www.casertaconcepts.com
IBM Governed data lake is a value-driven big data platform journey. The journey starts by ingesting wide variety of data, governing it, applying data science and machine learning on it to produce actionable insights.
How AI will impact Web and Social Media Intelligence - Uljan Sharka (Crystal.io)Data Driven Innovation
Data is the new oil. With more channels and KPIs on the rise it’s becoming more and more difficult to get value from Digital Data. Artificial Intelligence will change the status quo through Natural Language Processing, Machine Deep Learning, Voice Recognition and Computer Vision by saving time, providing real time processed KPIs and by driving operations through predictions and actionable insights.
This deck talks about the basic overview of NoSQL technologies, implementation vendors/products, case studies, and some of the core implementation algorithms. The presentation also describes a quick overview of "Polyglot Persistency", "NewSQL" like emerging trends.
The deck is targeted to beginners who wants to get an overview of NoSQL databases.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
Big Data, NoSQL, NewSQL & The Future of Data ManagementTony Bain
It is an exciting and interesting time to be involved in data. More change of influence has occurred in the database management in the last 18 months than has occurred in the last 18 years. New technologies such as NoSQL & Hadoop and radical redesigns of existing technologies, like NewSQL , will change dramatically how we manage data moving forward.
These technologies bring with them possibilities both in terms of the scale of data retained but also in how this data can be utilized as an information asset. The ability to leverage Big Data to drive deep insights will become a key competitive advantage for many organisations in the future.
Join Tony Bain as he takes us through both the high level drivers for the changes in technology, how these are relevant to the enterprise and an overview of the possibilities a Big Data strategy can start to unlock.
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
Recently the concept of a ‘data mesh’ was introduced by Zhamak Deghani to solve architectural and organizational challenges with getting value from data at scale more logically and efficiently, built around four principles:
* Domain-oriented decentralized data ownership
* Data as a product
* Self-serve data infrastructure as a platform
* Federated computational governance
This presentation will initially deep-dive into the ‘data mesh’ and how it fundamentally differs from the typical data lake architectures used today. Subsequently, it describes OLX Europe’s current data platform state aimed partially towards a more decentralized data architecture, covering its analytical data platform, data infrastructure, data discovery, and data privacy.
Finally, it will see to what extent the main principles around the ‘data mesh’ can be applied to a future vision for our data platform and what advantages and challenges implementing such a vision can bring for OLX and other companies.
For more information on data mesh principles, check out the original article by Zhamak: https://martinfowler.com/articles/data-mesh-principles.html.
How to Place Data at the Center of Digital Transformation in BFSIDenodo
Watch full webinar here: https://bit.ly/3j7E9Jo
Consumers are increasingly using digital banking tools and insurance models, and these numbers will only continue to grow. Financial and insurance organizations have to adapt to the new and always changing situation while complying with new regulations, such as IFRS17, and embracing ESG criteria.
At the heart of any digital transformation is data. Therefore, it is not a stretch to say that data management and analytics strategies differentiate many of the leaders from the laggards in the banking, financial services and insurance (BFSI) industry. BFSI organizations still relying on slow, traditional systems and data management processes will find themselves falling behind their competition. In addition, as many adopt cloud strategies, these traditional approaches fill the cloud modernization process with downtime and end user frustration. In fact, according to a McKinsey article, cloud combined with distributed data infrastructure will define how consumers and providers adopt digital insurance models for the next decade.
Hear how the BFSI industry is leveraging data virtualization to deploy data fabric or data mesh architectures for enterprise-wide digital transformation.
Join this webinar to learn:
- The latest trends in BFSI for 2023 and how data and analytics is reshaping the industry
- How a logical data architecture can help you capitalize on your data
- How Denodo customers digitally transformed themselves using the Denodo Platform
A talk given at GeeCON 2018 in Prague, Czech Republic
In this talk we'll take a hard look at one of the most commonly used, and at least as commonly misunderstood, elements in software engineering: time. Time is so fundamental to the way humans experience reality that we don't normally give it a second thought, but it's just as fundamental to software systems. Without a correct model for working with time BAD THINGS HAPPEN: data is persisted out of order, exceptions occur where they shouldn't be possible, and production systems blow up.
