ksqlDB: Building Consciousness on Real Time Eventsconfluent
Speaker: Gnanaguru (Guru) Sattanathan, Systems Engineer, Confluent
From simple data processing to complex real-time event processing ksqlDB simplifies it all. Yes, ksqlDB is the streaming SQL engine that enables real-time data processing against Apache Kafka. It provides an easy-to-use, yet powerful interactive SQL interface for stream processing on Kafka.In this session lets build few ksqlDB use cases on the fly to understand how it is done and also discuss how you can get started with stream processing on your own.
Highlights:
- Fundamentals of Real-time Stream Processing
- ksqlDB Intro
- ksqlDB Recipes - Simple hands-on exercises
https://www.meetup.com/Chennai-Kafka/events/266140963/
Application Load Balancer and the integration with AutoScaling and ECS - Pop-...Amazon Web Services
Classic Load Balancer and Application Load Balancer automatically distributes incoming application traffic across multiple Amazon EC2 instances for fault tolerance and load distribution. In this session, we go into detail about the load balancers configuration and day-to-day management, as well as its use in conjunction with Auto Scaling ad ECS. We explain how to make decisions about the service and share best practices and useful tips for success.
ksqlDB: Building Consciousness on Real Time Eventsconfluent
Speaker: Gnanaguru (Guru) Sattanathan, Systems Engineer, Confluent
From simple data processing to complex real-time event processing ksqlDB simplifies it all. Yes, ksqlDB is the streaming SQL engine that enables real-time data processing against Apache Kafka. It provides an easy-to-use, yet powerful interactive SQL interface for stream processing on Kafka.In this session lets build few ksqlDB use cases on the fly to understand how it is done and also discuss how you can get started with stream processing on your own.
Highlights:
- Fundamentals of Real-time Stream Processing
- ksqlDB Intro
- ksqlDB Recipes - Simple hands-on exercises
https://www.meetup.com/Chennai-Kafka/events/266140963/
Application Load Balancer and the integration with AutoScaling and ECS - Pop-...Amazon Web Services
Classic Load Balancer and Application Load Balancer automatically distributes incoming application traffic across multiple Amazon EC2 instances for fault tolerance and load distribution. In this session, we go into detail about the load balancers configuration and day-to-day management, as well as its use in conjunction with Auto Scaling ad ECS. We explain how to make decisions about the service and share best practices and useful tips for success.
ksqlDB: A Stream-Relational Database Systemconfluent
Speaker: Matthias J. Sax, Software Engineer, Confluent
ksqlDB is a distributed event streaming database system that allows users to express SQL queries over relational tables and event streams. The project was released by Confluent in 2017 and is hosted on Github and developed with an open-source spirit. ksqlDB is built on top of Apache Kafka®, a distributed event streaming platform. In this talk, we discuss ksqlDB’s architecture that is influenced by Apache Kafka and its stream processing library, Kafka Streams. We explain how ksqlDB executes continuous queries while achieving fault tolerance and high vailability. Furthermore, we explore ksqlDB’s streaming SQL dialect and the different types of supported queries.
Matthias J. Sax is a software engineer at Confluent working on ksqlDB. He mainly contributes to Kafka Streams, Apache Kafka's stream processing library, which serves as ksqlDB's execution engine. Furthermore, he helps evolve ksqlDB's "streaming SQL" language. In the past, Matthias also contributed to Apache Flink and Apache Storm and he is an Apache committer and PMC member. Matthias holds a Ph.D. from Humboldt University of Berlin, where he studied distributed data stream processing systems.
https://db.cs.cmu.edu/events/quarantine-db-talk-2020-confluent-ksqldb-a-stream-relational-database-system/
KafkaConsumer - Decoupling Consumption and Processing for Better Resource Uti...confluent
When working with KafkaConsumer, we usually employ single thread both for reading and processing of messages. KafkaConsumer is not thread-safe, so using single thread fits in well. Downside of this approach is that you are limited to single thread for processing messages.
