AWS based Enterprise Digital Transformation Platform (EDTP) is architected as an Event Processing Digital Center around which all Businesses’ current and future data sources, consumers, services, and processes interact. The purpose of the Platform is to enable business innovation and agility by providing semantically-cohesive and structurally-flexible harmonized data across processes and systems and by bringing functions and capabilities to data instead of moving data.
Toyota Financial Services Digital Transformation - Think 2019Slobodan Sipcic
Toyota Financial Services (TFS) and IBM partnered to develop Data & Integration Platform (D&IP) to be the hub around which all current and future TFS data sources, services, and processes interact. To that end IBM have architected and deployed a FOAK event-based data stream processing and streaming integration platform. The main components of the architecture include: Kubernetes, Apache NiFi, Apache Kafka, Schema Registry, Jenkins, S3 and MongoDB. The platform is essential for realizing the TFS' strategic data stream processing and integration needs.
Informatica Cloud Services deliver purpose-built data integration cloud applications to allow business users to integrate data across cloud-based applications and on-premise systems and databases. Informatica Cloud Services address specific business processes (customer/product master synchronization, opportunity to order, etc.) and point-to-point data integration (e.g. Salesforce.com to on premise end-points).
The presentation introduces an innovative approach for accelerated development and deployment of a wide range of agile Services and Data Digital Transformation Solutions that scale. The platform is based on modern 4-tier evolutionary event-driven architectural style including cloud, containers, microservices, events, streaming, and sync & async processing. The approach is instantiated as a reusable asset “Enterprise Digital Transformation Platform”.
Postgres, the leading open source relational database, is positioned as the centerpiece of a pivot from traditional architectures to a micro-services based approach that is in full support of a DevOps motion.
Presented by Marc Linster, Senior Vice President of Product Development at EnterpriseDB, this explores how Postgres meets the key requirements for DevOps. Lister explains how Postgres is developer friendly, supporting the process with a versatile data model using JSONB, integrating other data sources using Foreign Data Wrappers, and how Postgres supports rapid deployment in the cloud and on premises.
(ENT211) Migrating the US Government to the Cloud | AWS re:Invent 2014Amazon Web Services
The US government has built hundreds of applications that must be refactored to task advantage of modern distributed systems. This session discusses EzBake, an open-source, secure big data platform deployed on top of Amazon EC2 and using Amazon S3 and Amazon RDS. This solution has helped speed the US government to the cloud and make big data easy. Furthermore this session discusses critical architecture design decisions through the creation of the platform in order to add additional security, leverage future AWS offerings, and cut total operations and maintenance costs.
Sponsored by CSC
Driven by data - Why we need a Modern Enterprise Data Analytics PlatformArne Roßmann
In order to turn data into opportunities, you need to build a modern data analytics platform. But because literally everything changes so fast, built-in flexibility is paramount.
This presentation covers:
- how to leverage all your data to generate insights
- the capabilities needed to build a flexible platform
- how to incorporate sustainability requirement
Toyota Financial Services Digital Transformation - Think 2019Slobodan Sipcic
Toyota Financial Services (TFS) and IBM partnered to develop Data & Integration Platform (D&IP) to be the hub around which all current and future TFS data sources, services, and processes interact. To that end IBM have architected and deployed a FOAK event-based data stream processing and streaming integration platform. The main components of the architecture include: Kubernetes, Apache NiFi, Apache Kafka, Schema Registry, Jenkins, S3 and MongoDB. The platform is essential for realizing the TFS' strategic data stream processing and integration needs.
Informatica Cloud Services deliver purpose-built data integration cloud applications to allow business users to integrate data across cloud-based applications and on-premise systems and databases. Informatica Cloud Services address specific business processes (customer/product master synchronization, opportunity to order, etc.) and point-to-point data integration (e.g. Salesforce.com to on premise end-points).
The presentation introduces an innovative approach for accelerated development and deployment of a wide range of agile Services and Data Digital Transformation Solutions that scale. The platform is based on modern 4-tier evolutionary event-driven architectural style including cloud, containers, microservices, events, streaming, and sync & async processing. The approach is instantiated as a reusable asset “Enterprise Digital Transformation Platform”.
Postgres, the leading open source relational database, is positioned as the centerpiece of a pivot from traditional architectures to a micro-services based approach that is in full support of a DevOps motion.
Presented by Marc Linster, Senior Vice President of Product Development at EnterpriseDB, this explores how Postgres meets the key requirements for DevOps. Lister explains how Postgres is developer friendly, supporting the process with a versatile data model using JSONB, integrating other data sources using Foreign Data Wrappers, and how Postgres supports rapid deployment in the cloud and on premises.
