This document discusses integrating big data beyond Hadoop. It begins with an introduction and overview of Kai Wähner and his background and expertise. The rest of the document focuses on big data integration, with sections on the challenges of integrating big data, choosing Hadoop as a solution, and different approaches to integration including using open source frameworks, suites, and custom connectors. Throughout there are examples of use cases and how companies are leveraging big data and integration to solve business problems. The overall message is that in order to get full value from data, you need to integrate different sources, and that big data integration approaches have advanced to make this more achievable.
Best Practices for Streaming IoT Data with MQTT and Apache KafkaKai Wähner
Organizations today are looking to stream IoT data to Apache Kafka. However, connecting tens of thousands or even millions of devices over unreliable networks can create some architecture challenges. In this session, we will identify and demo some best practices for implementing a large scale IoT system that can stream MQTT messages to Apache Kafka.
We use HiveMQ as open source MQTT broker to ingest data from IoT devices, ingest the data in real time into an Apache Kafka cluster for preprocessing (using Kafka Streams / KSQL), and model training + inference (using TensorFlow 2.0 and its TensorFlow I/O Kafka plugin).
We leverage additional enterprise components from HiveMQ and Confluent to allow easy operations, scalability and monitoring.
WJAX 2013 Slides online: Big Data beyond Apache Hadoop - How to integrate ALL...Kai Wähner
Big data represents a significant paradigm shift in enterprise technology. Big data radically changes the nature of the data management profession as it introduces new concerns about the volume, velocity and variety of corporate data. Apache Hadoop is the open source defacto standard for implementing big data solutions on the Java platform. Hadoop consists of its kernel, MapReduce, and the Hadoop Distributed Filesystem (HDFS). A challenging task is to send all data to Hadoop for processing and storage (and then get it back to your application later), because in practice data comes from many different applications (SAP, Salesforce, Siebel, etc.) and databases (File, SQL, NoSQL), uses different technologies and concepts for communication (e.g. HTTP, FTP, RMI, JMS), and consists of different data formats using CSV, XML, binary data, or other alternatives. This session shows different open source frameworks and products to solve this challenging task. Learn how to use every thinkable data with Hadoop – without plenty of complex or redundant boilerplate code.
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology.
Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way integrating with various legacy and modern data sources and sinks.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
• The Automotive Industry (and it’s not only Connected Cars)
• Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
• Smart Cities (including citizen health services, communication infrastructure, …)
All these industries and sectors do not have new characteristics and requirements. They require data integration, data correlation or real decoupling, just to name a few, but are now facing massively increased volumes of data.
Real-time messaging solutions have existed for many years. Hundreds of platforms exist for data integration (including ETL and ESB tooling or specific IIoT platforms). Proprietary monoliths monitor plants, telco networks, and other infrastructures for decades in real-time. But now, Kafka combines all the above characteristics in an open, scalable, and flexible infrastructure to operate mission-critical workloads at scale in real-time. And is taking over the world of connecting data.
Apache Kafka for Real-time Supply Chainin the Food and Retail IndustryKai Wähner
Use Cases, Architectures, and Real-World Examples for data in motion and real-time event streaming powered by Apache Kafka across the supply chain and logistics. Case studies and deployments include Baader, Walmart, Migros, Albertsons, Domino's Pizza, Instacart, Grab, Royal Caribbean, and more.
IoT Architectures for Apache Kafka and Event Streaming - Industry 4.0, Digita...Kai Wähner
The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. Whether you are in Healthcare, Telecommunications, Manufacturing, Banking or Retail to name a few industries, there is one key challenge and that's the integration of backend IoT data logs and applications, business services and cloud services to process the data in real time and at scale.
In this talk, we will be sharing how Kafka has become the leading technology used throughout the business to provide Real Time Event Streaming. Explore real life use cases of Kafka Connect, Kafka Streams and KSQL independent of the data deployment be it on a private or public Cloud, On Premise or at the Edge.
Audi - Connected car infrastructure
Robert Bosch Power Tools - Track and Trace of devices and people at construction areas
Deutsche Bahn - Customer 360 for train timetable updates
E.ON - IoT Streaming Platform to integrate and build smart home, smart building and smart grid infrastructures
Simplified Machine Learning Architecture with an Event Streaming Platform (Ap...Kai Wähner
Machine Learning is separated into model training and model inference. ML frameworks typically load historical data from a data store like HDFS or S3 to train models. This talk shows how you can completely avoid such a data store by ingesting streaming data directly via Apache Kafka from any source system into TensorFlow for model training and model inference using the capabilities of “TensorFlow I/O” add-on.
The talk compares this modern streaming architecture to traditional batch and big data alternatives and explains benefits like the simplified architecture, the ability of reprocessing events in the same order for training different models, and the possibility to build a scalable, mission-critical, real time ML architecture with muss less headaches and problems.
Key takeaways for the audience
• Scalable open source Machine Learning infrastructure
• Streaming ingestion into TensorFlow without the need for another data store like HDFS or S3 (leveraging TensorFlow I/O and its Kafka plugin)
• Stream Processing using analytic models in mission-critical deployments to act in Real Time
• Learn how Apache Kafka open source ecosystem including Kafka Connect, Kafka Streams and KSQL help to build, deploy, score and monitor analytic models
• Comparison and trade-offs between this modern streaming approach and traditional batch model training infrastructures
Apache Kafka, Tiered Storage and TensorFlow for Streaming Machine Learning wi...Kai Wähner
Don’t underestimate the Hidden Technical Debt in Machine Learning Systems.
Leverage Apache Kafka’s open ecosystem as a scalable and flexible Event Streaming Platform to build one pipeline for real-time and batch use cases.
Use Streaming Machine Learning with Apache Kafka, Tiered Storage, and TensorFlow IO to simplify your big data architecture.