By decoupling consumption and processing, we can achieve processing parallelization with single consumer and get the most out of multi-core CPU architectures available today. While this can be very useful in certain use-case scenarios, it's not trivial to implement.
How do we use multiple threads with KafkaConsumer which is not thread safe? How do we react to consumer group rebalancing? Can we get desired processing and ordering guarantees? In this talk we 'll try to answer these questions and explore challenges we face on our path.
Big Data means big hardware, and the less of it we can use to do the job properly, the better the bottom line. Apache Kafka makes up the core of our data pipelines at many organizations, including LinkedIn, and we are on a perpetual quest to squeeze as much as we can out of our systems, from Zookeeper, to the brokers, to the various client applications. This means we need to know how well the system is running, and only then can we start turning the knobs to optimize it. In this talk, we will explore how best to monitor Kafka and its clients to assure they are working well. Then we will dive into how to get the best performance from Kafka, including how to pick hardware and the effect of a variety of configurations in both the broker and clients. We’ll also talk about setting up Kafka for no data loss.
Northwestern Mutual Journey – Transform BI Space to CloudDatabricks
The volume of available data is growing by the second (to an estimated 175 zetabytes by 2025), and it is becoming increasingly granular in its information. With that change every organization is moving towards building a data driven culture. We at Northwestern Mutual share similar story of driving towards making data driven decisions to improve both efficiency and effectiveness. Legacy system analysis revealed bottlenecks, excesses, duplications etc. Based on ever growing need to analyze more data our BI Team decided to make a move to more modern, scalable, cost effective data platform. As a financial company, data security is as important as ingestion of data. In addition to fast ingestion and compute we would need a solution that can support column level encryption, Role based access to different teams from our datalake.
In this talk we describe our journey to move 100’s of ELT jobs from current MSBI stack to Databricks and building a datalake (using Lakehouse). How we reduced our daily data load time from 7 hours to 2 hours with capability to ingest more data. Share our experience, challenges, learning, architecture and design patterns used while undertaking this huge migration effort. Different sets of tools/frameworks built by our engineers to help ease the learning curve that our non-Apache Spark engineers would have to go through during this migration. You will leave this session with more understand on what it would mean for you and your organization if you are thinking about migrating to Apache Spark/Databricks.
3 Things to Learn About:
-How Kudu is able to fill the analytic gap between HDFS and Apache HBase
-The trade-offs between real-time transactional access and fast analytic performance
-How Kudu provides an option to achieve fast scans and random access from a single API
Kafka Tutorial - basics of the Kafka streaming platformJean-Paul Azar
Introduction to Kafka streaming platform. Covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example. Lastly, we added some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have started to expand on the Java examples to correlate with the design discussion of Kafka. We have also expanded on the Kafka design section and added references.
Watch this talk here: https://www.confluent.io/online-talks/how-apache-kafka-works-on-demand
Pick up best practices for developing applications that use Apache Kafka, beginning with a high level code overview for a basic producer and consumer. From there we’ll cover strategies for building powerful stream processing applications, including high availability through replication, data retention policies, producer design and producer guarantees.
We’ll delve into the details of delivery guarantees, including exactly-once semantics, partition strategies and consumer group rebalances. The talk will finish with a discussion of compacted topics, troubleshooting strategies and a security overview.
This session is part 3 of 4 in our Fundamentals for Apache Kafka series.
Here at Veruscript, we have many edge case scenarios where we need fine-grained access controls in our academic journal publishing platform.
Therefore performing authorisation to a resource by analysing any number of arbitrary attributes allows for the application to scale appropriately. Known as Attribute-Based Access Control (ABAC), these attributes are evaluated regardless of context; This could be username, role, organisation, domain, time-of-day, country, is the Queen of England, because the sky is blue, etc.
It is why Security Voters are the recommended way to check for user permissions in Symfony applications. Security Voters provide a mechanism that has a small learning curve to set up these fine-grained restrictions in Symfony applications using attributes.
In the simplest case, only a minimal amount of setup and configuration is required, the main advantage over ACLs. In the most complex case, policies can be added or modified without significant changes to the codebase.
