This document discusses using Red Hat JBoss Data Virtualization to gain better insights from big data. It describes how data challenges are getting bigger with the growth of big data, cloud, and mobile. Data virtualization software can virtually unify fragmented data across sources and make it available to applications as a single data source. The demo scenario shows how JBoss Data Virtualization is used to mashup sentiment analysis data from Hive with sales data from MySQL to determine if sentiment is a predictor of sales. A live demo then demonstrates integrating these different data sources through a JBoss Data Virtualization virtual data model.
Informatica Solution for SWIFT IntegrationKim Loughead
Overview of Informatica's solution for financial services organizations who need to exchange payment data including SWIFT, NACHA, SEPA, FIX, etc. messages with other financial institutions
Big data insights with Red Hat JBoss Data VirtualizationKenneth Peeples
You’re hearing a lot about big data these days. And big data and the technologies that store and process it, like Hadoop, aren’t just new data silos. You might be looking to integrate big data with existing enterprise information systems to gain better understanding of your business. You want to take informed action.
During this session, we’ll demonstrate how Red Hat JBoss Data Virtualization can integrate with Hadoop through Hive and provide users easy access to data. You’ll learn how Red Hat JBoss Data Virtualization:
Can help you integrate your existing and growing data infrastructure.
Integrates big data with your existing enterprise data infrastructure.
Lets non-technical users access big data result sets.
We’ll also provide typical uses cases and examples and a demonstration of the integration of Hadoop sentiment analysis with sales data.
Enabling Data as a Service with the JBoss Enterprise Data Services Platformprajods
This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank
Denodo 6.0: Self Service Search, Discovery & Governance using an Universal Se...Denodo
Presentation slides taken from Fast Data Strategy Roadshow San Francisco Bay Area.
For more Denodo 6-0 demos, please follow this link:https://goo.gl/XkxJjX
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...Denodo
In this presentation, executives from Denodo preview the new Denodo Platform 6.0 release that delivers Dynamic Query Optimizer, cloud offering on Amazon Web Services, and self-service data discovery and search. Over 30 analysts, led by Claudia Imhoff, provide input on strategic direction and benefits of Denodo 6.0 to the data virtualization and the broader data integration market.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/DR6r3m.
6 Solution Patterns for Accelerating Self-Service BI, Cloud, Big Data, and Ot...Denodo
A presentation by Saptarshi Sengupta, Sr. Product Marketing Manager, at the Fast Data Strategy Roadshow in San Francisco Bay Area.
For more information of Fast Data Strategy Roadshows, follow this link: https://goo.gl/wtwpBN
Informatica Solution for SWIFT IntegrationKim Loughead
Overview of Informatica's solution for financial services organizations who need to exchange payment data including SWIFT, NACHA, SEPA, FIX, etc. messages with other financial institutions
Big data insights with Red Hat JBoss Data VirtualizationKenneth Peeples
You’re hearing a lot about big data these days. And big data and the technologies that store and process it, like Hadoop, aren’t just new data silos. You might be looking to integrate big data with existing enterprise information systems to gain better understanding of your business. You want to take informed action.
During this session, we’ll demonstrate how Red Hat JBoss Data Virtualization can integrate with Hadoop through Hive and provide users easy access to data. You’ll learn how Red Hat JBoss Data Virtualization:
Can help you integrate your existing and growing data infrastructure.
Integrates big data with your existing enterprise data infrastructure.
Lets non-technical users access big data result sets.
We’ll also provide typical uses cases and examples and a demonstration of the integration of Hadoop sentiment analysis with sales data.
Enabling Data as a Service with the JBoss Enterprise Data Services Platformprajods
This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank
Denodo 6.0: Self Service Search, Discovery & Governance using an Universal Se...Denodo
Presentation slides taken from Fast Data Strategy Roadshow San Francisco Bay Area.
For more Denodo 6-0 demos, please follow this link:https://goo.gl/XkxJjX
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...Denodo
In this presentation, executives from Denodo preview the new Denodo Platform 6.0 release that delivers Dynamic Query Optimizer, cloud offering on Amazon Web Services, and self-service data discovery and search. Over 30 analysts, led by Claudia Imhoff, provide input on strategic direction and benefits of Denodo 6.0 to the data virtualization and the broader data integration market.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/DR6r3m.
6 Solution Patterns for Accelerating Self-Service BI, Cloud, Big Data, and Ot...Denodo
A presentation by Saptarshi Sengupta, Sr. Product Marketing Manager, at the Fast Data Strategy Roadshow in San Francisco Bay Area.
For more information of Fast Data Strategy Roadshows, follow this link: https://goo.gl/wtwpBN
Parallel In-Memory Processing and Data Virtualization Redefine Analytics Arch...Denodo
To watch full webinar, follow this link: https://goo.gl/3s9hRG
The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized repository. But this approach is slow and expensive, and sometimes not even feasible, because some data sources are too big to be replicated, and data is often too distributed such as those found in cloud data sources to make a “full centralization” strategy successful.
Attend this webinar to learn:
• Why Logical architectures are the best option when integrating Big Data.
• How Denodo’s parallel in-memory capabilities with dynamic query optimization redefine analytics architectures.
• How IT can meet business demands for data much faster with Data Virtualization.
Agenda:
• Challenges with traditional approaches for analytics architectures.
• Overview of Denodo's parallel in-memory capabilities.