(ENT211) Migrating the US Government to the Cloud | AWS re:Invent 2014Amazon Web Services
The US government has built hundreds of applications that must be refactored to task advantage of modern distributed systems. This session discusses EzBake, an open-source, secure big data platform deployed on top of Amazon EC2 and using Amazon S3 and Amazon RDS. This solution has helped speed the US government to the cloud and make big data easy. Furthermore this session discusses critical architecture design decisions through the creation of the platform in order to add additional security, leverage future AWS offerings, and cut total operations and maintenance costs.
Sponsored by CSC
Driven by data - Why we need a Modern Enterprise Data Analytics PlatformArne Roßmann
In order to turn data into opportunities, you need to build a modern data analytics platform. But because literally everything changes so fast, built-in flexibility is paramount.
This presentation covers:
- how to leverage all your data to generate insights
- the capabilities needed to build a flexible platform
- how to incorporate sustainability requirement
Benefits of Extending PowerCenter with Informatica CloudAshwin V.
This white paper is for current customers of Informatica PowerCenter who are wondering how to integrate SaaS applications into their IT infrastructure with a cloud integration solution that complements their deployment of PowerCenter
This presentation was delivered at the BI SIG in Palo Alto. It provides an overview of the market shift away from on-premise solutions to on-demand in the business intelligence industry.
Executing on the promise of the Internet of Things (IoT)Dell World
As sensors spread across almost every industry, the Internet of Things is triggering a massive influx of data. Data is coming from all directions – machinery, train tracks, shipping containers, and power stations. As we go from isolated systems to an integrated network of smart devices, enterprises need to develop smart data integration and analytics techniques to generate insights quickly. Not all data collected from sensors needs to be stored and analyzed in the cloud or data center. This session will discuss smart ways of integrating multiple data sources and using analytics techniques at the edge to enable faster decision making.
Webinar delivered in September 2012 featuring experts from Informatica Cloud and customers from Dolby and Actelion. For more information on Informatica Cloud integration applications and platform, please visit: http://www.informaticacloud.com/
Postgres Vision 2018: Your Migration Path - Rabobank and a New DBaaS EDB
Niels Zegveld, Manager, Engineering Database and Middleware of Rabobank, presented a case study at Postgres Vision 2018 that explained building a new Database-as-a-Service (DBaaS) with EDB Postgres so that IT managers would no longer have to interact with the OS.
Idera live 2021: Keynote Presentation The Future of Data is The Data Cloud b...IDERA Software
Join us for an introduction from Idera's CEO Randy Jacops followed by our Keynote Presentation: “The Future of Data is The Data Cloud”; presented by Kent Graziano (AKA The Data Warrior), Chief Technical Evangelist for Snowflake.
Lots has happened at Snowflake in the last few years (including a HUGE IPO!). In this session Kent will give an update on Snowflake’s vision of a world with unlimited access to governed data, enabling every organization to tackle the challenges and opportunities of today and be prepared for the possibilities of tomorrow.
Every company in the world still struggles with how to take all their siloed data and turn it into insight, quickly. The Snowflake Data Cloud enables organizations, in every industry, to democratize their data and become data-driven. This talk will introduce you to The Data Cloud, how it works, and the problems it solves for real companies across the globe and across industries. Kent will also update you on recent governance innovations such as dynamic data masking, tagging, and row access policies that will help you build a robust and secure analytics platform.
About our Keynote Speaker
= = = = = = = = = = = = = = =
Kent Graziano, is the Chief Technical Evangelist for Snowflake and an award-winning author, speaker, and thought leader. He is an Oracle ACE Director (Alumni), Knight of the OakTable Network, a certified Data Vault Master and Data Vault 2.0 Practitioner (CDVP2), and expert solution architect with over 35 years of experience, including more than 25 years of designing advanced data and analytics architectures (in multiple industries). He is an internationally recognized expert in cloud and agile data design. Mr. Graziano has developed and led many successful software and data analytics implementation teams, including multiple agile DW/BI teams. He has written numerous articles, authored 3 Kindle books, co-authored 4 other books (including the 1st Edition of The Data Model Resource Book), and has given hundreds of presentations around the world.
Postgres Vision 2018: The Changing Role of the DBA in the CloudEDB
Not that long ago, DBAs were the gateway to all things database related for enterprises. With the advent of the cloud, automation and DevOps, the DBAs role and responsibilities are rapidly evolving. In this presentation delivered at Postgres Vision 2018, Ken Rugg, Chief Product & Strategy Officer at EDB, explored the 10 most significant ways the role of the DBA has changed and what new, higher value skills a DBA will need be ready for epic change.