The talk will compare different access control paradigms: ABAC, RBAC and ACL, and will look into detail one specification for ABAC - Extensible Access Control Markup Language (XACML) and how this might be implemented in Symfony, for those considering a more "enterprise" use of Security Voters.
Can and should Apache Kafka replace a database? How long can and should I store data in Kafka? How can I query and process data in Kafka? These are common questions that come up more and more. This session explains the idea behind databases and different features like storage, queries, transactions, and processing to evaluate when Kafka is a good fit and when it is not.
The discussion includes different Kafka-native add-ons like Tiered Storage for long-term, cost-efficient storage and ksqlDB as event streaming database. The relation and trade-offs between Kafka and other databases are explored to complement each other instead of thinking about a replacement. This includes different options for pull and push-based bi-directional integration.
Key takeaways:
- Kafka can store data forever in a durable and high available manner
- Kafka has different options to query historical data
- Kafka-native add-ons like ksqlDB or Tiered Storage make Kafka more powerful than ever before to store and process data
- Kafka does not provide transactions, but exactly-once semantics
- Kafka is not a replacement for existing databases like MySQL, MongoDB or Elasticsearch
- Kafka and other databases complement each other; the right solution has to be selected for a problem
- Different options are available for bi-directional pull and push-based integration between Kafka and databases to complement each other
Video Recording:
https://youtu.be/7KEkWbwefqQ
Blog post:
https://www.kai-waehner.de/blog/2020/03/12/can-apache-kafka-replace-database-acid-storage-transactions-sql-nosql-data-lake/
In this slide deck we show how to implement custom Kafka Serializer for Producer. We then show how failover works configuring when broker/topic config min.insync.replicas, and Producer config acks (0, 1, -1, none, leader, all).
Then tutorial show how to implement Kafka producer batching and compression. Then use Producer metrics API to see how batching and compression improves throughput. Then this tutorial covers using retires and timeouts, and tested that it works. It explains how the setup of max inflight messages and retry back off work and when to use and not use inflight messaging.
It goes on to who how to implement a ProducerInterceptor. Then lastly, it shows how to implement a custom Kafka partitioner to implement a priority queue for important records. Through many of the step by step examples, this tutorial shows how to use some of the Kafka tools to do replication verification, and inspect the topic partition leadership status.
ksqlDB: A Stream-Relational Database Systemconfluent
Speaker: Matthias J. Sax, Software Engineer, Confluent
ksqlDB is a distributed event streaming database system that allows users to express SQL queries over relational tables and event streams. The project was released by Confluent in 2017 and is hosted on Github and developed with an open-source spirit. ksqlDB is built on top of Apache Kafka®, a distributed event streaming platform. In this talk, we discuss ksqlDB’s architecture that is influenced by Apache Kafka and its stream processing library, Kafka Streams. We explain how ksqlDB executes continuous queries while achieving fault tolerance and high vailability. Furthermore, we explore ksqlDB’s streaming SQL dialect and the different types of supported queries.
Matthias J. Sax is a software engineer at Confluent working on ksqlDB. He mainly contributes to Kafka Streams, Apache Kafka's stream processing library, which serves as ksqlDB's execution engine. Furthermore, he helps evolve ksqlDB's "streaming SQL" language. In the past, Matthias also contributed to Apache Flink and Apache Storm and he is an Apache committer and PMC member. Matthias holds a Ph.D. from Humboldt University of Berlin, where he studied distributed data stream processing systems.
https://db.cs.cmu.edu/events/quarantine-db-talk-2020-confluent-ksqldb-a-stream-relational-database-system/
KafkaConsumer - Decoupling Consumption and Processing for Better Resource Uti...confluent
When working with KafkaConsumer, we usually employ single thread both for reading and processing of messages. KafkaConsumer is not thread-safe, so using single thread fits in well. Downside of this approach is that you are limited to single thread for processing messages.