• Product Demo of parallel in-memory capabilities accelerating analytics performance.
• Q&A.
To watch all webinars in Denodo's Packed Lunch Webinar Series, follow this link: https://goo.gl/4xL9wM
Empowering your Enterprise with a Self-Service Data Marketplace (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uqcAN0
Self-service is a major goal of modern data strategists. A successfully implemented self-service initiative means that business users have access to holistic and consistent views of data regardless of its location, source or type. As data unification and data collaboration become key critical success factors for organizations, data catalogs play a key role as the perfect companion for a virtual layer to fully empower those self-service initiatives and build a self-service data marketplace requiring minimal IT intervention.
Denodo’s Data Catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It provides business users with the tool to generate their own insights with proper security, governance, and guardrails.
In this session we will cover:
- The role of a virtual semantic layer in self-service initiatives
- Key ingredients of a successful self-service data marketplace Self-service (consumption) vs. inventory catalogs
- Best practices and advanced tips for successful deployment
- A Demonstration: Product Demo
- Examples of customers using Denodo’s Data Catalog to enable self-service initiatives
Consumption based analytics enabled by Data VirtualizationDenodo
Watch full webinar here: https://buff.ly/2NM5Jtf
An eclectic mix of old and new data drives every decision and every interaction, but too many organisations are attempting unsuccessfully to consolidate this data into a single repository which is time-consuming, resource-intensive, expensive, and risky.
Join this Denodo and HCL Webinar to discover how data virtualization provides an effective modern day architecture and an alternative to data consolidation and the challenges of fragmented data ecosystems and traditional integration approaches. We will share stories and provide multiple perspectives on best practices and solutions.
Content will include:
- Business use cases that highlight challenges and solutions that result in faster time-to-market and greater ROI.
- Suggested approaches to achieve extreme agility for competitive advantage.
Watch full webinar here: https://bit.ly/3FcgiyK
Denodo recently released the Denodo Cloud Survey 2021. Learn about some of the insights we have from the survey as well as some of the use cases Denodo comes across in the cloud. We will also conduct a brief product demonstration highlighting how easy it is to migrate to the cloud and support access to data in hybrid cloud architectures.
In this session not only will we look at what you, the customers are saying in the Denodo Cloud Survey but also:
- We will explore how, in reality, many organizations are already operating in a hybrid or multi-cloud environment and how their needs are being met through the use of a logical data fabric and data virtualization
- We will discuss how easy it is to reduce the risk and minimize disruption when migrating to the cloud
- We will educate you on why a uniform security layer removes regulatory risk in data governance.
- Finally we will demonstrate some of the key capabilities of the Denodo Platform to support the above.
Best Practices: Data Virtualization Perspectives and Best PracticesDenodo
These are the slides from a presentation given by Rajeev Rangachari, Senior Technology Architect, Infosys at Fast Data Strategy Roadshow in San Francisco. Infosys were the official co sponsors of this event.
For more information about our partners Infosys, follow this link: https://goo.gl/wVy5j4
Case Study - Ibotta Builds A Self-Service Data Lake To Enable Business Growth...Vasu S
Read a case study that how Ibotta cut costs thanks to Qubole’s autoscaling and downscaling capabilities, and the ability to isolate workloads to separate clusters
https://www.qubole.com/resources/case-study/ibotta
Virtual Sandbox for Data Scientists at Enterprise ScaleDenodo
View the full webinar here: https://goo.gl/rMQEQK
The Virtual Sandbox is an overarching framework to support the enterprise-scale roll out of data science programs using the industry standard, CRISP-DM methodology.
Attend this session to learn how the Virtual Sandbox optimizes analytical model generation, testing, deployment and subsequent refinement by:
• Easing data access for exploration and mash ups via a governed, self-service data access platform.
• Supporting the creation of logical views using data virtualization for reuse across the organization.
• Facilitating quick and repeatable generation of data sets for analytical model testing and refinement.
• Hastening model deployment by operationalizing the model using shared development pipelines.
Agenda:
• Review the challenges faced by enterprise-scale data science programs.
• Overview of the Virtual Sandbox and its benefits.
• Product Demonstration.
• Q&A
Denodo as the Core Pillar of your API StrategyDenodo
Watch full webinar here: https://buff.ly/2KTz2IB
Most people associate data virtualization with BI and analytics. However, one of the core ideas behind data virtualization is the decoupling of the consumption method from the data model. Why should the need for data requests in JSON over HTTP require extra development? Denodo provides immediate access to its datasets via REST, OData 4, GeoJSON and other protocols, with no coding involved. Easy to scale, cloud friendly and ready to integrate with API management tools, Denodo can be the perfect tool to fulfill your API strategy!
Attend this session to learn:
- What’s the role of Denodo in an API strategy
- Integration between Denodo and other elements of the API stack, like API management tools
- How easy it is to access Denodo as a RESTful endpoint
- Advanced options of Denodo web services: OAuth, OpenAPI, geographical capabilities, etc.
Logical Data Warehouse and Data Lakes can play a role in many different type of projects and, in this presentation, we will look at some of the most common patterns and use cases. Learn about analytical and big data patterns as well as performance considerations. Example implementations will be discussed for each pattern.
- Architectural patterns for logical data warehouse and data lakes.
- Performance considerations.
- Customer use cases and demo.
This presentation is part of the Denodo Educational Seminar, and you can watch the video here goo.gl/vycYmZ.