We'll cover the various common representations of time, acknowledge their caveats and deficiencies, and hopefully learn a few new tools and practices along the way.
Nondeterministic Software for the Rest of UsTomer Gabel
A talk given at GeeCON 2018 in Krakow, Poland.
Classically-trained (if you can call it that) software engineers are used to clear problem statements and clear success and acceptance criteria. Need a mobile front-end for your blog? Sure! Support instant messaging for a million concurrent users? No problem! Store and serve 50TB of JSON blobs? Presto!
Unfortunately, it turns out modern software often includes challenges that we have a hard time with: those without clear criteria for correctness, no easy way to measure performance and success is about more than green dashboards. Your blog platform better have a spam filter, your instant messaging service has to have search, and your blobs will inevitably be fed into some data scientist's crazy contraption.
In this talk I'll share my experiences of learning to deal with non-deterministic problems, what made the process easier for me and what I've learned along the way. With any luck, you'll have an easier time of it!
This talk revisits dependency injection, and attempts to answer a single question honestly, or at least while pointing out and acknowledging the biases at play: "is dependency injection a good thing?"
Dependency injection has fast established itself as a major design pattern in modern software. No longer the province of server-side and enterprise software, it is now a fundamental component of frameworks from Spring to Angular.js.
With such widespread success, the time is ripe to take a fresh look at dependency injection if we are to understand it better. After all, DI is instrumental in building large systems that are loosely coupled, and it cleanly separates your tests from implementation... or does it?
(A talk given at GeeCON 2017 in Prague, Czech Republic)
Although event sourcing (and its sister pattern CQRS) has been gaining traction in recent years, it's still baffling for many engineers attempting to implement it for the first time. While there's plenty of material on the subject, most of it is too basic or theoretical for practical applications, and engineers often end up having to reinvent (or rediscover) suitable approaches and techniques.
This talk focuses on practical aspects of building event-sourced systems, lessons learned from our experience building such systems at Wix. We'll walk through the design and implementation of a relatively simple event-sourced system, covering the event model, underlying persistence model, code layering/factoring and operational considerations.
A talk given at Reversim Summit 2017 in Tel-Aviv, Israel.
The beautiful thing about software engineering is that it gives you the warm and fuzzy illusion of total understanding: I control this machine because I know how it operates. This is the result of layers upon layers of successful abstractions, which hide immense sophistication and complexity. As with any abstraction, though, these sometimes leak, and that's when a good grounding in what's under the hood pays off.
The second talk in this series peels a few layers of abstraction and takes a look under the hood of our "car engine", the CPU. While hardly anyone codes in assembly language anymore, your C# or JavaScript (or Scala or...) application still ends up executing machine code instructions on a processor; that is why Java has a memory model, why memory layout still matters at scale, and why you're usually free to ignore these considerations and go about your merry way.
You'll come away knowing a little bit about a lot of different moving parts under the hood; after all, isn't understanding how the machine operates what this is all about?
(From a talk given at BuildStuff 2016 in Vilnius, Lithuania.)
The beautiful thing about software engineering is that it gives you the warm and fuzzy illusion of total understanding: I control this machine because I know how it operates. This is the result of layers upon layers of successful abstractions, which hide immense sophistication and complexity. As with any abstraction, though, these sometimes leak, and that's when a good grounding in what's under the hood pays off.
This first in what will hopefully be a series of talks covers the fundamentals of storage, providing an overview of the three storage tiers commonly found on modern platforms (hard drives, RAM and CPU cache). You'll come away knowing a little bit about a lot of different moving parts under the hood; after all, isn't understanding how the machine operates what this is all about?