Tiered Storage for Kafka provides:
- one platform for all data processing
- an event-based source of truth for materialized views
- no need for a pipeline between Kafka and a Data Lake like Hadoop
Benefits:
- cost reduction
- long-term backup
- performance isolation (real-time and historical analysis in the same cluster)
Use Cases for Reprocessing Historical Events:
- New consumer application
- Error-handling
- Compliance / regulatory processing
- Query and analyze existing events
- Model training
Real-Life Use Cases & Architectures for Event Streaming with Apache KafkaKai Wähner
Streaming all over the World: Real-Life Use Cases & Architectures for Event Streaming with Apache Kafka.
Learn about various case studies for event streaming with Apache Kafka across industries. The talk explores architectures for real-world deployments from Audi, BMW, Disney, Generali, Paypal, Tesla, Unity, Walmart, William Hill, and more. Use cases include fraud detection, mainframe offloading, predictive maintenance, cybersecurity, edge computing, track&trace, live betting, and much more.
Best Practices for Streaming IoT Data with MQTT and Apache KafkaKai Wähner
Organizations today are looking to stream IoT data to Apache Kafka. However, connecting tens of thousands or even millions of devices over unreliable networks can create some architecture challenges. In this session, we will identify and demo some best practices for implementing a large scale IoT system that can stream MQTT messages to Apache Kafka.
We use HiveMQ as open source MQTT broker to ingest data from IoT devices, ingest the data in real time into an Apache Kafka cluster for preprocessing (using Kafka Streams / KSQL), and model training + inference (using TensorFlow 2.0 and its TensorFlow I/O Kafka plugin).
We leverage additional enterprise components from HiveMQ and Confluent to allow easy operations, scalability and monitoring.
WJAX 2013 Slides online: Big Data beyond Apache Hadoop - How to integrate ALL...Kai Wähner
Big data represents a significant paradigm shift in enterprise technology. Big data radically changes the nature of the data management profession as it introduces new concerns about the volume, velocity and variety of corporate data. Apache Hadoop is the open source defacto standard for implementing big data solutions on the Java platform. Hadoop consists of its kernel, MapReduce, and the Hadoop Distributed Filesystem (HDFS). A challenging task is to send all data to Hadoop for processing and storage (and then get it back to your application later), because in practice data comes from many different applications (SAP, Salesforce, Siebel, etc.) and databases (File, SQL, NoSQL), uses different technologies and concepts for communication (e.g. HTTP, FTP, RMI, JMS), and consists of different data formats using CSV, XML, binary data, or other alternatives. This session shows different open source frameworks and products to solve this challenging task. Learn how to use every thinkable data with Hadoop – without plenty of complex or redundant boilerplate code.
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology.
Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way integrating with various legacy and modern data sources and sinks.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
• The Automotive Industry (and it’s not only Connected Cars)
• Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
• Smart Cities (including citizen health services, communication infrastructure, …)
All these industries and sectors do not have new characteristics and requirements. They require data integration, data correlation or real decoupling, just to name a few, but are now facing massively increased volumes of data.
Real-time messaging solutions have existed for many years. Hundreds of platforms exist for data integration (including ETL and ESB tooling or specific IIoT platforms). Proprietary monoliths monitor plants, telco networks, and other infrastructures for decades in real-time. But now, Kafka combines all the above characteristics in an open, scalable, and flexible infrastructure to operate mission-critical workloads at scale in real-time. And is taking over the world of connecting data.
Apache Kafka for Real-time Supply Chainin the Food and Retail IndustryKai Wähner
Use Cases, Architectures, and Real-World Examples for data in motion and real-time event streaming powered by Apache Kafka across the supply chain and logistics. Case studies and deployments include Baader, Walmart, Migros, Albertsons, Domino's Pizza, Instacart, Grab, Royal Caribbean, and more.
IoT Architectures for Apache Kafka and Event Streaming - Industry 4.0, Digita...Kai Wähner
The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. Whether you are in Healthcare, Telecommunications, Manufacturing, Banking or Retail to name a few industries, there is one key challenge and that's the integration of backend IoT data logs and applications, business services and cloud services to process the data in real time and at scale.
In this talk, we will be sharing how Kafka has become the leading technology used throughout the business to provide Real Time Event Streaming. Explore real life use cases of Kafka Connect, Kafka Streams and KSQL independent of the data deployment be it on a private or public Cloud, On Premise or at the Edge.
Audi - Connected car infrastructure
Robert Bosch Power Tools - Track and Trace of devices and people at construction areas
Deutsche Bahn - Customer 360 for train timetable updates
E.ON - IoT Streaming Platform to integrate and build smart home, smart building and smart grid infrastructures
Simplified Machine Learning Architecture with an Event Streaming Platform (Ap...Kai Wähner
Machine Learning is separated into model training and model inference. ML frameworks typically load historical data from a data store like HDFS or S3 to train models. This talk shows how you can completely avoid such a data store by ingesting streaming data directly via Apache Kafka from any source system into TensorFlow for model training and model inference using the capabilities of “TensorFlow I/O” add-on.
The talk compares this modern streaming architecture to traditional batch and big data alternatives and explains benefits like the simplified architecture, the ability of reprocessing events in the same order for training different models, and the possibility to build a scalable, mission-critical, real time ML architecture with muss less headaches and problems.
Key takeaways for the audience
• Scalable open source Machine Learning infrastructure
• Streaming ingestion into TensorFlow without the need for another data store like HDFS or S3 (leveraging TensorFlow I/O and its Kafka plugin)
• Stream Processing using analytic models in mission-critical deployments to act in Real Time
• Learn how Apache Kafka open source ecosystem including Kafka Connect, Kafka Streams and KSQL help to build, deploy, score and monitor analytic models
• Comparison and trade-offs between this modern streaming approach and traditional batch model training infrastructures
Apache Kafka, Tiered Storage and TensorFlow for Streaming Machine Learning wi...Kai Wähner
Don’t underestimate the Hidden Technical Debt in Machine Learning Systems.
