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Spring Batch 2.0
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Recommandé
Spring batch
Spring batch introduction
Spring batch introduction
Alex Fernandez
#Let's dream with us #Spring Batch分散処理、並列処理
Java spring batch
Java spring batch
furuCRM株式会社 CEO/Dreamforce Vietnam Founder
Spring Batch Introduction
Spring Batch Introduction
Tadaya Tsuyukubo
spring batch overview in Seoul Seminar
Spring batch overivew
Spring batch overivew
Chanyeong Choi
Introduction to spring batch.
Spring batch
Spring batch
nishasowdri
SpringIO 2015 conference slides about usage of Spring Batch in large enterprises.
Spring batch for large enterprises operations
Spring batch for large enterprises operations
Ignasi González
Aspect oriented programming with Spring Framework. AspectJ support.
Spring Framework - AOP
Spring Framework - AOP
Dzmitry Naskou
Introduction to Spring Boot
Spring Boot
Spring Boot
Jiayun Zhou
Recommandé
Spring batch
Spring batch introduction
Spring batch introduction
Alex Fernandez
#Let's dream with us #Spring Batch分散処理、並列処理
Java spring batch
Java spring batch
furuCRM株式会社 CEO/Dreamforce Vietnam Founder
Spring Batch Introduction
Spring Batch Introduction
Tadaya Tsuyukubo
spring batch overview in Seoul Seminar
Spring batch overivew
Spring batch overivew
Chanyeong Choi
Introduction to spring batch.
Spring batch
Spring batch
nishasowdri
SpringIO 2015 conference slides about usage of Spring Batch in large enterprises.
Spring batch for large enterprises operations
Spring batch for large enterprises operations
Ignasi González
Aspect oriented programming with Spring Framework. AspectJ support.
Spring Framework - AOP
Spring Framework - AOP
Dzmitry Naskou
Introduction to Spring Boot
Spring Boot
Spring Boot
Jiayun Zhou
Spring batch overview.
Spring batch
Spring batch
Chandan Kumar Rana
Explanation of the fundamentals of Redux with additional tips and good practices. Presented in the Munich React Native Meetup, so the sample code is using React Native. Additional code: https://github.com/nacmartin/ReduxIntro
Introduction to Redux
Introduction to Redux
Ignacio Martín
University of Colorado PhD software engineering student Aaron Schram explains the details of creating a web applications using the Spring MVC framework
Spring MVC
Spring MVC
Aaron Schram
This session will be about maintaning the store on client side with redux, And will have more details about state management addressing single source of truth concept
react redux.pdf
react redux.pdf
Knoldus Inc.
DATA ACESS WITH JDBC
Spring jdbc
Spring jdbc
Harshit Choudhary
Spring Boot Tutorial
Spring Boot Tutorial
Spring Boot Tutorial
Naphachara Rattanawilai
A presentation to get stated with Facebook's React Js library. https://facebook.github.io/react/
Introduction to React JS for beginners
Introduction to React JS for beginners
Varun Raj
Spring Boot and REST API
Spring Boot and REST API
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07.pallav
Fundamentals of Spring Framework and an introduction to Spring Core, Web (MVC), Security and Test modules
Introduction to Spring Framework
Introduction to Spring Framework
Serhat Can
Introduction to wonderful Spring Boot framework. Presented by Rasheed (http://se.linkedin.com/pub/rasheed-waraich/46/113/72/) Co-founder Aurora Solutions (http://www.aurorasolutions.io/) & FixTelligent (www.fixtelligent.com)
Spring boot introduction
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Rasheed Waraich
Spring Framework Learning Example code: https://github.com/phengtola/spring-framework-learning
Spring Framework
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tola99
How to write application in Java 8 that do not waste resources and which can maximize effective utilization of CPU/RAM. Comparison of blocking and non-blocking approach for I/O and application services. Based on microservices implementing simple business logic in security/cryptography/payments domain. Demonstration of following aspects: * NIO at all edges of application * popular libraries that support NIO * single instance scalability * performance metrics (incl. throughput and latency) * resources utilization * code readability with CompletableFuture * application maintenance and debugging All above based on our experiences gathered during development of software platforms at Oberthur Technologies R&D Poland.
Practical non blocking microservices in java 8
Practical non blocking microservices in java 8
Michal Balinski
JPA and Hibernate
JPA and Hibernate
elliando dias
Presentation about main features about framework.
Spring data presentation
Spring data presentation
Oleksii Usyk
This is a basic tutorial on Spring core. Best viewed when animations and transitions are supported, e.g., view in MS Powerpoint. So, please try to view it with animation else the main purpose of this presentation will be defeated.
Spring Core
Spring Core
Pushan Bhattacharya
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Antoine Rey
This ppt provide basic understanding regarding Spring Boot. And how to configure Spring Boot application with Hibernate and mysql by using eclipse IDE. Also provides understanding about how to configure Spring Tool Suit (STS) in Eclipse.
Spring boot
Spring boot
Gyanendra Yadav
SpringBoot workshop @ PUC SE Day 2019
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PUC SE Day 2019 - SpringBoot
Josué Neis
What is React Native? How does React Native work? Writing React Native Expo Components, props, and states Component lifecycle Declarative and imperative Event handling User input Style Layout Data access Publishing your Project
20180518 QNAP Seminar - Introduction to React Native
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Eric Deng
Redux Toolkit - Quick Intro - 2022
Redux Toolkit - Quick Intro - 2022
Redux Toolkit - Quick Intro - 2022
Fabio Biondi
Talk at Java User Group Switzerland in Zürich
Spring Batch - Lessons Learned out of a real life banking system.