In Memory Parallel Processing for Big Data ScenariosDenodo
Watch the full webinar on demand here: https://goo.gl/5VyGns
Denodo Platform offers one of the most sought after data fabric capabilities through data discovery, preparation, curation and integration across the broadest range of data sources. As data volume and variety grows exponentially, Denodo Platform 7.0 will offer in-memory massive parallel processing (MPP) capability for the most advanced query optimization in the market.
Attend this session to learn:
• How Denodo Platform 7.0’s native built-in integration with MPP systems will provide query acceleration and MPP caching
• How to successfully approach highly complex big data scenarios, leveraging inexpensive MPP solutions
• With the MPP capability in place, how data driven insights can be generated in real-time with Denodo Platform
Agenda:
• Challenges with traditional architectures
• Denodo Platform MPP capabilities and applications
• Product demonstration
• Q&A
User can run queries via MicroStrategy’s visual interface without the need to write unfamiliar HiveQL or MapReduce scripts. In essence, any user, without programming skill in Hadoop, can ask questions against vast volumes of structured and unstructured data to gain valuable business insights.
SQL Azure Database is a cloud database service from Microsoft. SQL Azure provides web-facing database functionality as a utility service. Cloud-based database solutions such as SQL Azure can provide many benefits, including rapid provisioning, cost-effective scalability, high availability, and reduced management overhead. This paper provides an overview on some scale out strategies, challenges with scaling out on-premise and how you can benefit with scaling out with SQL Azure.
Data Science Operationalization: The Journey of Enterprise AIDenodo
Watch full webinar here: https://bit.ly/3kVmYJl
As we move into a world driven by AI initiatives, we find ourselves facing new and diverse challenges when it comes to operationalization. Creating a solution and putting it into practice, is certainly not the same. The challenges span various organizational and data facades. In many instances, the data scientists may be working in silos and connecting to the live data may not always be possible. But how does one guarantee their developed model in a silo is still relevant to live data? How can we manage the data flow and data access across the entire AI operationalization cycle?
Watch on-demand to explore:
- The journey and challenges of the Data Scientist
- How Denodo data virtualization with data movement streamlines operationalization
- The best practices and techniques when dealing with siloed data
- How customers have used data virtualization in their data science initiatives
SAP Analytics Cloud: Haben Sie schon alle Datenquellen im Live-Zugriff?Denodo
Watch full webinar here: https://bit.ly/3hfEO6d
Die SAP Analytics Cloud (kurz "SAC" genannt) ist ein Service in der Cloud, der umfangreiche Analysefunktionen für Benutzer in einem Produkt bereit stellt. Wie immer bei der SAP ist auch die SAC technologisch gut integriert in die Welt der SAP Systeme.
Doch die Daten, die Unternehmen heutzutage analysieren möchten, befinden sich sehr häufig in den unterschiedlichsten Datenquellen: In relationalen Datenbanken, in Data Lakes, in Webservices, in Dateien, in NoSQL Datenbanken,... Und so stellt sich zwangsläufig die Frage, wie Sie aus der SAC heraus alle Daten konnektieren, transformieren und kombinieren können. Und das möglichst live, d.h. mit Abfragen auf Echtzeit-Daten! Hier kommt die Datenvirtualisierung ins Spiel: Sie bietet Anwendungen (so auch der SAC) einen einheitlichen, integrierten und performanten Zugriff auf SAP Daten und non-SAP Daten.
Erfahren Sie in diesem Webcast:
- Wie die Datenvirtualisierung funktioniert (in a Nutshell)
- Wie Sie aus der SAC heraus auf alle ihre Daten in Echtzeit zugreifen können ("Live Data Connection" genannt)
- Wie die Datenvirtualisierung die Performance auch für Abfragen auf grossen Datenmengen optimiert
GDPR Noncompliance: Avoid the Risk with Data VirtualizationDenodo
You can watch the full webinar on-demand here: https://goo.gl/2f2RYF
In its recent report “Predictions 2018: A year of reckoning”, Forrester predicts that 80% of firms affected by GDPR will not comply with the regulation by May 2018. Of those noncompliant firms, 50% will intentionally not comply.
Compliance doesn’t have to be this difficult! What if you have an opportunity to facilitate GDPR compliance with a mature technology and significant cost reduction? Data virtualization is a mature, cost-effective technology that enables privacy by design to facilitate GDPR compliance.
Attend this session to learn:
• How data virtualization provides a GDPR compliance foundation with data catalog, auditing, and data security.
• How you can enable single enterprise-wide data access layer with guardrails.
• Why data virtualization is a must-have capability for compliance use cases.
• How Denodo’s customers have facilitated compliance.
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEEDwebwinkelvakdag
Data lakes & data warehouses, whether on-premises or in the cloud promise to provide a centralized, cost-effective and scalable foundation for modern analytics. However, organisations continue to struggle to deliver accurate, current and analytics-ready data sets in a timely fashion. Traditional ingestion tools weren’t designed to handle hundreds or even thousands of data sources and the lack of lineage forces data consumers to manually aggregate information from sources they trust. In this session, you’ll learn how to future-proof your modern data environment to meet the needs of the business for the long term. We'll examine how to overcome common challenges, the related must-have technology solutions in the data lake/ data warehousing world, using real-world success stories and even a few architecture tips from industry experts.
