Submit Search
Upload
Spring Batch 2.0
•
34 likes
•
8,408 views
Guido Schmutz
Follow
Technology
Report
Share
Report
Share
1 of 35
Recommended
Spring batch
Spring batch introduction
Spring batch introduction
Alex Fernandez
Spring Batch Introduction
Spring Batch Introduction
Tadaya Tsuyukubo
#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
Introduction to spring batch.
Spring batch
Spring batch
nishasowdri
spring batch overview in Seoul Seminar
Spring batch overivew
Spring batch overivew
Chanyeong Choi
Spring batch overview.
Spring batch
Spring batch
Chandan Kumar Rana
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
Java Hibernate Introduction, Architecture and Example with step by step guidance to run the program especially for students and teachers. Learn More @ http://java2all.com/technology/hibernate
Java Hibernate Programming with Architecture Diagram and Example
Java Hibernate Programming with Architecture Diagram and Example
kamal kotecha
Recommended
Spring batch
Spring batch introduction
Spring batch introduction
Alex Fernandez
Spring Batch Introduction
Spring Batch Introduction
Tadaya Tsuyukubo
#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
Introduction to spring batch.
Spring batch
Spring batch
nishasowdri
spring batch overview in Seoul Seminar
Spring batch overivew
Spring batch overivew
Chanyeong Choi
Spring batch overview.
Spring batch
Spring batch
Chandan Kumar Rana
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
Java Hibernate Introduction, Architecture and Example with step by step guidance to run the program especially for students and teachers. Learn More @ http://java2all.com/technology/hibernate
Java Hibernate Programming with Architecture Diagram and Example
Java Hibernate Programming with Architecture Diagram and Example
kamal kotecha
This is an introduction to Spring Batch Framework. After reading this presentation, you will be able to know how Spring Batch works, and you will be able to download a maven project as an example.
Spring Batch Introduction (and Bitbucket Project)
Spring Batch Introduction (and Bitbucket Project)
Guillermo Daniel Salazar
Aspect oriented programming with Spring Framework. AspectJ support.
Spring Framework - AOP
Spring Framework - AOP
Dzmitry Naskou
Hibernate in Action
Hibernate in Action
Akshay Ballarpure
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Antoine Rey
Hibernate Presentation
Hibernate Presentation
guest11106b
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.
Introduction to SPRING FRAMEWORK
Spring Framework
Spring Framework
nomykk
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
Hibernate presentation
Hibernate presentation
Hibernate presentation
Manav Prasad
In this Java Spring Training session, you will learn Spring – Inversion of Control, Dependency Injection and Bean definitions. Topics covered in this session are: For more information, visit this link: Spring Framework • Core Container • Data Access/Integration • Web Layer • Spring Setup • Key features • Spring Bean • Dependency Injection • Relation between DI and IoC • Spring IoC Containers • Spring DI https://www.mindsmapped.com/courses/software-development/spring-fundamentals-learn-spring-framework-and-spring-boot/
Spring - Part 1 - IoC, Di and Beans
Spring - Part 1 - IoC, Di and Beans
Hitesh-Java
An overview of JPA 2.1 API. Stress is given on Entity Context and how it works as well as different types of relationships.
Java persistence api 2.1
Java persistence api 2.1
Rakesh K. Cherukuri
Spring tutorial for beginners - Learn Java Spring Framework version 3.1.0 starting from environment setup, inversion of control (IoC), dependency injection, bean scopes, bean life cycle, inner beans, autowiring, different modules, aspect oriented programming (AOP), database access (JDBC), Transaction Management, Web MVC framework, Web Flow, Exception handling, EJB integration and Sending email etc.
Spring ppt
Spring ppt
Mumbai Academisc
Découvrez le framework web Spring Boot qui a la cote ! Apprenez comment son système d'auto-configuration fonctionne. Live coding et exemple de migration vers Spring Boot sont de la partie.
Introduction à spring boot
Introduction à spring boot
Antoine Rey
Spring Boot Application. It is easy to create and run spring applications.