Spring Batch - Lessons Learned out of a real life banking system.
Raffael Schmid
Presentation on J2EE batch process design, tuning and performance.
J2EE Batch Processing
J2EE Batch Processing
Chris Adkin
Contenu connexe
Tendances
Spring batch overview.
Spring batch
Spring batch
Chandan Kumar Rana
Explanation of the fundamentals of Redux with additional tips and good practices. Presented in the Munich React Native Meetup, so the sample code is using React Native. Additional code: https://github.com/nacmartin/ReduxIntro
Introduction to Redux
Introduction to Redux
Ignacio Martín
University of Colorado PhD software engineering student Aaron Schram explains the details of creating a web applications using the Spring MVC framework
Spring MVC
Spring MVC
Aaron Schram
This session will be about maintaning the store on client side with redux, And will have more details about state management addressing single source of truth concept
react redux.pdf
react redux.pdf
Knoldus Inc.
DATA ACESS WITH JDBC
Spring jdbc
Spring jdbc
Harshit Choudhary
Spring Boot Tutorial
Spring Boot Tutorial
Spring Boot Tutorial
Naphachara Rattanawilai
A presentation to get stated with Facebook's React Js library. https://facebook.github.io/react/
Introduction to React JS for beginners
Introduction to React JS for beginners
Varun Raj
Spring Boot and REST API
Spring Boot and REST API
Spring Boot and REST API
07.pallav
Fundamentals of Spring Framework and an introduction to Spring Core, Web (MVC), Security and Test modules
Introduction to Spring Framework
Introduction to Spring Framework
Serhat Can
Introduction to wonderful Spring Boot framework. Presented by Rasheed (http://se.linkedin.com/pub/rasheed-waraich/46/113/72/) Co-founder Aurora Solutions (http://www.aurorasolutions.io/) & FixTelligent (www.fixtelligent.com)
Spring boot introduction
Spring boot introduction
Rasheed Waraich
Spring Framework Learning Example code: https://github.com/phengtola/spring-framework-learning
Spring Framework
Spring Framework
tola99
How to write application in Java 8 that do not waste resources and which can maximize effective utilization of CPU/RAM. Comparison of blocking and non-blocking approach for I/O and application services. Based on microservices implementing simple business logic in security/cryptography/payments domain. Demonstration of following aspects: * NIO at all edges of application * popular libraries that support NIO * single instance scalability * performance metrics (incl. throughput and latency) * resources utilization * code readability with CompletableFuture * application maintenance and debugging All above based on our experiences gathered during development of software platforms at Oberthur Technologies R&D Poland.
Practical non blocking microservices in java 8
Practical non blocking microservices in java 8
Michal Balinski
JPA and Hibernate
JPA and Hibernate
elliando dias
Presentation about main features about framework.
Spring data presentation
Spring data presentation
Oleksii Usyk
This is a basic tutorial on Spring core. Best viewed when animations and transitions are supported, e.g., view in MS Powerpoint. So, please try to view it with animation else the main purpose of this presentation will be defeated.
Spring Core
Spring Core
Pushan Bhattacharya
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Antoine Rey
This ppt provide basic understanding regarding Spring Boot. And how to configure Spring Boot application with Hibernate and mysql by using eclipse IDE. Also provides understanding about how to configure Spring Tool Suit (STS) in Eclipse.
Spring boot
Spring boot
Gyanendra Yadav
SpringBoot workshop @ PUC SE Day 2019
PUC SE Day 2019 - SpringBoot
PUC SE Day 2019 - SpringBoot
Josué Neis
What is React Native? How does React Native work? Writing React Native Expo Components, props, and states Component lifecycle Declarative and imperative Event handling User input Style Layout Data access Publishing your Project
20180518 QNAP Seminar - Introduction to React Native
20180518 QNAP Seminar - Introduction to React Native
Eric Deng
Redux Toolkit - Quick Intro - 2022
Redux Toolkit - Quick Intro - 2022
Redux Toolkit - Quick Intro - 2022
Fabio Biondi
Tendances
(20)
Spring batch
Spring batch
Introduction to Redux
Introduction to Redux
Spring MVC
Spring MVC
react redux.pdf
react redux.pdf
Spring jdbc
Spring jdbc
Spring Boot Tutorial
Spring Boot Tutorial
Introduction to React JS for beginners
Introduction to React JS for beginners
Spring Boot and REST API
Spring Boot and REST API
Introduction to Spring Framework
Introduction to Spring Framework
Spring boot introduction
Spring boot introduction
Spring Framework
Spring Framework
Practical non blocking microservices in java 8
Practical non blocking microservices in java 8
JPA and Hibernate
JPA and Hibernate
Spring data presentation
Spring data presentation
Spring Core
Spring Core
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Spring boot
Spring boot
PUC SE Day 2019 - SpringBoot
PUC SE Day 2019 - SpringBoot
20180518 QNAP Seminar - Introduction to React Native
20180518 QNAP Seminar - Introduction to React Native
Redux Toolkit - Quick Intro - 2022
Redux Toolkit - Quick Intro - 2022
En vedette
Talk at Java User Group Switzerland in Zürich
Spring Batch - Lessons Learned out of a real life banking system.
Spring Batch - Lessons Learned out of a real life banking system.
Raffael Schmid
Presentation on J2EE batch process design, tuning and performance.
J2EE Batch Processing
J2EE Batch Processing
Chris Adkin
Parallel batch processing with spring batch slideshare
Parallel batch processing with spring batch slideshare
Morten Andersen-Gott
This is spring core
Spring tutorial
Spring tutorial
Phuong Le
SPRING TUTORIALS
Spring tutorial
Spring tutorial
mamog
Présentation de Spring Batch
Spring Batch
Spring Batch
victor_gallet
SpringCamp 2013 : About Jdk8
SpringCamp 2013 : About Jdk8
Sangmin Lee
This presentation shows Spring Web Services, Spring Integration and Spring Batch applied to a typical scenario. It walks through the advantages of the technologies and their sweet spots.