Denodo’s Data Catalog: Bridging the Gap between Data and Business (APAC)Denodo
Watch full webinar here: https://bit.ly/3nxGFam
Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails.
In this session you will learn about:
- The role of a virtual semantic layer in self service initiatives
- What are the key capabilities of Denodo’s new Data Catalog
- Best practices and advanced tips for a successful deployment
- How customers are using the Denodo’s Data Catalog to enable self-service initiatives
Transforming Business in a Digital Era with Big Data and MicrosoftPerficient, Inc.
The socially integrated world, the rise of mobile, the Internet of Things - this explosion of data can be directed and used, rather than simply managed. That's why Big Data and advanced analytics are key components of most digital transformation strategies.
In the last year, Microsoft has made key moves to extend its data platform into this realm. Stalwart platforms like SQL Server and Excel join up with new PaaS offerings to make up a dynamic and powerful Big Data/advanced analytics ecosystem.
In this webinar, our experts covered:
-Why you should include Big Data and advanced analytics in your digital transformation strategy
-Challenges facing digital transformation initiatives
-What options the Microsoft toolset offers for Big Data (Hadoop) and advanced analytics
-How to leverage products and services you already own for your digital transformation
Parallel In-Memory Processing and Data Virtualization Redefine Analytics Arch...Denodo
To watch full webinar, follow this link: https://goo.gl/3s9hRG
The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized repository. But this approach is slow and expensive, and sometimes not even feasible, because some data sources are too big to be replicated, and data is often too distributed such as those found in cloud data sources to make a “full centralization” strategy successful.
Attend this webinar to learn:
• Why Logical architectures are the best option when integrating Big Data.
• How Denodo’s parallel in-memory capabilities with dynamic query optimization redefine analytics architectures.
• How IT can meet business demands for data much faster with Data Virtualization.
Agenda:
• Challenges with traditional approaches for analytics architectures.
• Overview of Denodo's parallel in-memory capabilities.
• Product Demo of parallel in-memory capabilities accelerating analytics performance.
• Q&A.
To watch all webinars in Denodo's Packed Lunch Webinar Series, follow this link: https://goo.gl/4xL9wM
Empowering your Enterprise with a Self-Service Data Marketplace (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uqcAN0
Self-service is a major goal of modern data strategists. A successfully implemented self-service initiative means that business users have access to holistic and consistent views of data regardless of its location, source or type. As data unification and data collaboration become key critical success factors for organizations, data catalogs play a key role as the perfect companion for a virtual layer to fully empower those self-service initiatives and build a self-service data marketplace requiring minimal IT intervention.
Denodo’s Data Catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It provides business users with the tool to generate their own insights with proper security, governance, and guardrails.
In this session we will cover:
- The role of a virtual semantic layer in self-service initiatives
- Key ingredients of a successful self-service data marketplace Self-service (consumption) vs. inventory catalogs
- Best practices and advanced tips for successful deployment
- A Demonstration: Product Demo
- Examples of customers using Denodo’s Data Catalog to enable self-service initiatives
Consumption based analytics enabled by Data VirtualizationDenodo
Watch full webinar here: https://buff.ly/2NM5Jtf
An eclectic mix of old and new data drives every decision and every interaction, but too many organisations are attempting unsuccessfully to consolidate this data into a single repository which is time-consuming, resource-intensive, expensive, and risky.
Join this Denodo and HCL Webinar to discover how data virtualization provides an effective modern day architecture and an alternative to data consolidation and the challenges of fragmented data ecosystems and traditional integration approaches. We will share stories and provide multiple perspectives on best practices and solutions.
Content will include:
- Business use cases that highlight challenges and solutions that result in faster time-to-market and greater ROI.
- Suggested approaches to achieve extreme agility for competitive advantage.
Watch full webinar here: https://bit.ly/3FcgiyK
Denodo recently released the Denodo Cloud Survey 2021. Learn about some of the insights we have from the survey as well as some of the use cases Denodo comes across in the cloud. We will also conduct a brief product demonstration highlighting how easy it is to migrate to the cloud and support access to data in hybrid cloud architectures.
In this session not only will we look at what you, the customers are saying in the Denodo Cloud Survey but also:
- We will explore how, in reality, many organizations are already operating in a hybrid or multi-cloud environment and how their needs are being met through the use of a logical data fabric and data virtualization
- We will discuss how easy it is to reduce the risk and minimize disruption when migrating to the cloud
- We will educate you on why a uniform security layer removes regulatory risk in data governance.
- Finally we will demonstrate some of the key capabilities of the Denodo Platform to support the above.
Best Practices: Data Virtualization Perspectives and Best PracticesDenodo
These are the slides from a presentation given by Rajeev Rangachari, Senior Technology Architect, Infosys at Fast Data Strategy Roadshow in San Francisco. Infosys were the official co sponsors of this event.
For more information about our partners Infosys, follow this link: https://goo.gl/wVy5j4
Case Study - Ibotta Builds A Self-Service Data Lake To Enable Business Growth...Vasu S
Read a case study that how Ibotta cut costs thanks to Qubole’s autoscaling and downscaling capabilities, and the ability to isolate workloads to separate clusters
https://www.qubole.com/resources/case-study/ibotta
Virtual Sandbox for Data Scientists at Enterprise ScaleDenodo
View the full webinar here: https://goo.gl/rMQEQK
The Virtual Sandbox is an overarching framework to support the enterprise-scale roll out of data science programs using the industry standard, CRISP-DM methodology.