Native Spark Executors on Kubernetes: Diving into the Data Lake - Chicago Clo...Mariano Gonzalez
Everybody wants to do big data on a data lake! However, implementing it and maintaining the infrastructure necessary to explore it, such as Spark, has been a historically challenging endeavor. Kubernetes is the tool of choice for cloud orchestration, and Spark continues to be the de facto framework for most data wrangling tasks. We’ve previously tried different data lake architectures, and suffered from the pain that Hadoop carries with it. Finally, we decided to bring the best from the cloud and big data worlds together, and walk you through a session on how to set an endless data lake powered with native Spark executors on Kubernetes
Idera live 2021: Will Data Vault add Value to Your Data Warehouse? 3 Signs th...IDERA Software
Data Vault 2.0 is more than a modeling approach, it is an invaluable methodology that adds value to an array of data warehouse projects. Join Michael Olschimke as he describes the positive impact of Data Vault 2.0 to data warehousing teams. This session also includes a short demonstration of Data Vault Express, a product proven to automate the entire data vault lifecycle to deliver data vault solutions to the business faster, at lower cost and with less risk.
Join us and learn how you can make Data Vaults a practical reality.
Meet the Speaker
= = = = = = = = =
Michael Olschimke has more than 20 years of experience in Information Technology. During the last eight years, he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining and holds a Master of Science in Information Systems from Santa Clara University in Silicon Valley, California. Michael is one of the Chief Executive Officer (CEO) and co-founders of Scalefree where he is responsible for the business direction of the company. He is also co-author of the book "Building a Scalable Data Warehouse with Data Vault 2.0".
Learn how to solve the top 3 challenges Snowflake customers face, and what you can do to ensure high-performance, intelligent analytics at any scale. Ideal for those currently using Snowflake and those considering it.
https://www.brighttalk.com/webcast/18317/422499
Webinar: Hybrid Cloud Integration - Why It's Different and Why It MattersSnapLogic
In this webinar, hear from 451 Research analyst Carl Lehmann about how IT organizations are challenged like never before with several disruptive changes. As hybrid clouds proliferate and as workloads shift across these disruptive venues, enterprises must now consider a thoughtful and strategic approach to hybrid cloud integration.
This presentation features a discussion of the business and technical trends driving hybrid cloud integration, how hybrid cloud integration is different from traditional approaches to integration, and why it matters.
To learn more, visit: www.snaplogic.com/connect-faster
The SnapLogic Integration Cloud for ServiceNowSnapLogic
Learn more about using the SnapLogic Integration Cloud to unlock ServiceNow potential by integrating it with major ITSM Cloud and on-premise applications including BMC Remedy, CA Clarity, SAP SolutionManager, and Workday. SnapLogic’s ServiceNow integration will greatly improve efficiency and quality of IT service management.
To learn more, visit: http://www.snaplogic.com/solutions/servicenow-integration.
Pivotal Big Data Suite: A Technical OverviewVMware Tanzu
How and why are companies like Uber, Netflix and AirBnB so successful, what you need to in order to become successful in the same way that they are and how Pivotal can help you with that.
Speaker: Les Klein, EMEA CTO Data, Pivotal
As open source databases become the enterprise standard, making all data available and accessible for AI has become an even bigger challenge. In the presentation delivered at Postgres Vision 2018, Rob Thomas, General Manager of IBM Analytics, provided answers for how companies can prepare their Information Architecture for AI, leverage containers and multi-cloud for innovation, and deliver a data and analytics strategy at scale.
Weathering the Data Storm – How SnapLogic and AWS Deliver Analytics in the Cl...SnapLogic
In this webinar, learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
We also discuss how Earth Networks gained faster data insights using SnapLogic’s Amazon Redshift data integration and other connectors to quickly integrate, transfer and analyze data from multiple applications.
To learn more, visit: www.snaplogic.com/redshift
Benefits of Extending PowerCenter with Informatica CloudAshwin V.
This white paper is for current customers of Informatica PowerCenter who are wondering how to integrate SaaS applications into their IT infrastructure with a cloud integration solution that complements their deployment of PowerCenter
This presentation was delivered at the BI SIG in Palo Alto. It provides an overview of the market shift away from on-premise solutions to on-demand in the business intelligence industry.
Executing on the promise of the Internet of Things (IoT)Dell World
As sensors spread across almost every industry, the Internet of Things is triggering a massive influx of data. Data is coming from all directions – machinery, train tracks, shipping containers, and power stations. As we go from isolated systems to an integrated network of smart devices, enterprises need to develop smart data integration and analytics techniques to generate insights quickly. Not all data collected from sensors needs to be stored and analyzed in the cloud or data center. This session will discuss smart ways of integrating multiple data sources and using analytics techniques at the edge to enable faster decision making.
