Name: Streaming von SAP-Daten und mehr nach Apache Kafka
Start: 2018-04-10T08:00:00Z
End: 2018-04-10T08:00:47.000Z
Location: BrightTALK
Rating: 0

Confluent is building the foundational platform for data in motion. Our cloud-native offering is designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organisation. With Confluent, organisations can create a central nervous system to innovate and win in a digital-first world.

Are you struggling to scale your data streaming use cases and break down organisational silos? Join Lyndon Hedderly and Burhan Nazir of Confluent as they share their expertise on deploying enterprise-wide data streaming and accelerating the speed to realising measurable business value derived from a data-streaming investment.

With years of experience enabling companies to deploy data streaming, Lyndon and Burhan have identified the missing factors in data streaming deployments, including a lack of general business visibility, an absence of allocated budget for Kafka or data streaming, and no senior-level or C-suite sponsorship.

During this webinar, you will learn five top tips on successfully implementing an enterprise-wide streaming platform. You will also discover how organisations are leveraging data streaming to scale their operations and break down silos.

Take advantage of this opportunity to learn from the experts in data streaming. Register now to join Lyndon and Burhan and take the first step towards realising the full potential of your data.

Five Tips for Enabling Enterprise-Wide Data Streaming

Data Streaming with Apache Kafka and Apache Flink is one of the world's most relevant and talked about paradigms in technology. With the buzz around this technology growing, join Kai Waehner, Global Field CTO at Confluent, to hear his predictions for the 'Top Five Trends for Data Streaming in 2024'. In this webinar, Kai will discuss:

• Data Sharing: Decentralized data mesh architecture with independent data products building or buying cloud-native software components. Collaborating within and outside the organization with data sharing using streaming protocols like Kafka, APIs like REST/HTTP, and open standards like AsyncAPI

• Data Contracts: Policy enforcement for structure, integrity constraints, metadata, rules, and other requirements to ensure data governance and compliance across the end-to-end data streaming pipelines

• Serverless Stream Processing: Focusing on business value leveraging a fully managed, integrated, and secure infrastructure for data correlation to implement streaming ETL and application development.

• Multi-Cloud: Data bridge, migrations, or disaster recovery across cloud providers with reliable uni- or bidirectional data synchronization

• AI: Data fabric for machine learning infrastructures to train models, real-time model scoring, and integrating 3rd party services like GenAI LLMs or SaaS offerings

Top Five Data Streaming Trends for 2024

Data pipelines do much of the heavy lifting in organisations for integrating, transforming, and preparing the data for subsequent use in downstream systems for operational use cases. Despite being critical to the data value stream, data pipelines fundamentally haven’t evolved in the last few decades. These legacy pipelines are holding organisations back from getting value from their data as real-time streaming becomes essential.
 
This webinar will walk through the story of a bank that uses an Oracle database to store sensitive customer information and RabbitMQ as the message broker for credit card transaction events. Their goal is to perform real-time analysis on credit card transactions to flag fraudulent transactions and push suspicious activity flags to MongoDB Atlas, their modern cloud-native database that powers their in-app mobile notifications.
 
To illustrate this use case, you’ll see a live demo of:

• Confluent’s fully managed connectors for Oracle CDC Source and RabbitMQ Source to stream the data in real-time ksqlDB to merge the two data sources, generating a unified view of customers and their credit card activity and flagging fraudulent transactions

• The fully managed MongoDB Atlas sink connector to load the aggregated and transformed data into MongoDB Atlas

• Along with the live demo and customer use case, you’ll learn about the challenges with batch-based data pipelines and the benefits of streaming data pipelines to power modern data flows.

How to Build Streaming Pipelines for Cloud Databases

According to SAP, over seventy per cent of the world's business transactions touch an SAP system, cementing SAP's role in providing business-critical software. This business criticality requires faultless integration across cloud and on-premise software deployments to ensure a secure, reliable, uninterrupted service. Architecting a robust event-driven ecosystem is central to achieving this. Rojo constructed for a global manufacturer a Confluent solution for real-time distribution of data alongside a user-friendly interface.