Spring Web Service, Spring Integration and Spring Batch
Spring Web Service, Spring Integration and Spring Batch
Eberhard Wolff
Design & Develop Batch Applications in Java/JEE
Design & Develop Batch Applications in Java/JEE
Design & Develop Batch Applications in Java/JEE
Naresh Chintalcheru
아해팀 스터디 스프링 배치
Ahea Team Spring batch
Ahea Team Spring batch
Sunghyun Roh
1. Dear, ... to share my small work and search on Enterprise Architecture Visualization 2.So, my presentation today will be based on those outlines: We will go through Introduction part that has a summary of the goal of my topic, EA, EA tools, problems and soulution The second part will be more concentrated on EA visualization And the conclusion 3. Introduction 4. From this definiton wi see that: -this is the aim of visualization -to make sense and conect all infromation available -with different methods and models. 5. And out of this, the goal of my presentation is to give an overview of visual techniques, methods and approaches in existing EA tools, and to see what we can recommend for further and future development. 6. So, to answer what is EA we must say that the task of EA is to make the interaction between IT and business processes and to represent it. And in this context EA should offer fast response, better efficiency and shorter adaptation time in a globalized world. 7. And, we use EA to manage change and complexity in several steps: 1. To have an overview in current or real situation 2. Connecting business and IT 3. Outsourcing 4. To support projects 5. To support portfolio management 6. Communication with stakeholders 7. Impact analysis and trade-off analysis ( is something cost-effective) .... ...
Enterprise ArchitectureVisualization
Enterprise ArchitectureVisualization
Shkumbin Rrushaj
In this presentation, Tim Fanelli provides an introduction to JSR352 programming, and builds a simple application utilizing the JSR 352 chunk processing model. The sample program presented may be downloaded here: https://www.dropbox.com/s/55fsjt4ylny95hc/MySampleBatch.jar Or, email Tim Fanelli - the contact information is on slide 3!
Three Key Concepts for Understanding JSR-352: Batch Programming for the Java ...
Three Key Concepts for Understanding JSR-352: Batch Programming for the Java ...
timfanelli
JavaQne 2015の発表内容
REST with Spring Boot #jqfk
REST with Spring Boot #jqfk
Toshiaki Maki
좌충우돌 ORM 개발기 | Devon 2012
좌충우돌 ORM 개발기 | Devon 2012
Daum DNA
This talk will explore one of the newest API for Java EE 7, the JSR 352, Batch Applications for the Java Platform. Batch processing is found in nearly every industry when you need to execute a non-interactive, bulk-oriented and long running operation task. A few examples are: financial transactions, billing, inventory management, report generation and so on. The JSR 352 specifies a common set of requirements that every batch application usually needs like: checkpointing, parallelization, splitting and logging. It also provides you with a job specification language and several interfaces that allow you to implement your business logic and interact with the batch container. We are going to live code a real life example batch application, starting with a simple task and then evolve it using the advanced API's until we have a full parallel and checkpointing reader-processor-writer batch. By the end of the session, attendees should be able to understand the use cases of the JSR 352, when to apply it and how to develop a full Java EE Batch Application.
Java EE 7 Batch processing in the Real World
Java EE 7 Batch processing in the Real World
Roberto Cortez
스프링과 JPA를 함께 동작하는 방법, 스프링 데이터 JPA, 스프링 데이터 JPA에서 QueryDSL을 다루는 방법을 설명합니다.
Ksug2015 jpa5 스프링과jpa
Ksug2015 jpa5 스프링과jpa
Younghan Kim
OKKY 세미나에서 발표한 자바 웹 Backend 개발자 학습 로드맵과 소프트웨어 학습 방법에 대해 공유한 자료
소프트웨어 학습 및 자바 웹 개발자 학습 로드맵
소프트웨어 학습 및 자바 웹 개발자 학습 로드맵
Javajigi Jaesung
A talk introducing Microservices with Spring Boot
Microservices with Spring Boot
Microservices with Spring Boot
Joshua Long
스프링 캠프 발표자료 - SpringDataJPA
SpringDataJPA - 스프링 캠프
SpringDataJPA - 스프링 캠프
Younghan Kim
A Sample of a SOA Integration Blueprint based on Oracle SOA Suite
SOA Integration Blueprint with Oracle SOA Suite
SOA Integration Blueprint with Oracle SOA Suite
Matthias Furrer
En vedette
(20)
Spring Batch - Lessons Learned out of a real life banking system.
Spring Batch - Lessons Learned out of a real life banking system.
J2EE Batch Processing
J2EE Batch Processing
Parallel batch processing with spring batch slideshare
Parallel batch processing with spring batch slideshare
Spring tutorial
Spring tutorial
Spring tutorial
Spring tutorial
Spring Batch
Spring Batch
SpringCamp 2013 : About Jdk8
SpringCamp 2013 : About Jdk8
Spring Web Service, Spring Integration and Spring Batch
Spring Web Service, Spring Integration and Spring Batch
Design & Develop Batch Applications in Java/JEE
Design & Develop Batch Applications in Java/JEE
Ahea Team Spring batch
Ahea Team Spring batch
Enterprise ArchitectureVisualization
Enterprise ArchitectureVisualization
Three Key Concepts for Understanding JSR-352: Batch Programming for the Java ...