Spring Boot
Spring Boot
HongSeong Jeon
Spring Boot Tutorial
Spring Boot Tutorial
Spring Boot Tutorial
Naphachara Rattanawilai
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
It aims to give details about various Spring Core concepts like DI, IoC etc
Spring Framework
Spring Framework
NexThoughts Technologies
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
Communication between Microservices is inherently unreliable. These integration points may produce cascading failures, slow responses, service outages. We will walk through stability patterns like timeouts, circuit breaker, bulkheads and discuss how they improve stability of Microservices.
Stability Patterns for Microservices
Stability Patterns for Microservices
pflueras
This document is about how to Write a CRUD App with Spring Boot Jpa or jdbc. a related example for this document is on github with the following address : https://github.com/ghorbanihamid/SpringBoot_AOP_JPA_Example
Spring boot jpa
Spring boot jpa
Hamid Ghorbani
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
More Related Content
What's hot
This is an introduction to Spring Batch Framework. After reading this presentation, you will be able to know how Spring Batch works, and you will be able to download a maven project as an example.
Spring Batch Introduction (and Bitbucket Project)
Spring Batch Introduction (and Bitbucket Project)
Guillermo Daniel Salazar
Aspect oriented programming with Spring Framework. AspectJ support.
Spring Framework - AOP
Spring Framework - AOP
Dzmitry Naskou
Hibernate in Action
Hibernate in Action
Akshay Ballarpure
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Antoine Rey
Hibernate Presentation
Hibernate Presentation
guest11106b
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.
Introduction to SPRING FRAMEWORK
Spring Framework
Spring Framework
nomykk
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
Hibernate presentation
Hibernate presentation
Hibernate presentation
Manav Prasad
In this Java Spring Training session, you will learn Spring – Inversion of Control, Dependency Injection and Bean definitions. Topics covered in this session are: For more information, visit this link: Spring Framework • Core Container • Data Access/Integration • Web Layer • Spring Setup • Key features • Spring Bean • Dependency Injection • Relation between DI and IoC • Spring IoC Containers • Spring DI https://www.mindsmapped.com/courses/software-development/spring-fundamentals-learn-spring-framework-and-spring-boot/
Spring - Part 1 - IoC, Di and Beans
Spring - Part 1 - IoC, Di and Beans
Hitesh-Java
An overview of JPA 2.1 API. Stress is given on Entity Context and how it works as well as different types of relationships.
Java persistence api 2.1
Java persistence api 2.1
Rakesh K. Cherukuri
Spring tutorial for beginners - Learn Java Spring Framework version 3.1.0 starting from environment setup, inversion of control (IoC), dependency injection, bean scopes, bean life cycle, inner beans, autowiring, different modules, aspect oriented programming (AOP), database access (JDBC), Transaction Management, Web MVC framework, Web Flow, Exception handling, EJB integration and Sending email etc.
Spring ppt
Spring ppt
Mumbai Academisc
Découvrez le framework web Spring Boot qui a la cote ! Apprenez comment son système d'auto-configuration fonctionne. Live coding et exemple de migration vers Spring Boot sont de la partie.
Introduction à spring boot
Introduction à spring boot
Antoine Rey
Spring Boot Application. It is easy to create and run spring applications.
Spring Boot
Spring Boot
HongSeong Jeon
Spring Boot Tutorial
Spring Boot Tutorial
Spring Boot Tutorial
Naphachara Rattanawilai
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
It aims to give details about various Spring Core concepts like DI, IoC etc
Spring Framework
Spring Framework
NexThoughts Technologies
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
Communication between Microservices is inherently unreliable. These integration points may produce cascading failures, slow responses, service outages. We will walk through stability patterns like timeouts, circuit breaker, bulkheads and discuss how they improve stability of Microservices.