Leverage Apache Kafka’s open ecosystem as a scalable and flexible Event Streaming Platform to build one pipeline for real-time and batch use cases.
Use Streaming Machine Learning with Apache Kafka, Tiered Storage, and TensorFlow IO to simplify your big data architecture.
Tiered Storage for Kafka provides:
- one platform for all data processing
- an event-based source of truth for materialized views
- no need for a pipeline between Kafka and a Data Lake like Hadoop
Benefits:
- cost reduction
- long-term backup
- performance isolation (real-time and historical analysis in the same cluster)
Use Cases for Reprocessing Historical Events:
- New consumer application
- Error-handling
- Compliance / regulatory processing
- Query and analyze existing events
- Model training
Real-Life Use Cases & Architectures for Event Streaming with Apache KafkaKai Wähner
Streaming all over the World: Real-Life Use Cases & Architectures for Event Streaming with Apache Kafka.
Learn about various case studies for event streaming with Apache Kafka across industries. The talk explores architectures for real-world deployments from Audi, BMW, Disney, Generali, Paypal, Tesla, Unity, Walmart, William Hill, and more. Use cases include fraud detection, mainframe offloading, predictive maintenance, cybersecurity, edge computing, track&trace, live betting, and much more.
The Rise Of Event Streaming – Why Apache Kafka Changes EverythingKai Wähner
Business digitalization trends like microservices, the Internet of Things or Machine Learning are driving the need to process events at a whole new scale, speed and efficiency. Traditional solutions like ETL/data integration or messaging are not build to serve these needs.
Today, the open source project Apache Kafka® is being used by thousands of companies including over 60% of the Fortune 100 to power and innovate their businesses by focusing their data strategies around event-driven architectures leveraging event streaming.We will discuss the market and technology changes that have given rise to Kafka and to Event Streaming, and we will introduce the audience to the key aspects of building an Event streaming platform with Kafka. Examples of productive use cases from the automotive, manufacturing and transportation sector will showcase the power of event streaming.
DataOps on Streaming Data: From Kafka to InfluxDB via Kubernetes Native Flows...InfluxData
In this session, we are going to create a Lenses DataOps hub for IoT data with Apache Kafka and InfluxDB flows over Kubernetes. We will demonstrate how to create streaming flows and securely explore and monitor real-time data. We will use Kubernetes to spin up scalable flows and go through how we can simply provision such flows with secret management and monitoring end to end out capabilities.
Apache Kafka in the Public Sector (Government, National Security, Citizen Ser...Kai Wähner
The Rise of Data in Motion in the Public Sector powered by event streaming with Apache Kafka.
Citizen Services:
- Health services, e.g. hospital modernization, track & trace - Covid distance control
- Public administration - reduce bureaucracy, data democratization across government departments
- eGovernment - Efficient and digital citizen engagement, e.g. personal ID application process
Smart City
- Smart driving, parking, buildings, environment
Waste management
- Open exchange – e.g. mobility services (1st and 3rd party)
Energy
- Smart grid and utilities infrastructure (energy distribution, smart home, smart meters, smart water, etc.)
- National Security
Law enforcement, surveillance, police/interior security data exchange
- Defense and military (border control, intelligent solider)
Cybersecurity for situational awareness and threat intelligence
Kappa vs Lambda Architectures and Technology ComparisonKai Wähner
Real-time data beats slow data. That’s true for almost every use case. Nevertheless, enterprise architects build new infrastructures with the Lambda architecture that includes separate batch and real-time layers.
This video explores why a single real-time pipeline, called Kappa architecture, is the better fit for many enterprise architectures. Real-world examples from companies such as Disney, Shopify, Uber, and Twitter explore the benefits of Kappa but also show how batch processing fits into this discussion positively without the need for a Lambda architecture.
The main focus of the discussion is on Apache Kafka (and its ecosystem) as the de facto standard for event streaming to process data in motion (the key concept of Kappa), but the video also compares various technologies and vendors such as Confluent, Cloudera, IBM Red Hat, Apache Flink, Apache Pulsar, AWS Kinesis, Amazon MSK, Azure Event Hubs, Google Pub Sub, and more.
Video recording of this presentation:
https://youtu.be/j7D29eyysDw
Further reading:
https://www.kai-waehner.de/blog/2021/09/23/real-time-kappa-architecture-mainstream-replacing-batch-lambda/
https://www.kai-waehner.de/blog/2021/04/20/comparison-open-source-apache-kafka-vs-confluent-cloudera-red-hat-amazon-msk-cloud/
https://www.kai-waehner.de/blog/2021/05/09/kafka-api-de-facto-standard-event-streaming-like-amazon-s3-object-storage/
The Rise of Data in Motion in the Healthcare Industry - Use Cases, Architectures and Examples powered by Apache Kafka.
Use Cases for Data in Motion in the Healthcare Industry:
- Know Your Patient (= “Customer 360”)
- Operations (Healthcare 4.0 including Drug R&D, Patient Care, etc.)
- IT Perspective (Cybersecurity, Mainframe Offload, Hybrid Cloud, Streaming ETL, etc)
Real-world examples include Covid-19 Electronic Lab Reporting, Cerner, Optum, Centene, Humana, Invitae, Bayer, Celmatix, Care.com.
Kafka and Machine Learning in Banking and Insurance IndustryKai Wähner
Streaming Machine Learning and Apache Kafka for real-time analytics-The Next Generation of Intelligent Software for Financial Services and Insurance Industries.