Three Key Concepts for Understanding JSR-352: Batch Programming for the Java ...
REST with Spring Boot #jqfk
REST with Spring Boot #jqfk
좌충우돌 ORM 개발기 | Devon 2012
좌충우돌 ORM 개발기 | Devon 2012
Java EE 7 Batch processing in the Real World
Java EE 7 Batch processing in the Real World
Ksug2015 jpa5 스프링과jpa
Ksug2015 jpa5 스프링과jpa
소프트웨어 학습 및 자바 웹 개발자 학습 로드맵
소프트웨어 학습 및 자바 웹 개발자 학습 로드맵
Microservices with Spring Boot
Microservices with Spring Boot
SpringDataJPA - 스프링 캠프
SpringDataJPA - 스프링 캠프
SOA Integration Blueprint with Oracle SOA Suite
SOA Integration Blueprint with Oracle SOA Suite
Similaire à Spring Batch 2.0
Arnaud vous propose de découvrir le framework Spring Batch: du Hello World! jusqu'à l'exécution multi-threadée de batch, en passant par la lecture de fichiers CSV et la reprise sur erreur. Les techniques qu'utilise le framework pour lire et écrire efficacement de grands volumes de données e vous seront pas non plus épargnées ! La présentation se base sur une approche problème/solution, avec de nombreux exemples de code et des démos. A la suite de cette présentation, vous saurez si Spring Batch convient à vos problématiques et aurez toutes les cartes en mains pour l'intégrer à vos applications batch.
Spring Batch Workshop
Spring Batch Workshop
lyonjug
PAVONE Espresso Workflow is a workflow management solution, based on Java EE technology. The focus is on team-oriented processes, known as human workflow management. It has an easy-to-use and powerful API.
Workflow Management with Espresso Workflow
Workflow Management with Espresso Workflow
Rolf Kremer
An introduction to jBPM
jBPM 4 BeJUG Event March 20 2009
jBPM 4 BeJUG Event March 20 2009
Tom Baeyens
This is reference for software developers.
Spring Batch
Spring Batch
Jayasree Perilakkalam
SpringBatch intro demo to Domino developers using Mongo DB backend
Intro to SpringBatch NoSQL 2021
Intro to SpringBatch NoSQL 2021
Slobodan Lohja
Advisor Jumpstart: JavaScript
Advisor Jumpstart: JavaScript
dominion
Os Johnson
Os Johnson
oscon2007
This is an adaptation of the presentation given at the SpringOne 2008 conference in Hollywood, FL. It contains some updates on project status, and also information about the recently published book "Spring Python 1.1" This slideshow is licensed under a Creative Commons Attribution 3.0 United States License.
Intro To Spring Python
Intro To Spring Python
gturnquist
jBPM5 presentation at JUDCon
jBPM5 in action - a quickstart for developers
jBPM5 in action - a quickstart for developers
Kris Verlaenen
Session given at the PTJUG (Portugal JUG): A Business Process Management System (BPMS) offers you the capabilities to better manage and streamline your business processes. JBoss jBPM continues its vision in this area by offering a lightweight process engine for executing business processes, combined with the necessary services and tooling to support business processes in their entire life cycles. This allows not only developers but also business users to manage your business processes more efficiently. A lot has happened in the BPM area over the last few years, with the introduction of the BPMN 2.0 standard, the increasing interest in more dynamic and adaptive processes, integration with business rules and event processing, case management, etc. In this session, we will show you how jBPM5 tackles these challenges, discuss migration to this new platform and give you an overview of its most important features.
JBoss Brings More Power to your Business Processes (PTJUG)
JBoss Brings More Power to your Business Processes (PTJUG)
Eric D. Schabell
Workflow demo
Workflow demo
Kamal Raj
...and thus your forms automagically disappeared
...and thus your forms automagically disappeared
Luc Bors
JavaScript introduction presented by Phuong - eXo Portal team.
eXo SEA - JavaScript Introduction Training
eXo SEA - JavaScript Introduction Training
Hoat Le
Introductory presentation to action-based Java MVC framework Struts 2.
Introducing Struts 2
Introducing Struts 2
wiradikusuma
Summary of experiences launching a not-for-profit startup with Google AppEngine for Java
The 90-Day Startup with Google AppEngine for Java
The 90-Day Startup with Google AppEngine for Java
David Chandler
Jsp
Jsp
DSKUMAR G
My talk at MerbCamp in San Diego. I'll apologize up front. ;)
Adventurous Merb
Adventurous Merb
Matt Todd
Given at TechMaine's Java Users Group on Feb 26 2008 Why do we need another build tool when we already have Ant? By focusing on convention over configuration, Maven allows you to declaratively define how your project is built, which reduces a lot of the procedural code that you'd need to implement in every build file if you were using Ant. This, along with Maven's built-in management of repositories for project dependencies, allows you to streamline your build process. Ultimately Maven can reduce the amount of time that would otherwise be wasted hunting down jar files and fiddling with boilerplate build scripts. This presentation covers Maven's core concepts. It introduces the Plugin architecture, and explain how the most popular plugins are used. It also covers the POM concept and how it relates to dependency tracking and repositories.