By decoupling consumption and processing, we can achieve processing parallelization with single consumer and get the most out of multi-core CPU architectures available today. While this can be very useful in certain use-case scenarios, it's not trivial to implement.
How do we use multiple threads with KafkaConsumer which is not thread safe? How do we react to consumer group rebalancing? Can we get desired processing and ordering guarantees? In this talk we 'll try to answer these questions and explore challenges we face on our path.
Big Data means big hardware, and the less of it we can use to do the job properly, the better the bottom line. Apache Kafka makes up the core of our data pipelines at many organizations, including LinkedIn, and we are on a perpetual quest to squeeze as much as we can out of our systems, from Zookeeper, to the brokers, to the various client applications. This means we need to know how well the system is running, and only then can we start turning the knobs to optimize it. In this talk, we will explore how best to monitor Kafka and its clients to assure they are working well. Then we will dive into how to get the best performance from Kafka, including how to pick hardware and the effect of a variety of configurations in both the broker and clients. We’ll also talk about setting up Kafka for no data loss.
Northwestern Mutual Journey – Transform BI Space to CloudDatabricks
The volume of available data is growing by the second (to an estimated 175 zetabytes by 2025), and it is becoming increasingly granular in its information. With that change every organization is moving towards building a data driven culture. We at Northwestern Mutual share similar story of driving towards making data driven decisions to improve both efficiency and effectiveness. Legacy system analysis revealed bottlenecks, excesses, duplications etc. Based on ever growing need to analyze more data our BI Team decided to make a move to more modern, scalable, cost effective data platform. As a financial company, data security is as important as ingestion of data. In addition to fast ingestion and compute we would need a solution that can support column level encryption, Role based access to different teams from our datalake.
In this talk we describe our journey to move 100’s of ELT jobs from current MSBI stack to Databricks and building a datalake (using Lakehouse). How we reduced our daily data load time from 7 hours to 2 hours with capability to ingest more data. Share our experience, challenges, learning, architecture and design patterns used while undertaking this huge migration effort. Different sets of tools/frameworks built by our engineers to help ease the learning curve that our non-Apache Spark engineers would have to go through during this migration. You will leave this session with more understand on what it would mean for you and your organization if you are thinking about migrating to Apache Spark/Databricks.
3 Things to Learn About:
-How Kudu is able to fill the analytic gap between HDFS and Apache HBase
-The trade-offs between real-time transactional access and fast analytic performance
-How Kudu provides an option to achieve fast scans and random access from a single API
Kafka Tutorial - basics of the Kafka streaming platformJean-Paul Azar
Introduction to Kafka streaming platform. Covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example. Lastly, we added some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have started to expand on the Java examples to correlate with the design discussion of Kafka. We have also expanded on the Kafka design section and added references.
Watch this talk here: https://www.confluent.io/online-talks/how-apache-kafka-works-on-demand
Pick up best practices for developing applications that use Apache Kafka, beginning with a high level code overview for a basic producer and consumer. From there we’ll cover strategies for building powerful stream processing applications, including high availability through replication, data retention policies, producer design and producer guarantees.
We’ll delve into the details of delivery guarantees, including exactly-once semantics, partition strategies and consumer group rebalances. The talk will finish with a discussion of compacted topics, troubleshooting strategies and a security overview.
This session is part 3 of 4 in our Fundamentals for Apache Kafka series.
Here at Veruscript, we have many edge case scenarios where we need fine-grained access controls in our academic journal publishing platform.
Therefore performing authorisation to a resource by analysing any number of arbitrary attributes allows for the application to scale appropriately. Known as Attribute-Based Access Control (ABAC), these attributes are evaluated regardless of context; This could be username, role, organisation, domain, time-of-day, country, is the Queen of England, because the sky is blue, etc.
It is why Security Voters are the recommended way to check for user permissions in Symfony applications. Security Voters provide a mechanism that has a small learning curve to set up these fine-grained restrictions in Symfony applications using attributes.
In the simplest case, only a minimal amount of setup and configuration is required, the main advantage over ACLs. In the most complex case, policies can be added or modified without significant changes to the codebase.