Attend this session to learn how the Virtual Sandbox optimizes analytical model generation, testing, deployment and subsequent refinement by:
• Easing data access for exploration and mash ups via a governed, self-service data access platform.
• Supporting the creation of logical views using data virtualization for reuse across the organization.
• Facilitating quick and repeatable generation of data sets for analytical model testing and refinement.
• Hastening model deployment by operationalizing the model using shared development pipelines.
Agenda:
• Review the challenges faced by enterprise-scale data science programs.
• Overview of the Virtual Sandbox and its benefits.
• Product Demonstration.
• Q&A
Denodo as the Core Pillar of your API StrategyDenodo
Watch full webinar here: https://buff.ly/2KTz2IB
Most people associate data virtualization with BI and analytics. However, one of the core ideas behind data virtualization is the decoupling of the consumption method from the data model. Why should the need for data requests in JSON over HTTP require extra development? Denodo provides immediate access to its datasets via REST, OData 4, GeoJSON and other protocols, with no coding involved. Easy to scale, cloud friendly and ready to integrate with API management tools, Denodo can be the perfect tool to fulfill your API strategy!
Attend this session to learn:
- What’s the role of Denodo in an API strategy
- Integration between Denodo and other elements of the API stack, like API management tools
- How easy it is to access Denodo as a RESTful endpoint
- Advanced options of Denodo web services: OAuth, OpenAPI, geographical capabilities, etc.
Logical Data Warehouse and Data Lakes can play a role in many different type of projects and, in this presentation, we will look at some of the most common patterns and use cases. Learn about analytical and big data patterns as well as performance considerations. Example implementations will be discussed for each pattern.
- Architectural patterns for logical data warehouse and data lakes.
- Performance considerations.
- Customer use cases and demo.
This presentation is part of the Denodo Educational Seminar, and you can watch the video here goo.gl/vycYmZ.
In Memory Parallel Processing for Big Data ScenariosDenodo
Watch the full webinar on demand here: https://goo.gl/5VyGns
Denodo Platform offers one of the most sought after data fabric capabilities through data discovery, preparation, curation and integration across the broadest range of data sources. As data volume and variety grows exponentially, Denodo Platform 7.0 will offer in-memory massive parallel processing (MPP) capability for the most advanced query optimization in the market.
Attend this session to learn:
• How Denodo Platform 7.0’s native built-in integration with MPP systems will provide query acceleration and MPP caching
• How to successfully approach highly complex big data scenarios, leveraging inexpensive MPP solutions
• With the MPP capability in place, how data driven insights can be generated in real-time with Denodo Platform
Agenda:
• Challenges with traditional architectures
• Denodo Platform MPP capabilities and applications
• Product demonstration
• Q&A
User can run queries via MicroStrategy’s visual interface without the need to write unfamiliar HiveQL or MapReduce scripts. In essence, any user, without programming skill in Hadoop, can ask questions against vast volumes of structured and unstructured data to gain valuable business insights.
SQL Azure Database is a cloud database service from Microsoft. SQL Azure provides web-facing database functionality as a utility service. Cloud-based database solutions such as SQL Azure can provide many benefits, including rapid provisioning, cost-effective scalability, high availability, and reduced management overhead. This paper provides an overview on some scale out strategies, challenges with scaling out on-premise and how you can benefit with scaling out with SQL Azure.
Data Science Operationalization: The Journey of Enterprise AIDenodo
Watch full webinar here: https://bit.ly/3kVmYJl
As we move into a world driven by AI initiatives, we find ourselves facing new and diverse challenges when it comes to operationalization. Creating a solution and putting it into practice, is certainly not the same. The challenges span various organizational and data facades. In many instances, the data scientists may be working in silos and connecting to the live data may not always be possible. But how does one guarantee their developed model in a silo is still relevant to live data? How can we manage the data flow and data access across the entire AI operationalization cycle?
Watch on-demand to explore:
- The journey and challenges of the Data Scientist
- How Denodo data virtualization with data movement streamlines operationalization
- The best practices and techniques when dealing with siloed data
- How customers have used data virtualization in their data science initiatives
SAP Analytics Cloud: Haben Sie schon alle Datenquellen im Live-Zugriff?Denodo
Watch full webinar here: https://bit.ly/3hfEO6d
Die SAP Analytics Cloud (kurz "SAC" genannt) ist ein Service in der Cloud, der umfangreiche Analysefunktionen für Benutzer in einem Produkt bereit stellt. Wie immer bei der SAP ist auch die SAC technologisch gut integriert in die Welt der SAP Systeme.
Doch die Daten, die Unternehmen heutzutage analysieren möchten, befinden sich sehr häufig in den unterschiedlichsten Datenquellen: In relationalen Datenbanken, in Data Lakes, in Webservices, in Dateien, in NoSQL Datenbanken,... Und so stellt sich zwangsläufig die Frage, wie Sie aus der SAC heraus alle Daten konnektieren, transformieren und kombinieren können. Und das möglichst live, d.h. mit Abfragen auf Echtzeit-Daten! Hier kommt die Datenvirtualisierung ins Spiel: Sie bietet Anwendungen (so auch der SAC) einen einheitlichen, integrierten und performanten Zugriff auf SAP Daten und non-SAP Daten.