Demystifying Maven
Demystifying Maven
Mike Desjardins
This is from my series of lectures on C++ and Design Patterns at Interra. This was first presented in 2008
Generalized Functors - Realizing Command Design Pattern in C++
Generalized Functors - Realizing Command Design Pattern in C++
ppd1961
JavaScript
JavaScript
Doncho Minkov
Similaire à Spring Batch 2.0
(20)
Spring Batch Workshop
Spring Batch Workshop
Workflow Management with Espresso Workflow
Workflow Management with Espresso Workflow
jBPM 4 BeJUG Event March 20 2009
jBPM 4 BeJUG Event March 20 2009
Spring Batch
Spring Batch
Intro to SpringBatch NoSQL 2021
Intro to SpringBatch NoSQL 2021
Advisor Jumpstart: JavaScript
Advisor Jumpstart: JavaScript
Os Johnson
Os Johnson
Intro To Spring Python
Intro To Spring Python
jBPM5 in action - a quickstart for developers
jBPM5 in action - a quickstart for developers
JBoss Brings More Power to your Business Processes (PTJUG)
JBoss Brings More Power to your Business Processes (PTJUG)
Workflow demo
Workflow demo
...and thus your forms automagically disappeared
...and thus your forms automagically disappeared
eXo SEA - JavaScript Introduction Training
eXo SEA - JavaScript Introduction Training
Introducing Struts 2
Introducing Struts 2
The 90-Day Startup with Google AppEngine for Java
The 90-Day Startup with Google AppEngine for Java
Jsp
Jsp
Adventurous Merb
Adventurous Merb
Demystifying Maven
Demystifying Maven
Generalized Functors - Realizing Command Design Pattern in C++
Generalized Functors - Realizing Command Design Pattern in C++
JavaScript
JavaScript
Plus de Guido Schmutz
Analytical platforms for PoCs and evaluation can be built in the cloud in an hour - with ready-made setup scripts. But if you put the services together freely, it gets more difficult. The open-source platform-in-a-box "Platys" (https://github.com/TrivadisPF/platys) shows that it is easier for test and PoC environments. In addition to possible uses and examples, we explain services and "just briefly" set up a data lake with a database, event broker, stream processing, blob store, SQL access and data science notebook.
30 Minutes to the Analytics Platform with Infrastructure as Code
30 Minutes to the Analytics Platform with Infrastructure as Code
Guido Schmutz
Today's modern data architectures and the their implementations contain an Event Broker. What are the benefits of placing an Event Broker in a Modern Data (Analytics) Architecture? What exactly is an Event Broker and what capabilities should it provide? Why is Apache Kafka the most popular realisation of an Event Broker? These and many other questions will be answered in this session. The talk will start with a vendor-neutral definition of the capabilities of an Event Broker. Then the session will highlight the different architecture styles which can be supported using an Event Broker (Kafka), such as Streaming Data Integration, Stream Analytics and Decoupled Event-Driven Applications and how can these be combined into a unified architecture, making the Event Broker the central nervous system of an enterprise architecture. We will end with an overview of the Kafka ecosystem and a placement of the various components onto the Modern Data (Analytics) Architecture.
Event Broker (Kafka) in a Modern Data Architecture
Event Broker (Kafka) in a Modern Data Architecture
Guido Schmutz
The concept of "Data Lake" is in everyone's mind today. The idea of storing all the data that accumulates in a company in a central location and making it available sounds very interesting at first. But Data Lake can quickly turn from a clear, beautiful mountain lake into a huge pond, especially if it is inexpertly entrusted with all the source data formats that are common in today's enterprises, such as XML, JSON, CSV or unstructured text data. Who, after some time, still has an overview of which data, which format and how they have developed over different versions? Anyone who wants to help themselves from the Data Lake must ask themselves the same questions over and over again: what information is provided, what data types do they have and how has the content changed over time? Data serialization frameworks such as Apache Avro and Google Protocol Buffer (Protobuf), which enable platform-independent data modeling and data storage, can help. This talk will discuss the possibilities of Avro and Protobuf and show how they can be used in the context of a data lake and what advantages can be achieved. The support on Avro and Protobuf by Big Data and Fast Data platforms is also a topic.
Big Data, Data Lake, Fast Data - Dataserialiation-Formats
Big Data, Data Lake, Fast Data - Dataserialiation-Formats
Guido Schmutz
ksqlDB is a stream processing SQL engine, which allows stream processing on top of Apache Kafka. ksqlDB is based on Kafka Stream and provides capabilities for consuming messages from Kafka, analysing these messages in near-realtime with a SQL like language and produce results again to a Kafka topic. By that, no single line of Java code has to be written and you can reuse your SQL knowhow. This lowers the bar for starting with stream processing significantly. ksqlDB offers powerful capabilities of stream processing, such as joins, aggregations, time windows and support for event time. In this talk I will present how KSQL integrates with the Kafka ecosystem and demonstrate how easy it is to implement a solution using ksqlDB for most part. This will be done in a live demo on a fictitious IoT sample.
ksqlDB - Stream Processing simplified!
ksqlDB - Stream Processing simplified!
Guido Schmutz
For a long time we discuss how much data we can keep in Kafka. Can we store data forever or do we remove data after a while and maybe having the history in a data lake on Object Storage or HDFS? With the advent of Tiered Storage in Confluent Enterprise Platform, storing data much longer in Kafka is much very feasible. So can we replace a traditional data lake with just Kafka? Maybe at least for the raw data? But what about accessing the data, for example using SQL? KSQL allows for processing data in a streaming fashion using an SQL like dialect. But what about reading all data of a topic? You can reset the offset and still use KSQL. But there is another family of products, so-called query engines for Big Data. They originate from the idea of reading Big Data sources such as HDFS, object storage or HBase, using the SQL language. Presto, Apache Drill and Dremio are the most popular solutions in that space. Lately these query engines also added support for Kafka topics as a source of data. With that you can read a topic as a table and join it with information available in other data sources. The idea of course is not real-time streaming analytics but batch analytics directly on the Kafka topic, without having to store it in a big data storage. This talk answers, how well these tools support Kafka as a data source. What serialization formats do they support? Is there some form of predicate push-down supported or do we have to always read the complete topic? How performant is a query against a topic, compared to a query against the same data sitting in HDFS or an object store? And finally, will this allow us to replace our data lake or at least part of it by Apache Kafka?