-- A talk given at GeeCON Kraków 2016.
With Java 8 adoption skyrocketing, is Scala still relevant? In our opinion, the answer is an unequivocal yes. To make our point, Tomer Gabel (system architect at Wix) will showcase practical examples where Scala's features provide a definitive advantage over Java 8. These include:
* Effective logging with traits and by-name parameters;
* Pattern matching for fun and profit;
* Type-safe, efficient serialization with type classes.
A talk given at a Wix Ukraine R&D meetup in Dnipropetrovsk, Ukraine on 6 April, 2016.
Video recording: https://youtu.be/EXxA3PlcdBg?t=3680
Sample code: https://github.com/holograph/scala-vs-java8
(A talk given at Wix R&D in Dnipro, Ukraine on March 2017. Video available at https://www.youtube.com/watch?v=eIX33mQdkAI&feature=youtu.be)
While microservices are conceptually simple, it's a deep rabbit hole to go down. Deceptively simple questions can have far-reaching implications: Which communication protocol should I choose? Is event-driven the way to go? What monitoring tools should I put in place?
In this talk we'll cover some of the fundamental questions, outline the solutions adopted or developed by Wix, and share our hindsight on what worked well for us, what didn't and thoughts on future directions for our stack.
Scala Refactoring for Fun and Profit (Japanese subtitles)Tomer Gabel
A talk given at Scala Matsuri 2016 in Tokyo, Japan.
New Scala practitioners often experience the uncomfortable feeling of "not quite getting it." If you've studied the syntax and written tests, maybe production code; if you're becoming comfortable with the language and libraries, but keep worrying that there's "a better way", or that your code isn't "idiomatic enough" - this session is for you.
By refactoring a real, live codebase, this talk will provide you with new tools and increased confidence. Between the provided examples and the ensuing discussion, you will walk away with a better feel for Scala and how to employ it in the real world.
Of the myriad challenges in scaling up an engineering organization, onboarding new employees is probably the least well-understood. There are relatively common solutions for large-scale recruitment, finance and administration, but onboarding remains a question that many organizations struggle with.
At Wix we've been struggling with massive scaling challenges: over the last two years our company headcount has doubled itself, and we had to learn to cope with the influx while maintaining velocity. In this talk we'll share with you the story of how we set up Wix Academy, an engineer-driven training organization, the solutions we've developed (and still are!), and what we've learned in our first year of operation.
A presentation given at Velocity 2016 in Amsterdam, The Netherlands (previously at BuildStuff 2015 in Vilnius, Lithuania).
The Scala programming language has been gaining significant traction over the last few years, being adopted by vastly different organizations from startups to large enterprises. While the language itself is pretty well understood and explained in tutorials and books, there is an apparent dearth of practical advice for new adopters on the best approach to integrating the new technology. In this talk I’ll attempt to offer such advice gathered over several years of production Scala use, focusing on tools, practices, patterns and the community, in the hope of making your transition into the Scala ecosystem easier and better-informed up front.
A talk given at JavaOne 2015 in San Francisco.
A talk given at JDay Lviv 2015 in Ukraine; originally developed by Yoav Abrahami, and based on the works of Kyle "Aphyr" Kingsbury:
Consistency, availability and partition tolerance: these seemingly innocuous concepts have been giving engineers and researchers of distributed systems headaches for over 15 years. But despite how important they are to the design and architecture of modern software, they are still poorly understood by many engineers.
This session covers the definition and practical ramifications of the CAP theorem; you may think that this has nothing to do with you because you "don't work on distributed systems", or possibly that it doesn't matter because you "run over a local network." Yet even traditional enterprise CRUD applications must obey the laws of physics, which are exactly what the CAP theorem describes. Know the rules of the game and they'll serve you well, or ignore them at your own peril...