Stability Patterns for Microservices
Stability Patterns for Microservices
pflueras
This document is about how to Write a CRUD App with Spring Boot Jpa or jdbc. a related example for this document is on github with the following address : https://github.com/ghorbanihamid/SpringBoot_AOP_JPA_Example
Spring boot jpa
Spring boot jpa
Hamid Ghorbani
What's hot
(20)
Spring Batch Introduction (and Bitbucket Project)
Spring Batch Introduction (and Bitbucket Project)
Spring Framework - AOP
Spring Framework - AOP
Hibernate in Action
Hibernate in Action
Workshop Spring - Session 4 - Spring Batch
Workshop Spring - Session 4 - Spring Batch
Hibernate Presentation
Hibernate Presentation
react redux.pdf
react redux.pdf
Spring Framework
Spring Framework
Spring boot
Spring boot
Hibernate presentation
Hibernate presentation
Spring - Part 1 - IoC, Di and Beans
Spring - Part 1 - IoC, Di and Beans
Java persistence api 2.1
Java persistence api 2.1
Spring ppt
Spring ppt
Introduction à spring boot
Introduction à spring boot
Spring Boot
Spring Boot
Spring Boot Tutorial
Spring Boot Tutorial
Spring Core
Spring Core
Spring Framework
Spring Framework
Introduction to Spring Framework
Introduction to Spring Framework
Stability Patterns for Microservices
Stability Patterns for Microservices
Spring boot jpa
Spring boot jpa
Viewers also liked
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
Viewers also liked
(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
Similar to 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
Similar to 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
More from 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
More from 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
Recently uploaded
When you think of a highly secure meeting environment, do you instantly think 'Microsoft Teams'!? Or do you think about some unknown application, troublesome UI and daunting login process...? If you think the latter - let's change that! In this session Femke will show you how using Teams Premium features can create secure, but also good looking meetings! PRETTY. Make sure your company's brand is represented before, during and after the meeting with Customization policies in place. SECURE. Lets utilize Meeting templates and Sensitivity Labels to protect your meeting and data to prevent sensitive information from being leaked. After this session, you will have a clear understanding of the capabilities of Teams Premium features and how to set up the perfect meeting that suits your organizational requirements!
ECS 2024 Teams Premium - Pretty Secure
ECS 2024 Teams Premium - Pretty Secure
Femke de Vroome
Intrigued by why some of the world's largest companies (Netflix, Google, Cisco, Twitter, Uber etc) are using gRPC? In this demo based talk we delve into the world of gRPC in .Net, what it does and why we should use it. We compare the interface with both Rest and graphQL. We will show you how to implement grpc server-side in .net and in the web. Finally, I will show you how the tooling helps you deliver powerful interfaces and interact with them quickly and simply.
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John Staveley
John Staveley
The Epson EcoTank L3210 is a high-performance and cost-efficient printer designed to meet the printing needs of both home users and small businesses. Equipped with Epson’s revolutionary EcoTank ink tank system, the Epson eliminates the need for traditional ink cartridges, thereby significantly reducing printing costs and plastic waste. With its PrecisionCore technology, this printer delivers sharp, vibrant prints for both documents and photos. Its user-friendly design ensures easy setup and operation, while its compact form factor saves valuable desk space. Whether it’s everyday printing jobs or creative projects, the Epson EcoTank L3210 provides a reliable and eco-friendly printing solution.
Buy Epson EcoTank L3210 Colour Printer Online.pptx
Buy Epson EcoTank L3210 Colour Printer Online.pptx
EasyPrinterHelp
How to differentiate Sales Cloud and CPQ on first glance might be tricky if you do not know where to look and what to look at. You will know :-) Managing the sales process within Salesforce is a common use case that can be managed with standart Sales Cloud. If you want to do entire quoting process you will find out Salesforce CPQ solution exists. What is then the difference if both can handle selling products? You will see comparison of 10 different features, which Sales Cloud and Salesforce CPQ handle differently. Simple question you will always remember if you should consider using Salesforce CPQ will be a cherry on top.
10 Differences between Sales Cloud and CPQ, Blanka Doktorová
10 Differences between Sales Cloud and CPQ, Blanka Doktorová
CzechDreamin
This presentation dives into the practical applications of machine learning within Google's operations, providing a comprehensive overview of how to leverage AI technologies to solve real-world business challenges. Key Points Covered: - Introduction to Machine Learning at Google: Discussion on the role of ML and its evolution in enhancing Google's operational efficiency. - Experience Sharing: Insights into the team's long-term engagement with machine learning projects and the impacts on Google’s operational strategies. - Practical Applications: Real-world examples of ML applications within Google’s daily operations, providing a blueprint to adapt similar strategies. - Challenges and Solutions: Discussion on the challenges faced during the implementation of ML projects and the strategic solutions employed to overcome them. - Future of ML at Google: Insights into future trends in machine learning at Google and how they plan to continue integrating AI into their ecosystem.
Strategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering Teams
UXDXConf
A talk given by Julian Hyde at the San Francisco Distributed Systems Meetup on May 22, 2024.
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Julian Hyde
PLAI is the Italian Accelerator igniting the growth of innovative Startups and nurturing a community of talents in the Generative AI field.
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. Startups
Stefano
Screen flow is a powerful automation tool that is commonly designed for internal and external users. However, what about the guest users? We will dive into various methods of launching screen flows and understand how to make them publicly accessible, extending their usability to a broader audience. The presentation will also cover the implementation of security layers and highlight best practices for a smooth and protected user experience. Discover the potential of screen flows beyond conventional use and learn how to leverage them effectively.
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
CzechDreamin
Explore the core of Salesforce success in 'Salesforce Adoption – Metrics, Methods, and Motivation.' We will discuss essential metrics, effective methods to drive adoption, and the driving force behind user engagement and explore strategies for onboarding, training, and continuous support that empower users to navigate the platform seamlessly. By leveraging these tools, you can effectively measure adoption against your company’s goals and create an environment where users not only adopt Salesforce but actively contribute to its ongoing success.
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
CzechDreamin
This is a powerpoint that features Microsoft Teams Devices and everything that is new including updates to its software and devices for April 2024
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024
Stephanie Beckett
Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “Enterprise Knowledge Graphs: The Importance of Semantics” on May 9, 2024, at the annual Data Summit in Boston. In her presentation, Hedden describes the components of an enterprise knowledge graph and provides further insight into the semantic layer – or knowledge model – component, which includes an ontology and controlled vocabularies, such as taxonomies, for controlled metadata. While data experts tend to focus on the graph database components (RDF triple store or a label property graph), Hedden emphasizes they should not overlook the importance of the semantic layer.
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge
The Epson EcoTank L3210 is a high-performance and cost-efficient printer designed to meet the printing needs of both home users and small businesses. Equipped with Epson’s revolutionary EcoTank ink tank system, the Epson eliminates the need for traditional ink cartridges, thereby significantly reducing printing costs and plastic waste. With its PrecisionCore technology, this printer delivers sharp, vibrant prints for both documents and photos. Its user-friendly design ensures easy setup and operation, while its compact form factor saves valuable desk space. Whether it’s everyday printing jobs or creative projects, the Epson EcoTank L3210 provides a reliable and eco-friendly printing solution.
Buy Epson EcoTank L3210 Colour Printer Online.pdf
Buy Epson EcoTank L3210 Colour Printer Online.pdf
EasyPrinterHelp
FIDO Taipei Workshop: Securing the Edge with FDO
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
FIDO Alliance
Welcome to UiPath Test Automation using UiPath Test Suite series part 2. In this session, we will cover API test automation along with a web automation demo. Topics covered: Test Automation introduction API Example of API automation Web automation demonstration Speaker Pathrudu Chintakayala, Associate Technical Architect @Yash and UiPath MVP Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2
DianaGray10
The presentation underscores the strategic advantage of treating design systems not just as technical assets but as vital business components that require thoughtful management, robust planning, and strategic alignment with organizational goals. Key Points Covered: - Understanding Design Systems as Business Entities: Conceptualizing design systems as internal business entities can streamline their integration and evolution within a company. - Adoption and Expansion: Elaborating on the importance of tactical adoption across organizational structures, enhancing product suites to cater to user needs and broadening scope to mobile and content authoring solutions. - Data-Driven Development: Utilizing data insights for component development ensures that resources are allocated to create valuable, widely used features. - Financial Modeling for Design Systems: Developing sustainable funding models is crucial for long-term support and success of design systems. - Promoting Internal Buy-In: Stressing on strategies for promoting design systems within the organization to increase engagement and investment from internal stakeholders.
A Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System Strategy
UXDXConf
This talk offers actionable insights at an executive level for enhancing productivity and refining your portfolio management approach to propel your organization to greater heights. Key Points Covered: 1. Experience Transformation: - The core challenge remains consistent across organizations: converting budget into user-centric designs. - Strategies for deploying design resources effectively in both startups and large enterprises. 2. Strategic Frameworks: - Introduction to the "Ziggurat of Impact" model, detailing layers from basic system interactions to comprehensive customer experiences. - Practical insights on creating frameworks that scale with organizational complexity. 3. Organizational Impact: - Real-world examples of navigating design in large settings, focusing on the synthesis of consumer products and customer experiences. - Emphasis on the importance of designing systems that directly influence customer interactions. 4. Design Execution: - Detailed walkthrough of organizational layers affecting design execution, from touchpoints and customer activities to shared capabilities. - How to ensure design influences both the micro and macro aspects of customer interactions. 5. Measurement and Adaptation: - Techniques for measuring the impact of design decisions and adapting strategies based on data-driven insights. - The critical role of continuous improvement and feedback in refining customer experiences.
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for Success
UXDXConf
This talk focuses on the practical aspects of integrating various telephony systems with Salesforce, drawing on examples from implementations in the Czech scene. It aims to inform attendees about the spectrum of telephony solutions available, from small to large scale, and their compatibility with Salesforce. The presentation will highlight key considerations for selecting a telephony provider that integrates smoothly with Salesforce, including important questions to support the decision-making process. It will also discuss methods for integrating existing telephony systems with Salesforce, aimed at companies contemplating or in the process of adopting this CRM platform. The discussion is designed to provide a straightforward overview of the steps and considerations involved in telephony and Salesforce integration, with an emphasis on functionality, compatibility, and the practical experiences of Czech companies.
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
CzechDreamin
This is the official company presentation of IoT Analytics GmbH, a leading global provider of market insights and strategic business intelligence for the IoT, AI, Cloud, Edge, and Industry 4.0. We are trusted by 1000+ leading companies around the world for our market insights, including globally leading software, telecommunications, consulting, semiconductor, and industrial players.
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024
IoTAnalytics
FIDO Taipei Workshop: Securing the Edge with FDO
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FIDO Alliance
ScyllaDB has the potential to deliver impressive performance and scalability. The better you understand how it works, the more you can squeeze out of it. But before you squeeze, make sure you know what to monitor! Watch our experienced Postgres developer work through monitoring and performance strategies that help him understand what mistakes he’s made moving to NoSQL. And learn with him as our database performance expert offers friendly guidance on how to use monitoring and performance tuning to get his sample Rust application on the right track. This webinar focuses on using monitoring and performance tuning to discover and correct mistakes that commonly occur when developers move from SQL to NoSQL. For example: - Common issues getting up and running with the monitoring stack - Using the CQL optimizations dashboard - Common issues causing high latency in a node - Common issues causing replica imbalance - What a healthy system looks like in terms of memory - Key metrics to keep an eye on This isn’t “Death-by-Powerpoint.” We’ll walk through problems encountered while migrating a real application from Postgres to ScyllaDB – and try to fix them live as well.
Optimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through Observability
ScyllaDB
Recently uploaded
(20)
ECS 2024 Teams Premium - Pretty Secure
ECS 2024 Teams Premium - Pretty Secure
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John Staveley
Buy Epson EcoTank L3210 Colour Printer Online.pptx
Buy Epson EcoTank L3210 Colour Printer Online.pptx
10 Differences between Sales Cloud and CPQ, Blanka Doktorová
10 Differences between Sales Cloud and CPQ, Blanka Doktorová
Strategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering Teams
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. Startups
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024
Buy Epson EcoTank L3210 Colour Printer Online.pdf
Buy Epson EcoTank L3210 Colour Printer Online.pdf
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2
A Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System Strategy
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for Success
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
Optimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through Observability
Spring Batch 2.0
1.
Spring Batch 2.0
Overview Guido Schmutz Technology Manager [email_address] Zurich, 18.3.2009
2.
3.
4.
5.
6.
Item Oriented Processing
7.
8.
Spring Batch: Layered
Architecture
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Demo
20.
21.
22.
Spring Batch in
Trivadis Integration Architecture Blueprint
23.
24.
25.
26.
27.
28.
29.
30.
31.
Available Item Readers
32.
Available Item Writers
33.
34.
35.
Thank you! ?
www.trivadis.com