The talk will compare different access control paradigms: ABAC, RBAC and ACL, and will look into detail one specification for ABAC - Extensible Access Control Markup Language (XACML) and how this might be implemented in Symfony, for those considering a more "enterprise" use of Security Voters.
Can and should Apache Kafka replace a database? How long can and should I store data in Kafka? How can I query and process data in Kafka? These are common questions that come up more and more. This session explains the idea behind databases and different features like storage, queries, transactions, and processing to evaluate when Kafka is a good fit and when it is not.
The discussion includes different Kafka-native add-ons like Tiered Storage for long-term, cost-efficient storage and ksqlDB as event streaming database. The relation and trade-offs between Kafka and other databases are explored to complement each other instead of thinking about a replacement. This includes different options for pull and push-based bi-directional integration.
Key takeaways:
- Kafka can store data forever in a durable and high available manner
- Kafka has different options to query historical data
- Kafka-native add-ons like ksqlDB or Tiered Storage make Kafka more powerful than ever before to store and process data
- Kafka does not provide transactions, but exactly-once semantics
- Kafka is not a replacement for existing databases like MySQL, MongoDB or Elasticsearch
- Kafka and other databases complement each other; the right solution has to be selected for a problem
- Different options are available for bi-directional pull and push-based integration between Kafka and databases to complement each other
Video Recording:
https://youtu.be/7KEkWbwefqQ
Blog post:
https://www.kai-waehner.de/blog/2020/03/12/can-apache-kafka-replace-database-acid-storage-transactions-sql-nosql-data-lake/
In this slide deck we show how to implement custom Kafka Serializer for Producer. We then show how failover works configuring when broker/topic config min.insync.replicas, and Producer config acks (0, 1, -1, none, leader, all).
Then tutorial show how to implement Kafka producer batching and compression. Then use Producer metrics API to see how batching and compression improves throughput. Then this tutorial covers using retires and timeouts, and tested that it works. It explains how the setup of max inflight messages and retry back off work and when to use and not use inflight messaging.
It goes on to who how to implement a ProducerInterceptor. Then lastly, it shows how to implement a custom Kafka partitioner to implement a priority queue for important records. Through many of the step by step examples, this tutorial shows how to use some of the Kafka tools to do replication verification, and inspect the topic partition leadership status.
The Brand Center caters to the Brand Manager. Whether you're a network brand, an international trademark or a high potential brand, the Brand Center helps you centralize all your assets and create a real brand consistency.
The Product Dev Conundrum: To Build or Buy in a Digital World?Aggregage
Any PM or technical leader who’s led the charge of building a digital product knows that product engineering is one of the most expensive elements of business. In most cases, actually building software should be the last avenue that companies explore to deliver great products, as software engineering, data science and product development are complex, uncertain and hard to manage.
This presentation describes a user-centered website design process that reduces risk and aligns your business goals with the goals of your audience. The result is a professional business website that attracts and converts valuable prospects.
Adobe Experience Manager is a platform for managing, delivering, and organizing emerging themes. Its fundamental goal is to provide consumers with meaningful interactions that will help them create identities, fuel demand, and expand their scope.
Community Platform: Choosing the Right One Satya S
How will you go about selecting the best platform out there in the market? Are you selecting a product that has features which can really be utilized? Do you really require the host of features offered by the social networking tools? Get answers to all these questions and much more.
Csharptek tries to excel in delivering Microsoft teams services as we ensure seamless collaboration and communication. Our expertise encompasses setup, customization, and training for leveraging teams' capabilities in enhancing teamwork, productivity, and remote collaboration. benefit from our solutions for efficient meetings, file sharing, and improved connectivity across your organization.
Teams combines chat & collaboration, meetings & calling, and Apps & Workflows into a single app. This gives your teams the tools they need to collaborate, and it offers an extensible platform for building customized solutions.