Leveraging Scala Macros for Better ValidationTomer Gabel
A talk given at Scalapeño 2014 and JavaOne 2014 (video links to follow).
Data validation is a common enough problem that numerous attempts have been made to solve it elegantly. The de-facto solution in Java (JSR 303) has a number of shortcomings and fails to leverage the powerful Scala type system. The release of Scala 2.10.x introduced a couple of experimental metaprogramming features, namely reflection and macros. In this talk I'll introduce macros by way of a practical example: implementing a full-blown data validation engine, utilizing def macros and a Scala DSL to enable elegant validator definition syntax and call-site.
A talk given at ScalaUA 2016 in Kiev, Ukraine.
Scala combines a powerful type system with a lean but flexible syntax. This combination enables incredible flexibility in library design, most particularly in designing internal DSLs for many common scenarios: specification definition and matching in Specs² and ScalaTest, request routing in Spray and query construction in Squeryl, just to name a few. The budding DSL designer, however, will quickly realize that there are precious few resources on how to best approach the problem in Scala; the various techniques, limitations and workarounds are not generally well understood or documented, and every developer ends up running into the same challenges and dead-ends. In this talk I'll attempt to summarize what I've learned from reading, extending and designing Scala DSLs in the hopes that it'll save future Scala library designers a whole lot of pain.
Functional Leap of Faith (Keynote at JDay Lviv 2014)Tomer Gabel
Keynote talk given at JDay Lviv 2014 in Ukraine (http://www.jday.com.ua/). Video coming soon.
Abstract:
Some say that there's nothing new under the sun. However, looking back on five to six decades of computing, it's easy to see that things progress at their own leisurly pace. Structured programming, originating in the '60s, did not gain mainstream adoption until the '80s; object-oriented programming was hotly debated in the '70s and '80s but only gained widespread acceptance in the '90s. Every couple of decades sees an engineering leap that radically improves the software engineering discipline across the board. I believe we are now at such an inflection point, with functional programming concepts slowly sifting into the mainstream. After this talk, I hope you will too.
Watch video (in Hebrew): http://parleys.com/play/53f7a9cce4b06208c7b7ca1e
Type classes are a fundamental feature of Scala, which allows you to layer new functionality on top of existing types externally, i.e. without modifying or recompiling existing code. When combined with implicits, this is a truly remarkable tool that enables many of the advanced features offered by the Scala library ecosystem. In this talk we'll go back to basics: how type classes are defined and encoded, and cover several prominent use cases.
A talk given at the Underscore meetup on 19 August, 2014.
A talk given at the Wix Ukraine R&D meetup in Dnipropetrovsk, Ukraine on May 22, 2014.
So you've heard of this newfangled "Scala" thing and think it might be worth checking out. Good for you! Unfortunately, it's also daunting. Your first search for Scala is likely to pitch it as a "statically-typed hybrid object-oriented and functional language", which is technically true but doesn't really help much.
Instead, this talk will provide an overview of the language, focusing on five highly practical advantages Scala has over Java without a brain hemorrhage-inducing paradigm shift, followed by some tips and recommendations on Scala adoption in the real world and (as time allows) open-ended Q&A.
Nashorn: JavaScript that doesn’t suck (ILJUG)Tomer Gabel
View the video (in Hebrew) on Parleys: http://www.parleys.com/play/537f3dade4b0e9793767cd35
Java 8 introduces a new JavaScript engine called Nashorn. This presentation gives an overview of the new engine, provides some historical context and dives into the implementation details.