Join Rojo and Confluent on October 26 for a 'how to' webinar in which  Rojo will outline how to optimise the use of Apache Kafka in your SAP integration initiatives. By attending, you will learn about the following:
 

- Traditional middleware (ETL/ESB).
- Web services (SOAP/REST)
- 3rd party turnkey solutions
- Kafka-native connectivity via Kafka Connect
- Self-written solutions using SAP SDKs
- A custom Confluent Kafka solution by Rojo - data streaming

How to Unleash the Power of Data with SAP® and Apache Kafka®

Data Mesh has been gaining traction over the past year or two - and with good reason. With organizations constantly exploring the potential of data, it’s becoming increasingly clear that it’s Data Mesh that may be the key to enabling businesses to truly realize their data-driven initiatives.

In this Confluent webinar, experts are coming together to discuss how Data Mesh has emerged as a paradigm shift in data architecture and to share how teams can be empowered to harness the power of their data at scale. Join Lyndon Hedderly - Director of Customer Solutions at Confluent and Piethein Strengholt - Chief Data Officer (The Netherlands) at Microsoft as they explore:

- The core principles and fundamentals of Data Mesh 
- Best practices for implementing a Data Mesh into your organization, including how businesses can foster a culture of data ownership, accountability, and autonomy 
- What Data Mesh challenges may arise and how to navigate them 
- The stakeholders involved in implementing and managing a Data Mesh
- The business value and new revenue streams a Data Mesh can help realize

Unlocking the Power of Data Mesh: Decentralizing and Democratizing Data

80% of consumer analytics happens on data that’s older than 1 day. Learn how to extract actionable real time insights for your shoppers and products through a streaming analytic application. 

With Confluent and Imply, you can build a streaming analytic application that provides a 360 view of your customer’s buying behavior in 1 hour.

1. Aggregate all your data to build timely context around each customer profile
2. Visualize buying patterns instantly
3. Identify top selling products and refill inventory
4. Identify potential revenue streams in real time
5. Connect teams for shared insights with a consistent view of both streaming and historical data

Join us for an exclusive opportunity to hear from the thought leaders of Kafka and Apache Druid on how Confluent Cloud and Imply Polaris enable customers to leverage the power of interactive streaming platforms to accelerate real time data analytics. Bring your laptop for this interactive workshop

Who should attend:

1. Application developers and engineers interested in real time analytics
2. Engineers, developers, architects, or anyone interested in understanding real time system design and use cases. 
3. Any skill or maturity level with event-drive systems, Apache Kafka, or messaging in general. 

Please note: 
Confluent Cloud account and Imply Polaris account are required for the lab session. 

Sign-up for Confluent Cloud. New signups receive $400 to spend on Confluent Cloud during their first 60 days.

Sign-up for Imply Polaris here. New signups receive free usage for the first 30 days valued at $1872.

Building a Streaming Analytics Application in 1 Hour

What is Apache Kafka® and how does it work?

Apache Kafka® was built with the vision to become the central nervous system that makes real-time data available to all the applications that need to use it, with numerous use cases like stock trading and fraud detection, to transportation, data integration, and real-time analytics.

In this 2 part series you will get an overview of what Kafka is, what it's used for, and the core concepts that enable it to power a highly scalable, available, and resilient real-time event streaming platform. The series begins with an introduction to the shift toward real-time data streaming and continues all the way through to best practices for developing applications with Apache Kafka® and how to integrate Kafka into your environment.

Whether you’re just getting started or have already built stream processing applications, you will find actionable insights in this series that will enable you to further derive business value from your data systems.

This training is comprised of the following topics::

1. Benefits of Stream Processing and Apache Kafka® Use Cases
2. Apache Kafka® Architecture & Fundamentals Explained
3. How Apache Kafka® Works
4. Integrating Apache Kafka® Into Your Environment
5. Confluent Cloud

Register now to learn Apache Kafka® from Confluent, the company founded by Kafka’s original developers.