The slides cover use cases, architectures, and examples from various companies. Learn about Kafka + Machine Learning / Deep Learning for fraud detection and other use cases.
Industry-ready NLP Service Framework Based on Kafka (Bernhard Waltl and Georg...confluent
Natural Language Processing (NLP) focuses on the analysis and understanding of textual information either in written or spoken form. In recent years, NLP technologies has become business critical due to the overwhelming and ever-increasing amount of textual information to get customer or business process insights, but also to empower novel user experience by creating dialogue-based digital assistants understanding customer language. In our talk, we will explore how NLP use cases significantly benefit from stream processing and event driven architectures. We will present the NLP Service Framework representing a stream processing framework using Kafka in which NLP tasks run as microservices orchestrated in pipelines to perform complex end-to-end services. In the NLP Service Framework, Kafka is being used to orchestrate data flows containing of all kinds of textual information in different topics related to specific use cases. Different Kafka Streams based processors subsequently call NLP services to analyze and annotate the textural information within the data flows. Various applications like search-based application based upon Elasticsearch and Kibana or analytical databases eventually consumes the textual information that is augmented with annotations and inferred results of the NLP Services. Two important requirements of the NLP Service Framework are efficient communication between different services using REST interfaces and interoperability among services implemented in different languages such as Java or Python. We implement the gRPC framework and use ProtoBuff as data format to ensure both requirements. This Kafka-based architecture enables us to specify domain-specific but isolated end-to-end NLP services and guarantees highly scalable and robust handling of high volume of textual data from different BMW domains along the value chain, including customer, process, and vehicle data.
The Streaming Assessment – An Introductionconfluent
Business breakout during Confluent’s streaming event in Munich, presented by Lyndon Hedderly, Director of Customer Solutions at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
IIoT / Industry 4.0 with Apache Kafka, Connect, KSQL, Apache PLC4X Kai Wähner
Data integration and processing is a huge challenge in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry) due to monolithic systems and proprietary protocols. Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
This blog post covers a high level overview about the challenges and a good, flexible architecture. At the end, I share a video recording and the corresponding slide deck. These provide many more details and insights.
Apache Kafka is the De-facto Standard for Real-Time Event Streaming. It provides
Open Source (Apache 2.0 License)
Global-scale
Real-time
Persistent Storage
Stream Processing
PCL4X allows vertical integration and to write software independent of PLCs using JDBC-like adapters for various protocols like Siemens S7, Modbus, Allen Bradley, Beckhoff ADS, OPC-UA, Emerson, Profinet, BACnet, Ethernet.
Github example: https://github.com/kaiwaehner/iiot-integration-apache-plc4x-kafka-connect-ksql-opc-ua-modbus-siemens-s7
More details: http://www.kai-waehner.de/blog/2019/09/02/iiot-data-integr…and-apache-plc4x/
Video Recording: https://youtu.be/RWKggid25ds
Machine Learning with Apache Kafka in Pharma and Life SciencesKai Wähner
Blog Post:
https://www.kai-waehner.de/apache-kafka-event-streaming-pharmaceuticals-pharma-life-sciences-use-cases-architecture
Video Recording:
https://youtu.be/t2IH0brwGTg
AI/Machine learning and the Apache Kafka ecosystem are a great combination for training, deploying and monitoring analytic models at scale in real-time. They are showing up more and more in projects but still, feel like buzzwords and hype for science projects.
See how to connect the dots!
--How are Kafka and Machine Learning related?
--How can they be combined to productionize analytic models in mission-critical and scalable real-time applications?
--We will discuss a step-by-step approach to build a scalable and reliable real-time infrastructure for drug discovery doing data integration, feature engineering, image processing, model scoring and processing orchestration.
Use Cases:
R&D Engineering
Sales & Marketing
Manufacturing & Quality Assurance
Supply Chain
Product Monitoring & After Sales Support
VoC (Voice of Customer)
Single View Customer
Yield/Quality Optimization
Improved Drug Yield
Proactive Service Scheduling
Testing & Simulation
Drug Diversion
Process/Quality Monitoring
Inventory & Supply Chain Optimization
Proactive Service Offers
Patent Research and Analytics
Personalized Offers / Ads
EDW Offload
Supply Chain Network Design/Risk Management
Product Predictive Maintenance
Clinical Trials
Customer Segmentation
Smart Products
Serialization & e-Pedigree
Product Usage Tracking
GTM
Global Facilities
Inventory and Logistics Visibility
Warranty & Recall Management
Business breakout during Confluent’s streaming event in Munich, presented by Falko Schwarz, VP CEMEA at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Apache Kafka and MQTT - Overview, Comparison, Use Cases, ArchitecturesKai Wähner
Apache Kafka and MQTT are a perfect combination for many IoT use cases. This presentation covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions.
Blog series with more details here:
https://www.kai-waehner.de/blog/2021/03/15/apache-kafka-mqtt-sparkplug-iot-blog-series-part-1-of-5-overview-comparison/
Apache Kafka in Financial Services - Use Cases and ArchitecturesKai Wähner
The Rise of Event Streaming in Financial Services - Use Cases, Architectures and Examples powered by Apache Kafka.
The New FinServ Enterprise Reality: Every company is a software company. Innovate OR be Disrupted. Learn how Event Streaming with Apache Kafka and its ecosystem help...