Webinar delivered in September 2012 featuring experts from Informatica Cloud and customers from Dolby and Actelion. For more information on Informatica Cloud integration applications and platform, please visit: http://www.informaticacloud.com/
Postgres Vision 2018: Your Migration Path - Rabobank and a New DBaaS EDB
Niels Zegveld, Manager, Engineering Database and Middleware of Rabobank, presented a case study at Postgres Vision 2018 that explained building a new Database-as-a-Service (DBaaS) with EDB Postgres so that IT managers would no longer have to interact with the OS.
Idera live 2021: Keynote Presentation The Future of Data is The Data Cloud b...IDERA Software
Join us for an introduction from Idera's CEO Randy Jacops followed by our Keynote Presentation: “The Future of Data is The Data Cloud”; presented by Kent Graziano (AKA The Data Warrior), Chief Technical Evangelist for Snowflake.
Lots has happened at Snowflake in the last few years (including a HUGE IPO!). In this session Kent will give an update on Snowflake’s vision of a world with unlimited access to governed data, enabling every organization to tackle the challenges and opportunities of today and be prepared for the possibilities of tomorrow.
Every company in the world still struggles with how to take all their siloed data and turn it into insight, quickly. The Snowflake Data Cloud enables organizations, in every industry, to democratize their data and become data-driven. This talk will introduce you to The Data Cloud, how it works, and the problems it solves for real companies across the globe and across industries. Kent will also update you on recent governance innovations such as dynamic data masking, tagging, and row access policies that will help you build a robust and secure analytics platform.
About our Keynote Speaker
= = = = = = = = = = = = = = =
Kent Graziano, is the Chief Technical Evangelist for Snowflake and an award-winning author, speaker, and thought leader. He is an Oracle ACE Director (Alumni), Knight of the OakTable Network, a certified Data Vault Master and Data Vault 2.0 Practitioner (CDVP2), and expert solution architect with over 35 years of experience, including more than 25 years of designing advanced data and analytics architectures (in multiple industries). He is an internationally recognized expert in cloud and agile data design. Mr. Graziano has developed and led many successful software and data analytics implementation teams, including multiple agile DW/BI teams. He has written numerous articles, authored 3 Kindle books, co-authored 4 other books (including the 1st Edition of The Data Model Resource Book), and has given hundreds of presentations around the world.
Postgres Vision 2018: The Changing Role of the DBA in the CloudEDB
Not that long ago, DBAs were the gateway to all things database related for enterprises. With the advent of the cloud, automation and DevOps, the DBAs role and responsibilities are rapidly evolving. In this presentation delivered at Postgres Vision 2018, Ken Rugg, Chief Product & Strategy Officer at EDB, explored the 10 most significant ways the role of the DBA has changed and what new, higher value skills a DBA will need be ready for epic change.
Native Spark Executors on Kubernetes: Diving into the Data Lake - Chicago Clo...Mariano Gonzalez
Everybody wants to do big data on a data lake! However, implementing it and maintaining the infrastructure necessary to explore it, such as Spark, has been a historically challenging endeavor. Kubernetes is the tool of choice for cloud orchestration, and Spark continues to be the de facto framework for most data wrangling tasks. We’ve previously tried different data lake architectures, and suffered from the pain that Hadoop carries with it. Finally, we decided to bring the best from the cloud and big data worlds together, and walk you through a session on how to set an endless data lake powered with native Spark executors on Kubernetes
Idera live 2021: Will Data Vault add Value to Your Data Warehouse? 3 Signs th...IDERA Software
Data Vault 2.0 is more than a modeling approach, it is an invaluable methodology that adds value to an array of data warehouse projects. Join Michael Olschimke as he describes the positive impact of Data Vault 2.0 to data warehousing teams. This session also includes a short demonstration of Data Vault Express, a product proven to automate the entire data vault lifecycle to deliver data vault solutions to the business faster, at lower cost and with less risk.
Join us and learn how you can make Data Vaults a practical reality.
Meet the Speaker
= = = = = = = = =
Michael Olschimke has more than 20 years of experience in Information Technology. During the last eight years, he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining and holds a Master of Science in Information Systems from Santa Clara University in Silicon Valley, California. Michael is one of the Chief Executive Officer (CEO) and co-founders of Scalefree where he is responsible for the business direction of the company. He is also co-author of the book "Building a Scalable Data Warehouse with Data Vault 2.0".
Learn how to solve the top 3 challenges Snowflake customers face, and what you can do to ensure high-performance, intelligent analytics at any scale. Ideal for those currently using Snowflake and those considering it.
https://www.brighttalk.com/webcast/18317/422499
Webinar: Hybrid Cloud Integration - Why It's Different and Why It MattersSnapLogic
In this webinar, hear from 451 Research analyst Carl Lehmann about how IT organizations are challenged like never before with several disruptive changes. As hybrid clouds proliferate and as workloads shift across these disruptive venues, enterprises must now consider a thoughtful and strategic approach to hybrid cloud integration.