Originally presented at the Israeli Java User Group (ILJUG) Java 8 launch event on April 28th, 2014.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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
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.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
2. Social Commerce: An Introduction The last few years have seen tremendous growth in social networks Some estimates place Facebook above Google Even if not, we’re talking millions of daily unique visitors So the obvious question is… where’s the money? 2
4. Social Commerce: Business Case What’s wrong with traditional e-commerce? Discovery/recommendation features are extremely hard to get right Overly broad market targeting means lost sales and disgruntled, ad-weary customers The trust model is inherently broken Impossible to gauge truth and accuracy in customer reviews “Wisdom of the masses” does not always apply Not fun! Shopping is a social experience (going to the mall, holiday shopping sprees) This does not translate to existing e-commerce sites! 4
5. Social Commerce: Business Case “Social commerce” aims to address these deficiencies Correlating interests and products is more accurate and significantly easier when based on social context Social circles are inherently constructed on shared interests and perspectives A customer’s social network is much smaller in scope than generating a global, statistical recommendation model More accurate personalized data exposes new opportunities Personalized discovery allows more opportunity to tap the long tail Social interaction makes it easy to identify domain experts A single opinion provided by a friend, family member or acquaintance is more trustworthy than dozens of unrelated product reviews/ratings 5
6. Social Commerce: Business Case Most crucially, social commerce is all about user engagement and collaboration: Should I buy an iPhone, Blackberry or Android phone? Which wedding dress looks best? Which video games are suitable for a preschooler? 6 Ask your friends!
7. Social Commerce: The Axiom Social features increase user engagement Increased conversion Profit! 7
9. Enter: Delver The Delver team has two products on the market Two sides of the same coin, really: sears.com is a traditional e-commerce website with a social twist delver.com is a traditional social website with an e-commerce twist 9
10. The Technical Challenge sears.com is a fully blown commercial retail site Over 1 million page-views daily Over 270,000 visitors daily Traffic can easily spike up to ten times in the holiday season! 10
11. The Technical Challenge Processing social networks is not an easy proposition Massive amounts of branching data No data locality Very few assumptions can be made about the data Let’s address each of these in turn 11 Source: NetworkWeaver
12. The Technical Challenge Massive amounts of branching data: Imagine every Facebook user (500 million) Imagine each person is only connected to 100 others (conservative estimate) How is user X connected with Y? X has 100 friends Each of them has 100 friends 10,001 nodes visited! 101 reads from the underlying storage system! 12 X Y
13. The Technical Challenge No data locality: Any object may be connected to any other object in no particular order How to split the data? Some research is being done in the area (SPAR) 13
14. The Technical Challenge No easy assumptions: No “typical user” Not enough data to draw archetypes Significant, unavoidable long tail Difficult to pre-tune data structures 14
15. The Technical Challenge The crux of the problem: High branch factor necessitates many loads to serve even a simple request No data locality + high branch factor means very high random I/O Traditional storage models (RDBMS, flat files etc.) are a poor fit Serious research into graph storage, social network composition etc. only dates back a few years No best practices or “accepted truths” to build on 15
16. Use Case for GigaSpaces To solve the graph storage and traversal problem, we arrived at the following requirements: Completely in-memory storage No data locality means caching is inefficient Massive amounts of random I/O cannot scale vertically, and hardware (basically, spindle count) cost quickly becomes prohibitive If data access is sufficiently fast, data can be randomly partitioned Horizontal scaling with a well-known scale-up strategy Add more memory or more nodes to handle data growth Add more CPUs or additional nodes to handle load growth 16
17. Use Case for GigaSpaces Additional requirements include: Map/Reduce execution framework Graph traversal and data analysis requirements lend well to the map/reduce paradigm Code execution on the data nodes Because of the massive amounts of data involved, the network interface will be quickly saturated by retrievals Memory retrieval is at least two orders of magnitude faster than network throughput (DDR2-800 on a dual channel memory controller has a theoretical throughput maximum of 102.4Gb/s) 17