More details:
https://www.kai-waehner.de/apache-kafka-financial-services-industry-banking-finserv-payment-fraud-middleware-messaging-transactions
https://www.kai-waehner.de/blog/2020/04/15/apache-kafka-machine-learning-banking-finance-industry/
https://www.kai-waehner.de/blog/2020/04/24/mainframe-offloading-replacement-apache-kafka-connect-ibm-db2-mq-cdc-cobol/
Event-Streaming verstehen in unter 10 Minconfluent
Um die unternehmerische Geschwindigkeit zu erhöhen, die Wettbewerbsfähigkeit durch neue Produkte und Services zu steigern und schnell auf plötzlich ändernde Markteinflüsse reagieren zu können, müssen Daten und Ereignisströme in Echtzeit geteilt, verarbeitet und ausgewertet werden können. Apache Kafka hat sich hier als Industrie-Standard für Event-Streaming etabliert. Ob Connected Car, Industrie 4.0 oder Customer 360 – alle diese zukunftsorientierten Themen benötigen schnelle Kommunikation, effiziente Vernetzung und eine Verarbeitung von enormen Datenmengen in Echtzeit.
Event Mesh Presentation at Gartner AADI MumbaiSolace
Summit Puri, Global Head of Systems Engineering at Solace, talks about the architecture layer that will make your business event-driven. Find out more about event mesh in this presentation from Gartner AADI Mumbai on March 11th, 2019.
Financial Event Sourcing at Enterprise Scaleconfluent
For years, Rabobank has been actively investing in becoming a real-time, event-driven bank. If you are familiar with banking processes, you will understand that this is not simple. Many banking processes are implemented as batch jobs on not-so-commodity hardware, meaning that any migration effort is immense.
*Find out how Rabobank redesigned Rabo Alerts while continuing to provide a robust and stable alert system for its existing user base
*Learn how the project team managed to achieve a balance between the need to decentralise activity while not losing control
*Understand how Rabobank re-invented a reliable service to meet modern customer expectations
Driving Business Transformation with Real-Time Analytics Using Apache Kafka a...confluent
Watch this talk here: https://www.confluent.io/online-talks/driving-business-transformation-real-time-analytics-using-apache-kafka-and-ksql
Digital transformation is more than just a buzzword, it’s become a necessity in order to compete in the modern era. At the heart of digital transformation is real-time data. Your organization must respond in real time to every customer experience transaction, sale, and market movement in order to stay competitive.
Streaming data technologies like Apache Kafka® and Confluent KSQL, the streaming SQL engine for Apache Kafka, are being used to detect and react to events as they occur. Combining this technology with the analytics insights from RCG and visualizations from Arcadia Data delivers a powerful foundation for driving real time business decisions. Use cases span across industries and include retail transaction cost analysis, automotive maintenance and loyalty program management, and credit card fraud detection.
Join experts from Confluent, RCG and Arcadia Data for a discussion and demo on how companies are integrating streaming data technologies to transform their business.
You will learn:
-Why Apache Kafka is widely used for real-time event monitoring and decisioning
-How to integrate real-time analytics and visualizations to drive business processes
-How KSQL, streaming SQL for Kafka, can easily transform and filter streams of data in real time
The Rise Of Event Streaming – Why Apache Kafka Changes EverythingKai Wähner
Business digitalization trends like microservices, the Internet of Things or Machine Learning are driving the need to process events at a whole new scale, speed and efficiency. Traditional solutions like ETL/data integration or messaging are not build to serve these needs.
Today, the open source project Apache Kafka® is being used by thousands of companies including over 60% of the Fortune 100 to power and innovate their businesses by focusing their data strategies around event-driven architectures leveraging event streaming.We will discuss the market and technology changes that have given rise to Kafka and to Event Streaming, and we will introduce the audience to the key aspects of building an Event streaming platform with Kafka. Examples of productive use cases from the automotive, manufacturing and transportation sector will showcase the power of event streaming.
DataOps on Streaming Data: From Kafka to InfluxDB via Kubernetes Native Flows...InfluxData
In this session, we are going to create a Lenses DataOps hub for IoT data with Apache Kafka and InfluxDB flows over Kubernetes. We will demonstrate how to create streaming flows and securely explore and monitor real-time data. We will use Kubernetes to spin up scalable flows and go through how we can simply provision such flows with secret management and monitoring end to end out capabilities.
Apache Kafka in the Public Sector (Government, National Security, Citizen Ser...Kai Wähner
The Rise of Data in Motion in the Public Sector powered by event streaming with Apache Kafka.
Citizen Services:
- Health services, e.g. hospital modernization, track & trace - Covid distance control
- Public administration - reduce bureaucracy, data democratization across government departments
- eGovernment - Efficient and digital citizen engagement, e.g. personal ID application process
Smart City
- Smart driving, parking, buildings, environment
Waste management
- Open exchange – e.g. mobility services (1st and 3rd party)
Energy
- Smart grid and utilities infrastructure (energy distribution, smart home, smart meters, smart water, etc.)
- National Security
Law enforcement, surveillance, police/interior security data exchange
- Defense and military (border control, intelligent solider)
Cybersecurity for situational awareness and threat intelligence
Kappa vs Lambda Architectures and Technology ComparisonKai Wähner
Real-time data beats slow data. That’s true for almost every use case. Nevertheless, enterprise architects build new infrastructures with the Lambda architecture that includes separate batch and real-time layers.
This video explores why a single real-time pipeline, called Kappa architecture, is the better fit for many enterprise architectures. Real-world examples from companies such as Disney, Shopify, Uber, and Twitter explore the benefits of Kappa but also show how batch processing fits into this discussion positively without the need for a Lambda architecture.
The main focus of the discussion is on Apache Kafka (and its ecosystem) as the de facto standard for event streaming to process data in motion (the key concept of Kappa), but the video also compares various technologies and vendors such as Confluent, Cloudera, IBM Red Hat, Apache Flink, Apache Pulsar, AWS Kinesis, Amazon MSK, Azure Event Hubs, Google Pub Sub, and more.