Erfahren Sie in diesem Webcast:
- Wie die Datenvirtualisierung funktioniert (in a Nutshell)
- Wie Sie aus der SAC heraus auf alle ihre Daten in Echtzeit zugreifen können ("Live Data Connection" genannt)
- Wie die Datenvirtualisierung die Performance auch für Abfragen auf grossen Datenmengen optimiert
GDPR Noncompliance: Avoid the Risk with Data VirtualizationDenodo
You can watch the full webinar on-demand here: https://goo.gl/2f2RYF
In its recent report “Predictions 2018: A year of reckoning”, Forrester predicts that 80% of firms affected by GDPR will not comply with the regulation by May 2018. Of those noncompliant firms, 50% will intentionally not comply.
Compliance doesn’t have to be this difficult! What if you have an opportunity to facilitate GDPR compliance with a mature technology and significant cost reduction? Data virtualization is a mature, cost-effective technology that enables privacy by design to facilitate GDPR compliance.
Attend this session to learn:
• How data virtualization provides a GDPR compliance foundation with data catalog, auditing, and data security.
• How you can enable single enterprise-wide data access layer with guardrails.
• Why data virtualization is a must-have capability for compliance use cases.
• How Denodo’s customers have facilitated compliance.
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEEDwebwinkelvakdag
Data lakes & data warehouses, whether on-premises or in the cloud promise to provide a centralized, cost-effective and scalable foundation for modern analytics. However, organisations continue to struggle to deliver accurate, current and analytics-ready data sets in a timely fashion. Traditional ingestion tools weren’t designed to handle hundreds or even thousands of data sources and the lack of lineage forces data consumers to manually aggregate information from sources they trust. In this session, you’ll learn how to future-proof your modern data environment to meet the needs of the business for the long term. We'll examine how to overcome common challenges, the related must-have technology solutions in the data lake/ data warehousing world, using real-world success stories and even a few architecture tips from industry experts.
Denodo’s Data Catalog: Bridging the Gap between Data and Business (APAC)Denodo
Watch full webinar here: https://bit.ly/3nxGFam
Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails.
In this session you will learn about:
- The role of a virtual semantic layer in self service initiatives
- What are the key capabilities of Denodo’s new Data Catalog
- Best practices and advanced tips for a successful deployment
- How customers are using the Denodo’s Data Catalog to enable self-service initiatives
Transforming Business in a Digital Era with Big Data and MicrosoftPerficient, Inc.
The socially integrated world, the rise of mobile, the Internet of Things - this explosion of data can be directed and used, rather than simply managed. That's why Big Data and advanced analytics are key components of most digital transformation strategies.
In the last year, Microsoft has made key moves to extend its data platform into this realm. Stalwart platforms like SQL Server and Excel join up with new PaaS offerings to make up a dynamic and powerful Big Data/advanced analytics ecosystem.
In this webinar, our experts covered:
-Why you should include Big Data and advanced analytics in your digital transformation strategy
-Challenges facing digital transformation initiatives
-What options the Microsoft toolset offers for Big Data (Hadoop) and advanced analytics
-How to leverage products and services you already own for your digital transformation
Slides: Success Stories for Data-to-CloudDATAVERSITY
Companies are finding accessing data from a variety of sources can be labor-intensive and costly. Oftentimes these companies are looking to cloud solutions, but are then finding the traditional architecture brittle when trying to move data to the cloud, which can drain organizations of time and resources.
Join this webinar to hear several company success stories, the data-to-cloud issues they were encountering, and the steps these companies took to bring their cloud architecture to a successful, real-time analytic solution unlocking massive amounts of fresh enterprise-wide on a continuous basis.
In addition, you will learn how to:
• Modernize the ETL process to one that’s fast, flexible, and scalable
• Supply users with up-to-date, accurate, trusted data
• Increase your time to value with data in the cloud
• Best practices on how to minimize resource overhead
Watch full webinar here: https://bit.ly/2vN59VK
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
- What data virtualization really is.
- How it differs from other enterprise data integration technologies.
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations.
Where does Fast Data Strategy Fit within IT ProjectsDenodo
Fast Data Strategy is a must for organizations to become and be competitive. There are four use cases where Fast Data Strategy fits within IT Projects - Agile BI, Big Data/ Cloud, Data Services, and Single View. In this presentation, you will discover how four customers used data virtualization and Fast Data Strategy for these use cases.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/UxHMuJ.
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
View this webinar presentation as CenturyLink Technology Solutions (Formerly Savvis) and MapR as we deconstruct and demystify “the enterprise big data stack.” We provide you with a more holistic view of the landscape, explore use cases to show how you can derive business value from it, and share best practices for navigating through the fragmented big data environment.
Big Data Expo 2015 - Pentaho The Future of AnalyticsBigDataExpo
Leer hoe Pentaho kan helpen om zowel legacy data en ongestructureerde (Big) data van verschillende bronnen te blenden en te verrijken om zo waarde te creeeren voor uw organisatie. Praktische voorbeelden illustreren hoe Pentaho dit al bij vele organisaties heeft weten te bereiken.
Zie hoe organisaties Pentaho onder andere inzetten om:
• problemen met te lange ETL jobs op te lossen waardoor Data Warehouse loads weer doorgaan,
• de kosten van data-integratie te verlagen,
• het overlopen van traditionele Data Warehouses en bijkomende kosten doet voorkomen,
• Data Quality en Data Governence in uw process inbrengt en
• hoe dit vervolgens embedded in uw applicaties kan worden geanalyseerd.