18. Use Case for GigaSpaces As an operations tech I had a few things to add to the list, namely… Nonfunctional requirements: Built-in fault tolerance and high availability Zero-configuration (or as close to it as it gets) setup; in particular, component discovery and assignment must be automated Well-documented deployment, configuration and tuning process Monitoring API Administrative client for diagnosis, trouble resolution and manual intervention 18
19. Use Case for GigaSpaces GigaSpaces features map well to our requirements Data grid Compute grid High availability Horizontal data and load scaling Management API Very few viable alternatives: Hadoop, neo4j are disk-based Terracotta is overly simplistic and has no execution framework Oracle Coherence is expensive and has a limited feature set 19
20. Delver Architecture We ended up with a hybrid platform: GigaSpaces for graph storage, traversal and analysis MySQL for traditional, “simple” data as well as a backing store for GigaSpaces .NET-based front-end, Java-based back-end We had to factor our organization accordingly Data access team provides abstracted interfaces on top of GigaSpaces and MySQL Back-end “heavy lifting” services (e.g. recommendation engine) work directly against GigaSpaces Most other components either use the abstracted DAL or are simple enough to work directly against MySQL using (N)Hibernate 20
22. Key Benefits Significantly reduced integration costs GigaSpaces does a lot of what we need out of the box An alternative solution would require integrating several products, incurring significant integration and development overhead Broad feature set Social commerce is an emerging, dynamic market requiring rapid experimentation and adaptation The large feature set allows us to introduce new features into the system at a furious pace While primarily intended for graph storage, we also use GigaSpaces as a message queue, distributed lock server and distributed scheduler 22
23. Now is a good time for… Questions?COMMENTS? 23
24. Endgame Experience our work! Visit Delver at http://www.delver.com/in?invite=friends-and-family Visit Sears Social at http://catalog.sears.com Read about our work at http://blog.delver.com Have anything to discuss? Contact me at tomer@delver.com Visit my blog at http://www.tomergabel.com Follow me on Twitter at http://www.twitter.com/tomerg Thank you for your time! 24
Editor's Notes
Image sources (also linked):* Facebook US traffic estimates (http://www.insidefacebook.com/2011/01/03/november-2010-facebook-traffic/)* Top 20 visited websites (http://www.hitwise.com/us/datacenter/main/)
Case in point:Discovery and recommendation features: when was the last time YOU “might be interested in this product”? How accurate are the typical recommendation systems for you?Just how relevant is the typical ad or marketing campaign? When was the last time you went into Amazon and got a coupon for a truly relevant occasion or product? How tired are you of flashing banners?
Public data source: http://bizinformation.ca/www.sears.com#visitors
Massive amounts of data:* Imagine modeling every person on the planet (say, 6 billion). Now say each person is connected to just 100 others (a conservative estimate)Image source: http://networkweaver.blogspot.com/2010/03/overlapping-boards.html
Time distribution image source: http://blog.nielsen.com/nielsenwire/global/social-norms-twitter-users-follow-the-797-rule-in-the-u-k/Twitter following distribution image source: http://www.personalizemedia.com/twitter-long-tail-broadcastization-pre-twitter-reputation/
Inevitably, someone will ask: what are the problems you encountered?Barrier of entry:Ops: setting up a GigaSpaces cluster is not a hassle-free affair. Lots of work went into a robust, efficient bootstrapping procedure and we had to content with quite a few unexpected snags. I believe things are a lot better with the current version than they were a while ago. Furthermore, the overall cost of setting up and deploying GigaSpaces is significantly less than the total overhead for using specific products to tackle our various needs (compared to a traditional system, the cost of setting up e.g. MySQL+RHCS+client configuration; more likely we’d have had to use some sort of 3rd party graph storage, clustering and persistence solution)Devs: working against GigaSpacesis considerably harder than vanilla, commonplace RDBMS. To counter the barrier of entry we modeled our organization so that a core team of developers handle graph storage and data analysis, with most other teams either integrating with this subsystem or handling their own requirements with regular Hibernate/NHibernate over MySQL.Hard to handle migration paths, zero-time deployment and schema evolution. Features in 8.0 should help remedy the situation (cue Nati Shalom)