This presentation features a discussion of the business and technical trends driving hybrid cloud integration, how hybrid cloud integration is different from traditional approaches to integration, and why it matters.
To learn more, visit: www.snaplogic.com/connect-faster
The SnapLogic Integration Cloud for ServiceNowSnapLogic
Learn more about using the SnapLogic Integration Cloud to unlock ServiceNow potential by integrating it with major ITSM Cloud and on-premise applications including BMC Remedy, CA Clarity, SAP SolutionManager, and Workday. SnapLogic’s ServiceNow integration will greatly improve efficiency and quality of IT service management.
To learn more, visit: http://www.snaplogic.com/solutions/servicenow-integration.
Pivotal Big Data Suite: A Technical OverviewVMware Tanzu
How and why are companies like Uber, Netflix and AirBnB so successful, what you need to in order to become successful in the same way that they are and how Pivotal can help you with that.
Speaker: Les Klein, EMEA CTO Data, Pivotal
As open source databases become the enterprise standard, making all data available and accessible for AI has become an even bigger challenge. In the presentation delivered at Postgres Vision 2018, Rob Thomas, General Manager of IBM Analytics, provided answers for how companies can prepare their Information Architecture for AI, leverage containers and multi-cloud for innovation, and deliver a data and analytics strategy at scale.
Weathering the Data Storm – How SnapLogic and AWS Deliver Analytics in the Cl...SnapLogic
In this webinar, learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
We also discuss how Earth Networks gained faster data insights using SnapLogic’s Amazon Redshift data integration and other connectors to quickly integrate, transfer and analyze data from multiple applications.
To learn more, visit: www.snaplogic.com/redshift
Power Big Data Analytics with Informatica Cloud Integration for Redshift, Kin...Amazon Web Services
Companies are dealing with increasingly large data sets and looking for ways to significantly improve the scale and cost of Big Data analysis with AWS. This hands-on session shows you how you can achieve that. With hundreds of pre-built connectors, you will learn how to get your on-premise and cloud data into Redshift in minutes, not days, and at a significantly reduced costs using Informatica Cloud Integration. With fully certified support for large scale RDS deployments and Informatica’s Vibe Data Stream solution for automated streaming data collection for Kinesis, Informatica offers a comprehensive cloud integration solution for Big Data analytics with AWS. The ability to seamlessly migrate Informatica’s PowerCenter to Amazon Cloud (EC2) offers customers a Cloud migration path, with even higher performance and lower costs.
Cloud Modernization and Data as a Service OptionDenodo
Watch: https://bit.ly/2E99UNO
The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms. Cloud has become a key component of modern architecture design. Data lakes, IoT, NoSQL, SaaS, etc. coexist with relational databases to fuel the needs of modern analytics, ML and AI. Exploring and understanding the data available within your organization is a time-consuming task. And all of this without even knowing if that data will be useful at all.
Attend this session to learn:
- How dynamic data challenges and the speed of change requires a new approach to data architecture.
- Learn how logical data architecture can enable organizations to transition data faster to the cloud with zero downtime.
- Explore how data as a service and other API management capabilities is a must in a hybrid cloud environment.
Transform Your Data Integration Platform From Informatica To ODI Jade Global
Watch this webinar to know why to transform your Data Integration Platform from Informatica To ODI. Join us for the live demo of the InfatoODI tool and learn how you can reduce your implementation time by up to 70% and increase your productivity gains by up to 5 times. For more information, please visit: http://informaticatoodi.jadeglobal.com/
Sebastian Scholze, ATB
Presented at the Open Research Webinars co-organized by the Eclipse Foundation and OW2, Dec. 15, 2020
https://opensourceinnovation.eu/2020/december/
What is the Oracle PaaS Cloud for Developers (Oracle Cloud Day, The Netherlan...Lucas Jellema
The promise of the cloud is substantial. Oracle's public cloud promise goes beyond the generic promise. This presentation describes the promise of the Oracle Public Cloud specifically for developers. It describes the current state of the PaaS Platform, the actual and coming services and what they could mean to a developer. From same platform, different location (DBaaS, JCS) to cloud native stack (ICS, MCS) and services for Citizen Developers, the presentation touches upon virtually all services relevant to developers. The presentation concludes with first the steps enterprises can start taking to move to the cloud and second the steps individual developers could and perhaps should take in order to conquer the clouds.