Originally Published on Sep 23, 2014
IBM InfoSphere BigInsights, an enterprise-ready distribution of Hadoop, is designed to address the challenges of big data and modern IT by analyzing larger volumes of data more cost-effectively. Deployed on the cloud, it enables rapid deployment of clusters and real-time analytics.
FYI: The value of Hadoop and many more questions will be pondered at this year’s Strata/Hadoop World event in NYC (October 15-17, 2014) and certainly at IBM Insight (October 26-30, 2014).
Introduces the Microsoft’s Data Platform for on premise and cloud. Challenges businesses are facing with data and sources of data. Understand about Evolution of Database Systems in the modern world and what business are doing with their data and what their new needs are with respect to changing industry landscapes.
Dive into the Opportunities available for businesses and industry verticals: the ones which are identified already and the ones which are not explored yet.
Understand the Microsoft’s Cloud vision and what is Microsoft’s Azure platform is offering, for Infrastructure as a Service or Platform as a Service for you to build your own offerings.
Introduce and demo some of the Real World Scenarios/Case Studies where Businesses have used the Cloud/Azure for creating New and Innovative solutions to unlock these potentials.
Data Ninja Webinar Series: Accelerating Business Value with Data Virtualizati...Denodo
Watch the full webinar - Session one: Data Ninja Webinar Series by Denodo: https://goo.gl/yAdMpL
The following presentation was used during the webinar entitled: "Accelerating Business Value with Data Virtualization Solutions". It discusses the role of data virtualization in delivering real business value from your new and existing data assets.
This is session 1 of the Data Ninja Webinar Series organized by Denodo. If you want to learn more about some of the solutions enabled by data virtualization, click here to watch the entire series: https://goo.gl/8XFd1O
Fast Data Strategy Houston Roadshow PresentationDenodo
Fast Data Strategy Houston Roadshow focused on the next industrial revolution on the horizon, driven by the application of big data, IoT and Cloud technologies.
• Denodo’s innovative customer, Anadarko, elaborated on how data virtualization serves as the key component in their prescriptive and predictive analytics initiatives, driven by multi-structured data ranging from customer data to equipment data.
• Denodo’s session, Unleashing the Power of Data, described the complexity of the modern data ecosystem and how to overcome challenges and successfully harness insights.
• Our Partner Noah Consulting, an expert analytics solutions provider in the energy industry, explained how your peers are innovating using new business models and reducing cost in areas such as Asset Management and Operations by leveraging Data Virtualization and Prescriptive and Predictive Analytics.
For more information on upcoming roadshows near you, follow this link: https://goo.gl/WBDHiE
Integration intervention: Get your apps and data up to speedKenneth Peeples
SOA has been the defacto methodology for enterprise application and process integration, because loosely coupled components and composite applications are more agile and efficient. The perfect solution? Not quite.
The data’s always been the problem. The most efficient and agile applications and services can be dragged down by the point-to-point data connections of a traditional data integration stack. Virtualized data services can eliminate the friction and get your applications up to speed.
In this webinar we'll show you how to (replay at http://www.redhat.com/en/about/events/integration-intervention-get-your-apps-and-data-speed):
-Quickly and easily create a virtual data services layer to plug data into your SOA infrastructure for an agile and efficient solution
-Derive more business value from your services.
Powering Real-Time Analytics with Data Virtualization on AWS (ASEAN & ANZ)Denodo
Watch full webinar here: https://bit.ly/3h2yLnb
Presented at AWS Summit Online 2021 (ASEAN & ANZ)
Is your organization challenged with modernizing analytics in the cloud, while driving smarter data integration capabilities? With a logical data warehouse powered by data virtualization, you can combine all of the data across the enterprise and make it available to analytical and visualization tools that facilitate timely, insightful, and impactful decisions.
In this session, you will learn how data virtualization helps enterprises gain a unified view of the data across AWS, multi-cloud and hybrid cloud easily with a virtual data layer that abstracts business users from the technical details of where data resides.
Data Ninja Webinar Series: Realizing the Promise of Data LakesDenodo
Watch the full webinar: Data Ninja Webinar Series by Denodo: https://goo.gl/QDVCjV
The expanding volume and variety of data originating from sources that are both internal and external to the enterprise are challenging businesses in harnessing their big data for actionable insights. In their attempts to overcome big data challenges, organizations are exploring data lakes as consolidated repositories of massive volumes of raw, detailed data of various types and formats. But creating a physical data lake presents its own hurdles.
Attend this session to learn how to effectively manage data lakes for improved agility in data access and enhanced governance.
This is session 5 of the Data Ninja Webinar Series organized by Denodo. If you want to learn more about some of the solutions enabled by data virtualization, click here to watch the entire series: https://goo.gl/8XFd1O
Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...Denodo
Watch full webinar here: https://bit.ly/32TT2Uu
Data virtualization is not just for self-service, it’s also a first-class citizen when it comes to modern data platform architectures. Technology has forced many businesses to rethink their delivery models. Startups emerged, leveraging the internet and mobile technology to better meet customer needs (like Amazon and Lyft), disrupting entire categories of business, and grew to dominate their categories.
Schedule a complimentary Data Virtualization Discovery Session with g2o.