Video recording of this presentation:
https://youtu.be/j7D29eyysDw
Further reading:
https://www.kai-waehner.de/blog/2021/09/23/real-time-kappa-architecture-mainstream-replacing-batch-lambda/
https://www.kai-waehner.de/blog/2021/04/20/comparison-open-source-apache-kafka-vs-confluent-cloudera-red-hat-amazon-msk-cloud/
https://www.kai-waehner.de/blog/2021/05/09/kafka-api-de-facto-standard-event-streaming-like-amazon-s3-object-storage/
The Rise of Data in Motion in the Healthcare Industry - Use Cases, Architectures and Examples powered by Apache Kafka.
Use Cases for Data in Motion in the Healthcare Industry:
- Know Your Patient (= “Customer 360”)
- Operations (Healthcare 4.0 including Drug R&D, Patient Care, etc.)
- IT Perspective (Cybersecurity, Mainframe Offload, Hybrid Cloud, Streaming ETL, etc)
Real-world examples include Covid-19 Electronic Lab Reporting, Cerner, Optum, Centene, Humana, Invitae, Bayer, Celmatix, Care.com.
Kafka and Machine Learning in Banking and Insurance IndustryKai Wähner
Streaming Machine Learning and Apache Kafka for real-time analytics-The Next Generation of Intelligent Software for Financial Services and Insurance Industries.
The slides cover use cases, architectures, and examples from various companies. Learn about Kafka + Machine Learning / Deep Learning for fraud detection and other use cases.
Industry-ready NLP Service Framework Based on Kafka (Bernhard Waltl and Georg...confluent
Natural Language Processing (NLP) focuses on the analysis and understanding of textual information either in written or spoken form. In recent years, NLP technologies has become business critical due to the overwhelming and ever-increasing amount of textual information to get customer or business process insights, but also to empower novel user experience by creating dialogue-based digital assistants understanding customer language. In our talk, we will explore how NLP use cases significantly benefit from stream processing and event driven architectures. We will present the NLP Service Framework representing a stream processing framework using Kafka in which NLP tasks run as microservices orchestrated in pipelines to perform complex end-to-end services. In the NLP Service Framework, Kafka is being used to orchestrate data flows containing of all kinds of textual information in different topics related to specific use cases. Different Kafka Streams based processors subsequently call NLP services to analyze and annotate the textural information within the data flows. Various applications like search-based application based upon Elasticsearch and Kibana or analytical databases eventually consumes the textual information that is augmented with annotations and inferred results of the NLP Services. Two important requirements of the NLP Service Framework are efficient communication between different services using REST interfaces and interoperability among services implemented in different languages such as Java or Python. We implement the gRPC framework and use ProtoBuff as data format to ensure both requirements. This Kafka-based architecture enables us to specify domain-specific but isolated end-to-end NLP services and guarantees highly scalable and robust handling of high volume of textual data from different BMW domains along the value chain, including customer, process, and vehicle data.
The Streaming Assessment – An Introductionconfluent
Business breakout during Confluent’s streaming event in Munich, presented by Lyndon Hedderly, Director of Customer Solutions at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
IIoT / Industry 4.0 with Apache Kafka, Connect, KSQL, Apache PLC4X Kai Wähner
Data integration and processing is a huge challenge in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry) due to monolithic systems and proprietary protocols. Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
This blog post covers a high level overview about the challenges and a good, flexible architecture. At the end, I share a video recording and the corresponding slide deck. These provide many more details and insights.
Apache Kafka is the De-facto Standard for Real-Time Event Streaming. It provides
Open Source (Apache 2.0 License)
Global-scale
Real-time
Persistent Storage
Stream Processing
PCL4X allows vertical integration and to write software independent of PLCs using JDBC-like adapters for various protocols like Siemens S7, Modbus, Allen Bradley, Beckhoff ADS, OPC-UA, Emerson, Profinet, BACnet, Ethernet.
Github example: https://github.com/kaiwaehner/iiot-integration-apache-plc4x-kafka-connect-ksql-opc-ua-modbus-siemens-s7
More details: http://www.kai-waehner.de/blog/2019/09/02/iiot-data-integr…and-apache-plc4x/
Video Recording: https://youtu.be/RWKggid25ds
Machine Learning with Apache Kafka in Pharma and Life SciencesKai Wähner
Blog Post:
https://www.kai-waehner.de/apache-kafka-event-streaming-pharmaceuticals-pharma-life-sciences-use-cases-architecture
Video Recording:
https://youtu.be/t2IH0brwGTg
AI/Machine learning and the Apache Kafka ecosystem are a great combination for training, deploying and monitoring analytic models at scale in real-time. They are showing up more and more in projects but still, feel like buzzwords and hype for science projects.
See how to connect the dots!
--How are Kafka and Machine Learning related?
--How can they be combined to productionize analytic models in mission-critical and scalable real-time applications?
--We will discuss a step-by-step approach to build a scalable and reliable real-time infrastructure for drug discovery doing data integration, feature engineering, image processing, model scoring and processing orchestration.
Use Cases:
R&D Engineering
Sales & Marketing
Manufacturing & Quality Assurance
Supply Chain
Product Monitoring & After Sales Support
VoC (Voice of Customer)
Single View Customer
Yield/Quality Optimization
Improved Drug Yield
Proactive Service Scheduling
Testing & Simulation
Drug Diversion
Process/Quality Monitoring
Inventory & Supply Chain Optimization
Proactive Service Offers
Patent Research and Analytics
Personalized Offers / Ads
EDW Offload
Supply Chain Network Design/Risk Management
Product Predictive Maintenance
Clinical Trials
Customer Segmentation
Smart Products
Serialization & e-Pedigree
Product Usage Tracking
GTM
Global Facilities
Inventory and Logistics Visibility
Warranty & Recall Management
Business breakout during Confluent’s streaming event in Munich, presented by Falko Schwarz, VP CEMEA at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Apache Kafka and MQTT - Overview, Comparison, Use Cases, ArchitecturesKai Wähner
Apache Kafka and MQTT are a perfect combination for many IoT use cases. This presentation covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions.