Kafka as your Data Lake - is it Feasible?
Kafka as your Data Lake - is it Feasible?
Guido Schmutz
Today's modern data architectures and the their implementations contain an Event Hub. What are the benefits of placing an Event Hub in a Modern Data (Analytics) Architecture? What exactly is an Event Hub and what capabilities should it provide? Why is Apache Kafka the most popular realization of an Event Hub? These and many other questions will be answered in this session. The talk will start with a vendor-neutral definition of the capabilities of an Event Hub. Then the session will highlight the different architecture styles which can be supported using an Event Hub (Kafka), such as Streaming Data Integration, Stream Analytics and Decoupled Event-Driven Applications and how can these be combined into a unified architecture, making the Event Hub the central nervous system of an enterprise architecture. We will end with an overview of the Kafka ecosystem and a placement of the various components onto the Modern Data (Analytics) Architecture.
Event Hub (i.e. Kafka) in Modern Data Architecture
Event Hub (i.e. Kafka) in Modern Data Architecture
Guido Schmutz
Apache Kafka is a popular distributed streaming data platform and more and more is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate, ORDS APIs and bridging Kafka with Oracle AQ.
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Guido Schmutz
Today's modern data architectures and the their implementations contain an Event Hub. What are the benefits of placing an Event Hub in a Modern Data (Analytics) Architecture? What exactly is an Event Hub and what capabilities should it provide? Why is Apache Kafka the most popular realization of an Event Hub? These and many other questions will be answered in this session. The talk will start with a vendor-neutral definition of the capabilities of an Event Hub. Then the session will highlight the different architecture styles which can be supported using an Event Hub (Kafka), such as Streaming Data Integration, Stream Analytics and Decoupled Event-Driven Applications and how can these be combined into a unified architecture, making the Event Hub the central nervous system of an enterprise architecture. We will end with an overview of the Kafka ecosystem and a placement of the various components onto the Modern Data (Analytics) Architecture.
Event Hub (i.e. Kafka) in Modern Data (Analytics) Architecture
Event Hub (i.e. Kafka) in Modern Data (Analytics) Architecture
Guido Schmutz
What is a Microservices architecture and how does it differ from a Service-Oriented Architecture? Should you use traditional REST APIs to bind services together? Or is it better to use a richer, more loosely-coupled protocol? This talk will start with quick recap of how we created systems over the past 20 years and how different architectures evolved from it. The talk will show how we piece services together in event driven systems, how we use a distributed log (event hub) to create a central, persistent history of events and what benefits we achieve from doing so. Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk will show the difference between a request-driven and event-driven communication and show when to use which. It highlights how the modern stream processing systems can be used to hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
Building Event Driven (Micro)services with Apache Kafka
Building Event Driven (Micro)services with Apache Kafka
Guido Schmutz
An important underlying concept behind location-based applications is called geofencing. Geofencing is a process that allows acting on users and/or devices who enter/exit a specific geographical area, known as a geo-fence. A geo-fence can be dynamically generated—as in a radius around a point location, or a geo-fence can be a predefined set of boundaries (such as secured areas, buildings, boarders of counties, states or countries). Geofencing lays the foundation for realizing use cases around fleet monitoring, asset tracking, phone tracking across cell sites, connected manufacturing, ride-sharing solutions and many others. GPS tracking tells constantly and in real time where a device is located and forms the stream of events which needs to be analyzed against the much more static set of geo-fences. Many of the use cases mentioned above require low-latency actions taken place, if either a device enters or leaves a geo-fence or when it is approaching such a geo-fence. That’s where streaming data ingestion and streaming analytics and therefore the Kafka ecosystem comes into play. This session will present how location analytics applications can be implemented using Kafka and KSQL & Kafka Streams. It highlights the exiting features available out-of-the-box and then shows how easy it is to extend it by custom defined functions (UDFs). The design of such solution so that it can scale with both an increasing amount of position events as well as geo-fences will be discussed as well.
Location Analytics - Real-Time Geofencing using Apache Kafka
Location Analytics - Real-Time Geofencing using Apache Kafka
Guido Schmutz
Apache Kafka is a popular distributed streaming data platform. A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Data sources flowing into Kafka are often native data streams such as social media streams, telemetry data, financial transactions and many others. But these data stream only contain part of the information. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. To implement new and modern, real-time solutions, an up-to-date view of that information is needed. So how do we make sure that information can flow between the RDBMS and Kafka, so that changes are available in Kafka as soon as possible in near-real-time? This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate and bridging Kafka with Oracle Advanced Queuing (AQ).
Solutions for bi-directional integration between Oracle RDBMS and Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS and Apache Kafka
Guido Schmutz
Slides on the usage of Kafka which I used for the Speed Session at DOAG2019 at our booth.
What is Apache Kafka? Why is it so popular? Should I use it?
What is Apache Kafka? Why is it so popular? Should I use it?
Guido Schmutz
Apache Kafka is a popular distributed streaming data platform. A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Data sources flowing into Kafka are often native data streams such as social media streams, telemetry data, financial transactions and many others. But these data stream only contain part of the information. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. To implement new and modern, real-time solutions, an up-to-date view of that information is needed. So how do we make sure that information can flow between the RDBMS and Kafka, so that changes are available in Kafka as soon as possible in near-real-time? This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate and bridging Kafka with Oracle Advanced Queuing (AQ).