Part 1: Fundamentals for Apache Kafka

Confluent is hosting a technical thought leadership session to discuss how leading organisations move to real-time architecture to support business growth and enhance customer experience. This is a forum to discuss use cases with your peers to understand how other digital-native companies are utilising data in motion to drive competitive advantage.

The session will be virtual and led by Kai Waehner, a Technical Evangelist and a thought leader in this space. Register today to network with your peers and hear about the use cases that are transforming business.

Data in Motion Use Cases for the CTO

Data is becoming more crucial by the day to the financial services industry. Financial institutions are using their expanded data pools and cloud infrastructure to make better loans, improve their services and offerings to customers, comply with regulations, and detect fraud. 

Many companies, however, are not using data to its full potential. The old ‘data at rest model’ is becoming outdated as new ‘data in motion’ systems provide companies the ability to see how data changes as it flows through their organizations, enabling them to provide new applications and services to their customers and build out more efficient operating systems for their business. 

In this session, we explore how data in motion platforms empower financial services companies to make better decisions when it comes to the way they conduct operations and offer services. 

We discuss: 
-How financial institutions have incorporated data into their operations
-The ways a ‘data in motion’ system differs from the old ‘data at rest’ system 
-How a ‘data in motion’ system helps companies improve their operations and expand their services
-What the future of data looks like for financial services companies

Our speakers:
Duncan Ash is VP of Global Industries at Confluent. He has spent the last 25 years working at the intersection of business and technology to solve complex data and analytics problems, with a specific focus on the financial services industry. Duncan has spearheaded a diverse range of solutions for low-latency trading, market risk, fraud detection, and wealth management, most recently at Splunk, and previously at Qlik, SAS, and Sybase.

Jim Zucker is Lead Architect at Ness Financial Services vertical. With over 25 years of experience, Jim is an expert in digital transformation of risk, trading, credit, derivatives and compliance systems. Before joining Ness, Jim held senior leadership positions at Salomon Brothers, Citi and Calypso and was CTO of EZOPS. He is a US Army Veteran.

Data in Motion: the New Paradigm in Financial Services

Microservices have emerged as a widely discussed and adopted way to build modern and scalable applications. They are easier to build, manage and maintain than monoliths due to smaller code bases; they isolate complexity, allowing for smaller, more agile teams to create services, and they are flexible—allowing the use of various platforms, programming languages, and tools since these choices affect only an individual service and a small team at a time.



While a microservices architecture provides a good pattern for application modernization efforts, refactoring applications and modernizing existing applications is no small feat. Enterprises must do this thoughtfully or risk adopting a short-sighted strategy for their innovation and business needs.



During this webinar, you’ll see how Confluent empowers your developers to innovate faster while incrementally refactoring and migrating your existing applications. Register today.

Application Modernization Through Event-Driven Microservices

Daten müssen in Unternehmen immer schneller bereitgestellt werden. Oft scheitert es daran, dass einzelne Quellen nicht ohne großen Aufwand miteinander verknüpft werden können. Die Experten von Confluent, den Entwicklern von Apache Kafka®, und von Attunity, einem führenden Anbieter von Datenintegrations-Software, zeigen zusammen im Online Talk, wie Unternehmen sich den Herausforderungen der Digitalisierung erfolgreich stellen können: 

-Beschleunigung der Bereitstellung von Daten, um Echtzeitanalysen mit Live-Daten aus vielen Quellen zu ermöglichen. 
-Nahtlose Mainframe-Integration und Query-Offload für moderne, verteilte Analyse-Umgebungen. 
-SAP, DB2, Oracle, SQL und mehr - verwandeln Sie eine Datenbank in Minutenschnelle in einen Stream. 
-Erweiterung von Apache Kafka mit Confluent Platform, um alle Möglichkeiten einer modernen Streaming-Plattform auszuschöpfen.

Streaming von SAP-Daten und mehr nach Apache Kafka

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Streaming von SAP-Daten und mehr nach Apache Kafka

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