Evolving From Monolithic to Distributed Architecture Patterns in the CloudDenodo
Watch full webinar here: https://goo.gl/rSfYKV
Gartner states in its Predicts 2018: Data Management Strategies Continue to Shift Toward Distributed,
“As data management activities are becoming more widespread in both distributed processing use cases, like IoT, and demands for new types of data, emerging roles such as data scientists or data engineers are expected to be driving the new data management requirements in the coming two years. These trends indicate that both the collection of data as well as the need to connect to data are rapidly becoming the new normal, and that the days of a single data store with all the data of interest — the enterprise data warehouse — are long gone.”
Data management solutions are becoming distributed, heterogeneous and extremely diverse.
Attend this session to learn:
• How to evolve architecture patterns in the cloud using data virtualization.
• How data virtualization accelerates cloud migration and modernization.
• Successful cloud implementation case studies.
Microsoft investoi integraatioalustoihin kiivaammin kuin koskaan. BizTalk kehittyy edelleen ja Azureen julkaistaan kiihtyvään tahtiin pilvi-, hybridi- ja monitorointikyvykkyyksiä. Visual Studio Team Services tarjoaa välineet monitoimittajaympäristön pystytykseen ja automaatioon.
Bilotin arkkitehdit avaavat tässä esityksessä 13.10.2016 aamiaistilaisuudessa esitetyssä koosteessa relevantit akronyymit, Microsoftin roadmapin ja konkretisoivat integraation parhaita paloja.
Bahrain ch9 introduction to docker 5th birthday Walid Shaari
A hands-on workshop will go over the foundations of the containers platform, including an overview of the platform system components: images, containers, repositories, clustering, and orchestration. The strategy is to demonstrate through "live demo, and hands-on exercises." The reuse case of containers in building a portable distributed application cluster running a variety of workloads including HPC workload.
Qlik and Confluent Success Stories with Kafka - How Generali and Skechers Kee...HostedbyConfluent
Converting production databases into live data streams for Apache Kafka can be labor intensive and costly. As Kafka architectures grow, complexity also rises as data teams begin to configure clusters for redundancy, partitions for performance, as well as for consumer groups for correlated analytics processing. In this breakout session, you’ll hear data streaming success stories from Generali and Skechers that leverage Qlik Data Integration and Confluent. You’ll discover how Qlik’s data integration platform lets organizations automatically produce real-time transaction streams into Kafka, Confluent Platform, or Confluent Cloud, deliver faster business insights from data, enable streaming analytics, as well as streaming ingestion for modern analytics. Learn how these customer use Qlik and Confluent to: - Turn databases into live data feeds - Simplify and automate the real-time data streaming process - Accelerate data delivery to enable real-time analytics Learn how Skechers and Generali breathe new life into data in the cloud, stay ahead of changing demands, while lowering over-reliance on resources, production time and costs.
Cloud-Native Patterns for Data-Intensive ApplicationsVMware Tanzu
Are you interested in learning how to schedule batch jobs in container runtimes?
Maybe you’re wondering how to apply continuous delivery in practice for data-intensive applications? Perhaps you’re looking for an orchestration tool for data pipelines?
Questions like these are common, so rest assured that you’re not alone.
In this webinar, we’ll cover the recent feature improvements in Spring Cloud Data Flow. More specifically, we’ll discuss data processing use cases and how they simplify the overall orchestration experience in cloud runtimes like Cloud Foundry and Kubernetes.
Please join us and be part of the community discussion!
Presenters :
Sabby Anandan, Product Manager
Mark Pollack, Software Engineer, Pivotal
Lessons from Building Large-Scale, Multi-Cloud, SaaS Software at DatabricksDatabricks
The cloud has become one of the most attractive ways for enterprises to purchase software, but it requires building products in a very different way from traditional software
Building Modern Data Platform with Microsoft AzureDmitry Anoshin
This presentation will cover Cloud history and Microsoft Azure Data Analytics capabilities. Moreover, it has a real-world example of DW modernization. Finally, we will check the alternative solution on Azure using Snowflake and Matillion ETL.
DSD-INT 2018 Delft-FEWS new features - Boot VerversDeltares
Presentation by Gerben Boot & Marcel Ververs (Deltares) at the Delft-FEWS International User Days 2018, during the Delft Software Days - Edition 2018. 7 & 8 November 2018, Delft.