Blog series with more details here:
https://www.kai-waehner.de/blog/2021/03/15/apache-kafka-mqtt-sparkplug-iot-blog-series-part-1-of-5-overview-comparison/
Apache Kafka in Financial Services - Use Cases and ArchitecturesKai Wähner
The Rise of Event Streaming in Financial Services - Use Cases, Architectures and Examples powered by Apache Kafka.
The New FinServ Enterprise Reality: Every company is a software company. Innovate OR be Disrupted. Learn how Event Streaming with Apache Kafka and its ecosystem help...
More details:
https://www.kai-waehner.de/apache-kafka-financial-services-industry-banking-finserv-payment-fraud-middleware-messaging-transactions
https://www.kai-waehner.de/blog/2020/04/15/apache-kafka-machine-learning-banking-finance-industry/
https://www.kai-waehner.de/blog/2020/04/24/mainframe-offloading-replacement-apache-kafka-connect-ibm-db2-mq-cdc-cobol/
Event-Streaming verstehen in unter 10 Minconfluent
Um die unternehmerische Geschwindigkeit zu erhöhen, die Wettbewerbsfähigkeit durch neue Produkte und Services zu steigern und schnell auf plötzlich ändernde Markteinflüsse reagieren zu können, müssen Daten und Ereignisströme in Echtzeit geteilt, verarbeitet und ausgewertet werden können. Apache Kafka hat sich hier als Industrie-Standard für Event-Streaming etabliert. Ob Connected Car, Industrie 4.0 oder Customer 360 – alle diese zukunftsorientierten Themen benötigen schnelle Kommunikation, effiziente Vernetzung und eine Verarbeitung von enormen Datenmengen in Echtzeit.
Event Mesh Presentation at Gartner AADI MumbaiSolace
Summit Puri, Global Head of Systems Engineering at Solace, talks about the architecture layer that will make your business event-driven. Find out more about event mesh in this presentation from Gartner AADI Mumbai on March 11th, 2019.
Financial Event Sourcing at Enterprise Scaleconfluent
For years, Rabobank has been actively investing in becoming a real-time, event-driven bank. If you are familiar with banking processes, you will understand that this is not simple. Many banking processes are implemented as batch jobs on not-so-commodity hardware, meaning that any migration effort is immense.
*Find out how Rabobank redesigned Rabo Alerts while continuing to provide a robust and stable alert system for its existing user base
*Learn how the project team managed to achieve a balance between the need to decentralise activity while not losing control
*Understand how Rabobank re-invented a reliable service to meet modern customer expectations
Driving Business Transformation with Real-Time Analytics Using Apache Kafka a...confluent
Watch this talk here: https://www.confluent.io/online-talks/driving-business-transformation-real-time-analytics-using-apache-kafka-and-ksql
Digital transformation is more than just a buzzword, it’s become a necessity in order to compete in the modern era. At the heart of digital transformation is real-time data. Your organization must respond in real time to every customer experience transaction, sale, and market movement in order to stay competitive.
Streaming data technologies like Apache Kafka® and Confluent KSQL, the streaming SQL engine for Apache Kafka, are being used to detect and react to events as they occur. Combining this technology with the analytics insights from RCG and visualizations from Arcadia Data delivers a powerful foundation for driving real time business decisions. Use cases span across industries and include retail transaction cost analysis, automotive maintenance and loyalty program management, and credit card fraud detection.
Join experts from Confluent, RCG and Arcadia Data for a discussion and demo on how companies are integrating streaming data technologies to transform their business.
You will learn:
-Why Apache Kafka is widely used for real-time event monitoring and decisioning
-How to integrate real-time analytics and visualizations to drive business processes
-How KSQL, streaming SQL for Kafka, can easily transform and filter streams of data in real time
Talend, Leading Open Source DataIntegration plateform. Cedric CarboneCedric CARBONE
Slides corporate de la société Talend (Oct08) et ses 4 plateformes Open Source :
-Talend Open Studio
-Talend Integration Suite
-Talend Open Profiler
-Talend Data Quality
Plus d'info à http://www.talend.com
Structured Approach to Solution ArchitectureAlan McSweeney
The role of solution architecture is to identify answer to a business problem and set of solution options and their components. There will be many potential solutions to a problem with varying degrees of suitability to the underlying business need. Solution options are derived from a combination of Solution Architecture Dimensions/Views which describe characteristics, features, qualities, requirements and Solution Design Factors, Limitations And Boundaries which delineate limitations. Use of structured approach can assist with solution design to create consistency. The TOGAF approach to enterprise architecture can be adapted to perform some of the analysis and design for elements of Solution Architecture Dimensions/Views.
"Big Data beyond Apache Hadoop - How to Integrate ALL your Data" - JavaOne 2013Kai Wähner
Big data represents a significant paradigm shift in enterprise technology. Big data radically changes the nature of the data management profession as it introduces new concerns about the volume, velocity and variety of corporate data.
Apache Hadoop is the open source defacto standard for implementing big data solutions on the Java platform. Hadoop consists of its kernel, MapReduce, and the Hadoop Distributed Filesystem (HDFS). A challenging task is to send all data to Hadoop for processing and storage (and then get it back to your application later), because in practice data comes from many different applications (SAP, Salesforce, Siebel, etc.) and databases (File, SQL, NoSQL), uses different technologies and concepts for communication (e.g. HTTP, FTP, RMI, JMS), and consists of different data formats using CSV, XML, binary data, or other alternatives.
This session shows different open source frameworks and products to solve this challenging task. Learn how to use every thinkable data with Hadoop – without plenty of complex or redundant boilerplate code.