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Guido Schmutz
An important underlying concept behind location-based applications is called geofencing. Geofencing is a process that allows acting on users and/or devices who enter/exit a specific geographical area, known as a geo-fence. A geo-fence can be dynamically generated—as in a radius around a point location, or a geo-fence can be a predefined set of boundaries (such as secured areas, buildings, boarders of counties, states or countries). Geofencing lays the foundation for realizing use cases around fleet monitoring, asset tracking, phone tracking across cell sites, connected manufacturing, ride-sharing solutions and many others. GPS tracking tells constantly and in real time where a device is located and forms the stream of events which needs to be analyzed against the much more static set of geo-fences. Many of the use cases mentioned above require low-latency actions taken place, if either a device enters or leaves a geo-fence or when it is approaching such a geo-fence. That’s where streaming data ingestion and streaming analytics and therefore the Kafka ecosystem comes into play. This session will present how location analytics applications can be implemented using Kafka and KSQL & Kafka Streams. It highlights the exiting features available out-of-the-box and then shows how easy it is to extend it by custom defined functions (UDFs). The design of such solution so that it can scale with both an increasing amount of position events as well as geo-fences will be discussed as well.
Location Analytics Real-Time Geofencing using Kafka
Location Analytics Real-Time Geofencing using Kafka
Guido Schmutz
Most data visualisation solutions today still work on data sources which are stored persistently in a data store, using the so called “data at rest” paradigms. More and more data sources today provide a constant stream of data, from IoT devices to Social Media streams. These data stream publish with high velocity and messages often have to be processed as quick as possible. For the processing and analytics on the data, so called stream processing solutions are available. But these only provide minimal or no visualisation capabilities. One option is to first persist the data into a data store and then use a traditional data visualisation solution to present the data. If latency is not an issue, such a solution might be good enough. An other question is which data store solution is necessary to keep up with the high load on write and read. If it is not an RDBMS but an NoSQL database, then not all traditional visualisation tools might already integrate with the specific data store. An other option is to use a Streaming Visualisation solution. They are specially built for streaming data and often do not support batch data. A much better solution would be to have one tool capable of handling both, batch and streaming data. This talk presents different architecture blueprints for integrating data visualisation into a fast data solutions and then we show how the different blueprints can be implemented by mapping products onto the blueprints.
Streaming Visualisation
Streaming Visualisation
Guido Schmutz
Event Sourcing and CQRS are two popular patterns for implementing a Microservices architectures. With Event Sourcing we do not store the state of an object, but instead store all the events impacting its state. Then to retrieve an object state, we have to read the different events related to a certain object and apply them one by one. CQRS (Command Query Responsibility Segregation) on the other hand is a way to dissociate writes (Command) and reads (Query). Event Sourcing and CQRS are frequently grouped and used together to form something bigger. While it is possible to implement CQRS without Event Sourcing, the opposite is not necessarily correct. In order to implement Event Sourcing, an efficient Event Store is needed. But is that also true when combining Event Sourcing and CQRS? And what is an event store in the first place and what features should it implement? This presentation will first discuss what functionalities an event store should offer and then present how Apache Kafka can be used to implement an event store. But is Kafka good enough or do specific event store solutions such as AxonDB or Event Store provide a better solution?
Kafka as an event store - is it good enough?
Kafka as an event store - is it good enough?
Guido Schmutz
A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Today’s enterprises have their core systems often implemented on top of relational databases, such as the Oracle RDBMS. Implementing a new solution supporting the digital strategy using Kafka and the ecosystem can not always be done completely separate from the traditional legacy solutions. Often streaming data has to be enriched with state data which is held in an RDBMS of a legacy application. It’s important to cache this data in the stream processing solution, so that It can be efficiently joined to the data stream. But how do we make sure that the cache is kept up-to-date, if the source data changes? We can either poll for changes from Kafka using Kafka Connect or let the RDBMS push the data changes to Kafka. But what about writing data back to the legacy application, i.e. an anomaly is detected inside the stream processing solution which should trigger an action inside the legacy application. Using Kafka Connect we can write to a database table or view, which could trigger the action. But this not always the best option. If you have an Oracle RDBMS, there are many other ways to integrate the database with Kafka, such as Advanced Queueing (message broker in the database), CDC through Golden Gate or Debezium, Oracle REST Database Service (ORDS) and more. In this session, we present various blueprints for integrating an Oracle RDBMS with Apache Kafka in both directions and discuss how these blueprints can be implemented using the products mentioned before.
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Guido Schmutz
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures. The right architecture is key for any IT project. This is valid in the case for big data projects as well, but on the other hand there are not yet many standard architectures which have proven their suitability over years. This session discusses different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Event Driven architecture as well as Lambda and Kappa architecture. Each architecture is presented in a vendor- and technology-independent way using a standard architecture blueprint. In a second step, these architecture blueprints are used to show how a given architecture can support certain use cases and which popular open source technologies can help to implement a solution based on a given architecture.
Fundamentals Big Data and AI Architecture
Fundamentals Big Data and AI Architecture
Guido Schmutz
An important underlying concept behind location-based applications is called geofencing. Geofencing is a process that allows acting on users and/or devices who enter/exit a specific geographical area, known as a geo-fence. A geo-fence can be dynamically generated—as in a radius around a point location, or a geo-fence can be a predefined set of boundaries (such as secured areas, buildings, boarders of counties, states or countries). Geofencing lays the foundation for realising use cases around fleet monitoring, asset tracking, phone tracking across cell sites, connected manufacturing, ride-sharing solutions and many others. Many of the use cases mentioned above require low-latency actions taken place, if either a device enters or leaves a geo-fence or when it is approaching such a geo-fence. That’s where streaming data ingestion and streaming analytics and therefore the Kafka ecosystem comes into play. This session will present how location analytics applications can be implemented using Kafka and KSQL & Kafka Streams. It highlights the exiting features available out-of-the-box and then shows how easy it is to extend it by custom defined functions (UDFs).