Similar to Aws based digital_transformation_platform (20)
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
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
2. Agenda
• Business’ Ecosystems: Data and Integration Challenges
ü Digital Transformation Drivers
ü Digital Transformation Inhibitors
ü Digital Transformation Platform Northern Star Attributes
• How Platform Computing and EDTP Address Challenges
ü Enterprise Digital Transformation Platform
ü EDTP Layered Architecture
ü EDTP Layered Distributed Architecture
• EDTP Deep Dive
ü EDTP Fully Installed Through Automation on AWS
• Demo 1: Business Agility Through Automation of the
EDTP Full Stack Deployment
ü Demo 1a: ”Core Platform Pipeline”
ü Demo 1b: “Tech Components Pipeline”
ü Demo 1c: “Service Templates Pipeline”
• Demo 2: Accelerated Deployment of Digital Transformation
Solutions Based on the EDTP Data and Integration Services
ü Demo 2a: “Data Quality Through Harmonization”
ü Demo 2b: “Diverse Analytics”
ü Demo 2c: “Microservices Through Templating”
• Sample Use Cases:
ü Enterprise Logging Framework
ü Enterprise Interactions Logging Framework
ü Next Generation Campaign Management
ü Insurance Forms Automation
• Discussion and Next Steps
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4. Digital Transformation Drivers
Businesses may take on Digital
Transformation for several reasons. But
by far, the most likely reason is that
they have to: It is a survival issue.
A business’ ability to adapt quickly to
disruptions from incumbents and
startups, to time to market pressures,
and to rapidly changing customer
expectations has become critical.
It is about evolutions and changes
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5. Digital Transformation Inhibitors
Data and integration challenges
hindering businesses’ ability to
transform:
1. Data Quality and Consistency,
2. Coupling on Data & BL levels,
3. Point-to-Point Integration n-
square problem,
4. Point-to-Point with imbedded
transformations,
5. Multiple runtime environments.
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6. Digital Transformation Platform North Star Attributes
• Decoupling
• Adaptability:
⎯ Service Layer
⎯ Data Layer
⎯ Integration Layer
• Agility
• Elasticity
• Experimenting
• Fast-failing
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7. How Platform Computing and
EDTP Address Challenges
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8. Enterprise Digital Transformation Platform
To address the challenges we
developed EDTP for accelerated
development and deployment of a
wide range of agile Services and
Data Digital Transformation
Solutions (DTS) that scale.
The solutions are based on the
modern 4-tier architectural styles
including cloud, containers,
microservices, events, streaming,
and sync & async processing.
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9. EDTP Layered Architecture
EDTP is built on top of core
technologies including Docker
Kubernetes and OpenShift:
• Docker provides container services,
• Kubernetes run and scale containers
for production,
• OpenShift provides developers with
the features to manage their DevOps,
• EDTP builds on to of it to deliver full-
stack automation and accelerators for
delivery of DTS.
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10. EDTP Layered Distributed Architecture
EDTP has a microservices-based architecture of smaller, decoupled
units that work together. It runs on top of OpenShift and Kubernetes
clusters. The services are broken down by function:
• EDTP Technology Components and Services are deployed in
Containers - a virtual boundary of compute and memory resources
assigned to the components. The containers spin-up from Docker
images.
• OpenShift leverages the Kubernetes concept of a POD, which is one or
more Containers deployed together on one Worker Node, and the
smallest compute unit that can be defined, deployed, and managed.
• A Kubernetes Service serves as an internal load balancer. It exposes
an applications running on a set of PODs as a network service.
• An OpenShift Route is a way to expose a Service by giving it an
externally reachable hostname .
• The control plane, which is composed of Master Nodes, manages the
OpenShift cluster.
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13. Demo 1:Business Agility Through
Automation of the EDTP Full
Stack Deployment
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14. Demo 1: Scope
• Demo 1a – “Core Platform Pipeline”: deployment of the EDTP core platform components
(cloud agnostic infrastructure, Docker, Kubernetes and OpenShift) using Terraform.
• Demo 1b – “Tech Components Pipelines”: walkthrough the Jenkins pipelines for
deployments of the EDTP pluggable digital technology components (Ambassador, Nifi,
Zookeeper, Kafka, MongoDB, Istio and Elastic Stack).
• Demo 1c – “Service Templates Pipelines”: walkthrough the Jenkins pipelines for
deployments of the EDTP data and integration service templates (microservices, data
services, data streaming services, aggregation services, event processing services and
several integration patterns). The templates are used for accelerated deployments of
digital transformation solutions.
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15. Demo 1a: Core Platform Pipeline
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EDTP Core Components deployed.
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16. Demo 1a: From Empty VPC
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17. Demo 1a: To Core EDTP
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18. Demo 1b: Tech Components Pipeline
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Technology Components added to
the Core Platform
EDTP Core Components deployed.
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Demo 1b: From Core EDTP
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20. Demo 1b: To Core EDTP & Tech Components
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21. Demo 1c: Service Templates Pipeline
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Technology Components added to
the Core Platform
EDTP Core Components deployed.
Services added to the stack
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22. Demo 1c: Keep Adding Services
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23. Demo 2: “Accelerated Deployment of Digital
Transformation Solutions Based on the EDTP
Data and Integration Service Templates”
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24. Demo 2: Scope
• Demo 2a – “Data Quality Through Harmonization”: deployment of a
data harmonization solution based on the EDTP data streaming
service template.