Big Data beyond Apache Hadoop - How to integrate ALL your DataKai Wähner
Big data represents a significant paradigm shift in enterprise technology. Big data radically changes the nature of the data management profession as it introduces new concerns about the volume, velocity and variety of corporate data.
Apache Hadoop is the open source defacto standard for implementing big data solutions on the Java platform. Hadoop consists of its kernel, MapReduce, and the Hadoop Distributed Filesystem (HDFS). A challenging task is to send all data to Hadoop for processing and storage (and then get it back to your application later), because in practice data comes from many different applications (SAP, Salesforce, Siebel, etc.) and databases (File, SQL, NoSQL), uses different technologies and concepts for communication (e.g. HTTP, FTP, RMI, JMS), and consists of different data formats using CSV, XML, binary data, or other alternatives.
This session shows the powerful combination of Apache Hadoop and Apache Camel to solve this challenging task. Learn how to use every thinkable data with Hadoop – without plenty of complex or redundant boilerplate code. Besides supporting the integration of all different technologies and data formats, Apache Camel also offers an easy, standardized DSL to transform, split or filter incoming data using the Enterprise Integration Patterns (EIP). Therefore, Apache Hadoop and Apache Camel are a perfect match for processing big data on the Java platform.
Hadoop and the Data Warehouse: When to Use Which DataWorks Summit
In recent years, Apache™ Hadoop® has emerged from humble beginnings to disrupt the traditional disciplines of information management. As with all technology innovation, hype is rampant, and data professionals are easily overwhelmed by diverse opinions and confusing messages.
Even seasoned practitioners sometimes miss the point, claiming for example that Hadoop replaces relational databases and is becoming the new data warehouse. It is easy to see where these claims originate since both Hadoop and Teradata® systems run in parallel, scale up to enormous data volumes and have shared-nothing architectures. At a conceptual level, it is easy to think they are interchangeable, but the differences overwhelm the similarities. This session will shed light on the differences and help architects, engineering executives, and data scientists identify when to deploy Hadoop and when it is best to use MPP relational database in a data warehouse, discovery platform, or other workload-specific applications.
Two of the most trusted experts in their fields, Steve Wooledge, VP of Product Marketing from Teradata and Jim Walker of Hortonworks will examine how big data technologies are being used today by practical big data practitioners.
2015 02 12 talend hortonworks webinar challenges to hadoop adoptionHortonworks
Hadoop is no longer optional. Companies of all sizes are in various phases of their own Big Data journey. Whether you are just starting to explore the platform or have multiple clusters up and running, everyone is presented with a similar challenge - developing their internal skillset. Hadoop specialists are hard to find. Hand coding is too prone to error when it comes to storing, integrating or analyzing your data. However, it doesn’t need to be this difficult.
In this recorded webinar, Talend and Hortonworks help you learn how to unify all your data in Hadoop, with no specialized Big Data skills.
Find the recording here. www.talend.com/resources/webinars/challenges-to-hadoop-adoption-if-you-can-dream-it-you-can-build-it
This webinar covers: How Hadoop opens a new world of analytic applications, How to bridge the skills gap with our Big Data solutions, Experience a real-world, simple technical demo
Big Data brings big promise and also big challenges, the primary and most important one being the ability to deliver Value to business stakeholders who are not data scientists!
My slides on how to use cloud as a data platform at BigDataWeek 2013 Romania
http://www.eurocloud.ro/en/events/all-there-is-to-know-about-big-data/#.UXZFaUDvlVI
Every second of every day you hear about Electronic systems creating ever increasing quantities of data. Systems in markets such as finance, media, healthcare, government and scientific research feature strongly in the Big Data processing conversation. While extracting business value from Big Data is forecast to bring customer and competitive advantage and benefits. In this session hear Vas Kapsalis, NetApp Big Data Business Development Manager, discuss his views and experience on the wider world of Big Data.
C-BAG Big Data Meetup Chennai Oct.29-2014 Hortonworks and Concurrent on Casca...Hortonworks
Big Data is moving to the next level of maturity and it’s all about the applications. Dhruv Kumar, one of the minds behind Cascading, the most widely used and deployed development framework for building Big Data applications, will discuss how Cascading can enable developers to accelerate the time to market for their data applications, from development to production. In this session, Dhruv will introduce how to easily and reliably develop, test, and scale your data applications and then deploy them on Hadoop and Hortonworks Data Platform. He will show a demo using the Hortonworks Sandbox and Cascading. Recording is at
https://hortonworks.webex.com/hortonworks/lsr.php?RCID=e5582bcbc0516d35fc2dcf0bce86146e
BIG Data & Hadoop Applications in Social MediaSkillspeed
Explore the applications of BIG Data & Hadoop in Social Media via Skillspeed.
BIG Data & Hadoop in Social Media is a key differentiator, especially in terms of generating memorable customer experiences.
Herein, we discuss how leading social networks such as Facebook, Twitter, Pinterest, LinkedIN, Instagram & Stumble Upon utilize Hadoop.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
How to create intelligent Business Processes thanks to Big Data (BPM, Apache ...Kai Wähner
BPM is established, tools are stable, many companies use it successfully. However, today's business processes are based on data from relational databases or web services. Humans make decisions due to this information. Companies also use business intelligence and other tools to analyze their data. Though, business processes are executed without access to this important information because technical challenges occur when trying to integrate big masses of data from many different sources into the BPM engine. Additionally, bad data quality due to duplication, incompleteness and inconsistency prevents humans from making good decisions. That is status quo. Companies miss a huge opportunity here!
This session explains how to achieve intelligent business processes, which use big data to improve performance and outcomes. A live demo shows how big data can be integrated into business processes easily - just with open source tooling. In the end, the audience will understand why BPM needs big data to achieve intelligent business processes.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
78. Thanks for the attention!
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