On their own, many of the innovations in Teams are fairly simple. But taken together, they are incredibly powerful. I love the way threaded conversations are smart enough to know exactly when to collapse previous replies and focus on the latest comments. I love the way Teams brings SharePoint and Office together into an integrated document collaboration experience.
And I love the way my meetings in Teams are just more productive. Pre-meeting preparation is done in context; post-meeting follow-up includes a meeting recording; and the in-meeting experience helps focus attention, drive engagement, and foster inclusion with features including live captions, background blur and the ability to turn physical whiteboard into digital ink.
Only Teams delivers this hub for teamwork and it is built on the strength and scale of Microsoft 365 to provide the enterprise grade security and compliance our customers expect.
Effective Software Product Development -hiddenbrains.pdfphilipthomas428223
The basic steps to building an efficient app for your business needs have been collected in this presentation. Users of today are internet knowledgeable thanks to the pandemic-driven period, where every company expanded into the new app technology. checkout the steps and possible actions we have covered.
Agilion Consulting together with its’ in-house brands brings together over 25 professionals in compatible fields such as client service, project management, usability and user experience, graphic design, development, motion design, search engine optimization and staff solutions.
What is Augmented Reality Image Trackingpavan998932
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Looking for a reliable mobile app development company in Noida? Look no further than Drona Infotech. We specialize in creating customized apps for your business needs.
Visit Us For : https://www.dronainfotech.com/mobile-application-development/
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
1. Why use Frontify?
Acquiring a digital branding solution helps your business increase efficiency,
lower operational costs and stay brand consistent in all projects.
2
3. Single point of truth for all
brand definitions
Single access point for all
media assets (i.e. UI patterns,
templates, etc.)
Easy access and usage for
external partners and agencies
How do I ensure
brand consistency
across various
channels?
(digital and non-digital)
Providing an easily accessible
– central – brand
management platform.
Style Guide Workspace
4. Collaborate with
interdisciplinary teams in
dedicated project rooms.
Accelerate approvals and
handovers in large-scale
projects.
Simplify brand consistency
by having the guidelines right
at hand.
How do I keep my
brand and
marketing teams
efficient?
Implementing a toolset
of choice, to streamline
handovers, approvals and the
whole work process.
Style Guide Workspace
5. Create a unique place with clear
edit options.
Share it with only a few clicks –
including with external partners.
Move your brand platform into
the cloud.
How can I keep brand
guidelines up to date,
and easily share them
without friction?
Keep everything
online – making it
conveniently shareable.
Style Guide Pattern Library Media Library
6. Synchronize your UI patterns
with Frontify.
Make them accessible for
everyone including business
stakeholders.
Stay efficient by applying
the Frontify API – no code
duplication required.
How do I reuse digital
patterns without
having the technical
skills?
Make them available as
the digital part of your Style
Guide and give them context.
Style Guide Pattern Library
7. Use a software with best-in-class
usability.
Simplify your processes by
establishing a central truth for your
brand.
Provide a platform – used by over
1600+ enterprises.
How do I motivate
people to use the latest
Style Guides, assets and
other media?
Present them with a
modern platform with
the best usability on
the market.
Pattern Library Media Library Workspace
Style Guide Brand Portal
8. Retrieve some profound insights
about how our clients enhanced their
brand management, using Frontify.
3
Selected client cases
11. Results
Connecting departments with one
central platform.
Simplified brand governance and
overview of all new visual projects.
Enhanced brand consistency across
key channels.
Rising usage and commitment of
internal and external stakeholders
since launch.
12. Explore more cases
Over 100 large corporations have chosen Frontify as their central brand
platform ensuring brand consistency. Read more about these best practices.
Design System
at MAN
Automotive
A design system for the
digital landscape
ExploreExplore
Digital Asset
Management at Vodafone
Telecommunications
Brand portal in the cloud
Explore
Brand Guidelines at
ProSiebenSat.1
Television
The backbone of rebranding
13. Frontify is a SaaS-based brand management platform based in
St.Gallen, Switzerland designed to facilitate and streamline day-to-day
branding, marketing and development operations.
4
About Frontify