• Demo 2b – “Diverse Analytics”: deployment of a diverse analytics
solution based on the EDTP data streaming service template for
loading MongoDB JSON data to Snowflake tables for analytics.
• Demo 2c – “Microservices”: deployment of scalable microservices
from the EDTP templates.
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25. Demo 2a: Data Quality Through Harmonization
We demonstrate how EDTP ingress a stream of raw records, harmonizes and materializes records in
MongoDB collections for consumption by others utilizing egress services. The solution is fully
configurable via AVRO schemas (raw, harmonized, and materialize). Several EDTP features are
highlighted during the demo:
• Processing of batch and streaming data including CDC,
• Data quality & master data through harmonization,
• Transforming streaming data in flight via configurable DSL,
• Data-Vault pattern and full audit trail,
• Meta-data management,
• Flexibility of JSON/AVRO schemas as opposed to complex CDM,
• Flexibility of an elastic search index for cataloging, browsing and searching data.
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26. Demo 2a: EDTP Component Interactions
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27. Demo 2b: Diverse Analytics
We demonstrate a diverse analytics solution based on the
EDTP data streaming service template for loading MongoDB
JSON data to Snowflake tables for analytics. The demo is an
extension of Demo 2a and it highlights several EDTP
integration features including:
• Distributed, evolutionary architecture,
• Extensibility via connectors – Snowflake Connector for Kafka,
• Integration via loose coupling of the right systems for the job.
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28. Demo 2: Component Interaction View
1. Raw records
dropped into S3
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2 3
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2. Nifi service processes
records and publishes
on Raw topic
3. Harmonization service
processes raw data into
MongoDB and publishes
them on Harmonized
topic
4. Kafka Snowflake
Connector Service loads
data into Snowflake
table
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29. Demo 2: From S3 to MongoDB to Snowflake
1. Raw records dropped into
S3
2. Nifi service processes
records and publishes on
Raw topic
3. Harmonization service
processes raw data into
MongoDB and publishes
them on Harmonized topic
4. Kafka Snowflake
Connector Service loads
data into Snowflake table
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2
3
4
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30. Demo 2c: Microservices Through Templating
We demonstrate deployment of scalable microservices from the EDTP templates. The demonstration
highlights several EDTP features including:
• Microservices architectural style,
• Decoupling of software components on both business capability and data levels (smart endpoints dumb pipes),
• Exposing services as REST APIs – EDTP as API Economy Platform,
• Four tier digital transformation platform (services tier, aggregation tier, delivery tier and client tier),
• Simplified integration due to loose coupling of software components including mainframe and legacy applications,
• Processing patterns: synchronous and asynchronous with or without retries,
• Event-Driven Architecture Patterns: event notification, event-carried state transfer, event-sourcing and CQRSP (command
query responsibility segregation pattern),
• Handlers – for implementation of client specific business logic,
• Full-stack CI/CD/CT and DevOps.
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31. Demo 2c: Templating Idea
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In Software Development we develop classes and
use them to instantiate objects.
In EDTP Service Development we develop
Templates and Registration Services for a given
Service Class and use them to instantiate new
services of the same class.
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32. Demo 2c: Service Classes based on Patterns
Templating idea is especially powerful when combined with an idea of
using Patterns to define Service Classes
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From Pattern to Service Class Template to Class Instances
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33. Demo 2c: Examples of Patterns
EDTP provides templates for many Patterns including:
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Synchronous Pattern Asynchronous Pattern Asynchronous Pattern with Retries
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34. Demo 2c: Instantiating Service Instances Demo
We demonstrate how to instantiate new Service from Asynchronous Pattern
with Retries
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Asynchronous Pattern with Retries EDTP Service Class Template
Generic Schema
Demo will create
A Service Instance
Generic schema
includes the required
fields, such as:
• TenantID,
• Version #,
• CorelationID.
• Section for Service
Data.
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40. Next Step: Request Demonstration
Email Request to: ssipcic@gmail.com
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41. Request Demonstration
The following EDTP features can be demonstrate on request:
1. Automated Deployment of EDTP in Client’s AWS environment including:
a. Infrastructure,
b. Technology Components,
c. Services.
2. EDTP Data and Integration Capabilities including:
a. Ingestion of streaming and batch data,
b. Harmonization and Materialization of the streaming data,
c. Integration based on the EDTP Connector Services – such integration with Snowflake,
d. Service templating for accelerated deployment of enterprise services.
3. EDTP Support for Pattern Based Service Development including:
a. Event Notification,
b. Event-Carried State Transfer,
c. Event-Sourcing,
d. CQRS,
e. Asynchronous Processing,
f. Service Retries Processing,
g. and many more…
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