Location Analytics - Real-Time Geofencing using Kafka
Location Analytics - Real-Time Geofencing using Kafka
Guido Schmutz
Most data visualization solutions today still work on data sources which are stored persistently in a data store, using the so called “data at rest” paradigms. More and more data sources today provide a constant stream of data, from IoT devices to Social Media streams. These data stream publish with high velocity and messages often have to be processed as quick as possible. For the processing and analytics on the data, so called stream processing solutions are available. But these only provide minimal or no visualization capabilities. One option is to first persist the data into a data store and then use a traditional data visualization solution to present the data. If latency is not an issue, such a solution might be good enough. An other question is which data store solution is necessary to keep up with the high load on write and read. If it is not an RDBMS but an NoSQL database, then not all traditional visualization tools might already integrate with the specific data store. An other option is to use a Streaming Visualization solution. This talk presents different architecture blueprints for integrating data visualization into a fast data solutions.
Streaming Visualization
Streaming Visualization
Guido Schmutz
Plus de Guido Schmutz
(20)
30 Minutes to the Analytics Platform with Infrastructure as Code
30 Minutes to the Analytics Platform with Infrastructure as Code
Event Broker (Kafka) in a Modern Data Architecture
Event Broker (Kafka) in a Modern Data Architecture
Big Data, Data Lake, Fast Data - Dataserialiation-Formats
Big Data, Data Lake, Fast Data - Dataserialiation-Formats
ksqlDB - Stream Processing simplified!
ksqlDB - Stream Processing simplified!
Kafka as your Data Lake - is it Feasible?
Kafka as your Data Lake - is it Feasible?
Event Hub (i.e. Kafka) in Modern Data Architecture
Event Hub (i.e. Kafka) in Modern Data Architecture
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Event Hub (i.e. Kafka) in Modern Data (Analytics) Architecture
Event Hub (i.e. Kafka) in Modern Data (Analytics) Architecture
Building Event Driven (Micro)services with Apache Kafka
Building Event Driven (Micro)services with Apache Kafka
Location Analytics - Real-Time Geofencing using Apache Kafka
Location Analytics - Real-Time Geofencing using Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS and Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS and Apache Kafka
What is Apache Kafka? Why is it so popular? Should I use it?
What is Apache Kafka? Why is it so popular? Should I use it?
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Solutions for bi-directional integration between Oracle RDBMS & Apache Kafka
Location Analytics Real-Time Geofencing using Kafka
Location Analytics Real-Time Geofencing using Kafka
Streaming Visualisation
Streaming Visualisation
Kafka as an event store - is it good enough?
Kafka as an event store - is it good enough?
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Fundamentals Big Data and AI Architecture
Fundamentals Big Data and AI Architecture
Location Analytics - Real-Time Geofencing using Kafka
Location Analytics - Real-Time Geofencing using Kafka
Streaming Visualization
Streaming Visualization
Dernier
Read about the journey the Adobe Experience Manager team has gone through in order to become and scale API-first throughout the organisation.
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
Radu Cotescu
Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
apidays
Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
debabhi2
45-60 minute session deck from introducing Google Apps Script to developers, IT leadership, and other technical professionals.
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
wesley chun
Slides from the presentation on Machine Learning for the Arts & Humanities seminar at the University of Bologna (Digital Humanities and Digital Knowledge program)
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
Maria Levchenko
With real-time traffic, hazard alerts, and voice instructions, among others, launching an intuitive taxi app in Brazil is your golden ticket to entrepreneurial success. For more info visit our website : https://www.v3cube.com/uber-clone-portuguese-brazil/
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
V3cube
Discover the advantages of hiring UI/UX design services! Our blog explores how professional design can enhance user experiences, boost brand credibility, and increase customer engagement. Learn about the latest design trends and strategies that can help your business stand out in the digital landscape. Elevate your online presence with Pixlogix's expert UI/UX design services.
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
Pixlogix Infotech
Presented by Mike Hicks
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
sammart93
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Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
DianaGray10
Details
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
vu2urc
Stay safe, grab a drink and join us virtually for our upcoming "GenAI Risks & Security" Meetup to hear about how to uncover critical GenAI risks and vulnerabilities, AI security considerations in every company, and how a CISO should navigate through GenAI Risks.
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
lior mazor
With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
Principled Technologies
Presented by Sergio Licea and John Hendershot
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
wesley chun
My presentation at the Lehigh Carbon Community College (LCCC) NSA GenCyber Cyber Security Day event that is intended to foster an interest in the cyber security field amongst college students.
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
Michael W. Hawkins
How to get Oracle DBA Job as fresher.
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
Remote DBA Services
Copy of the slides presented by Matt Robison to the SFWelly Salesforce user group community on May 2 2024. The audience was truly international with attendees from at least 4 different countries joining online. Matt is an expert in data cloud and this was a brilliant session.
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
Anna Loughnan Colquhoun
These are the slides delivered in a workshop at Data Innovation Summit Stockholm April 2024, by Kristof Neys and Jonas El Reweny.
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Neo4j
Dernier
(20)
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Spring Batch 2.0
1.
Spring Batch 2.0
Overview Guido Schmutz Technology Manager [email_address] Zurich, 18.3.2009
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Item Oriented Processing
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Spring Batch: Layered
Architecture
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Demo
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Spring Batch in
Trivadis Integration Architecture Blueprint
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Available Item Readers
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Available Item Writers
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