Traditional companies are still struggling to meet rising customer expectations. During this webinar with the experts from g2o and Denodo we covered the following:
- How modern data platforms enable businesses to address these new customer expectation
- How you can drive value from your investment in a data platform now
- How you can use data virtualization to enable multi-cloud strategies
Leveraging the strategy insights of g2o and the power of the Denodo platform, companies do not need to undergo the costly removal and replacement of legacy systems to modernize their systems. g2o and Denodo can provide a strategy to create a modern data architecture within a company’s existing infrastructure.
SendGrid Improves Email Delivery with Hybrid Data WarehousingAmazon Web Services
When you received your Uber ‘Tuesday Evening Ride Receipt’ or Spotify’s ‘This Week’s New Music’ email, did you think about how they got there?
SendGrid’s reliable email platform delivers each month over 20 Billion transactional and marketing emails on behalf of many of your favorite brands, including Uber, Airbnb, Spotify, Foursquare and NextDoor.
SendGrid was looking to evolve its data warehouse architecture in order to improve decision making and optimize customer experience. They needed a scalable and reliable architecture that would allow them to move nimbly and efficiently with a relatively small IT organization, while supporting the needs of both business and technical users at SendGrid.
SendGrid’s Director of Enterprise Data Operations will be joining architects from Amazon Web Services (AWS) and Informatica to discuss SendGrid’s journey to a hybrid cloud architecture and how a hybrid data warehousing solution is optimized to support SendGrid’s analytics initiative. Speakers will also review common technologies and use cases being deployed in hybrid cloud today, common data management challenges in hybrid cloud and best practices for addressing these challenges.
Join us to learn:
• How to evolve to a hybrid data warehouse with Amazon Redshift for scalability, agility and cost efficiency with minimal IT resources
• Hybrid cloud data management use cases
• Best practices for addressing hybrid cloud data management challenges
Connect to the IoT with a lightweight protocol MQTTKenneth Peeples
Everything is connected in the Internet of Things. People, devices, machines, and more are all part of a network - sending and receiving data to and from other "things." What new opportunities can the IoT create for your business? The lightweight protocol MQTT can help connect to the Internet of Things.
Maximize information exchange in your enterprise with AMQPKenneth Peeples
Businesses need to efficiently exchange information inside the enterprise as well as with other enterprises. In order to reduce cost and enhance business agility, an open messaging standard is a necessity for interoperability and integration. Advanced Message Queueing Protocol (AMQP) is the open standard wire-level binary messaging protocol that describes how a message should be structured and sent across the network.
Join this webinar to learn more about:
-What AMQP is and it's applications.
-The features and benefits of AMQP.
-Why you should use AMQP in your enterprise.
-The differences between AMQP and other messaging standards, such as JMS.
-Topologies and architectures possible through the use of AMQP.
To build up any non-trivial business processing, you may have to connect systems that are exposed by web-services, fire off events over message queues, notify users via email or social networking, and much more.
Apache Camel is a lightweight integration framework that helps you connect systems in a consistent and reliable way. Focus on the business reasons behind what's being integrated, not the underlying details of how.
The presentation covers-
1. Red Hat JBoss Developer Program
2. Red Hat JBoss Fuse
3. Red Hat JBoss Data Virtualization
The workshop was recorded and we will provide a link once it has been posted.
Middleware Security for Apache CXF, Camel, ActiveMQ and Karaf as well as others continue to be an ongoing concern especially around Authentication, Authorization, Data at Rest and Data in Transit. The session will include a presentation and demonstrations of implementing Authentication (AuthN) and Authorization (AuthZ) as well as other security topics.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
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/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
"Impact of front-end architecture on development cost", Viktor Turskyi
JDV Big Data Webinar v2
1. GAIN BETTER INSIGHTS FROM BIG DATA
USING
RED HAT JBOSS DATA VIRTUALIZATION
Syed Rasheed Product Marketing Manager
Kenny Peeples Technical Marketing Manager
Red Hat Corporation
December 4th, 2013
2. Red Hat is…
“By running tests and executing numerous examples for specific teams, we were able to prove […] not
only would the solution work, but it will perform better & at a fraction of the costs.”
MICHAEL BLAKE, Director, Systems & Architecture
2
RED HAT CONFIDENTIAL
3. Agenda
●
Data challenges getting bigger
●
Red Hat Big Data Strategy and Platform
●
Data Virtualization Overview
●
Customer Use Case for Big Data integration using Data
Virtualization
●
●
3
Demo
Q&A
RED HAT CONFIDENTIAL
4. Poll Question #1
●
What are your plans regarding usage of Hadoop
technology at your company?
–
–
Under consideration
–
Under development
–
Project level deployment
–
4
No plans
Enterprise level deployment
RED HAT CONFIDENTIAL
5. Poll Question #2
●
What are your plans regarding usage of Data Virtualization
technology at your company?
–
–
Under consideration
–
Under development
–
Project level deployment
–
5
No plans
Enterprise level deployment
RED HAT CONFIDENTIAL
6. Data Driven Economy
Data is becoming the new raw
material of business: an economic
input almost on a par with capital and
labor. “Every day I wake up and ask,
‘how can I flow data better, manage
data better, analyze data better?”
CIO - Wal-Mart
6
RED HAT CONFIDENTIAL
7. Data Challenges Getting Bigger
Big Data, Cloud, and Mobile
Existing Data Integration approaches are not sufficient
●
Extracting and moving data adds latency and cost
●
Every project solves data access and integration in a different way
●
Solutions are tightly coupled to data sources
●
Poor flexibility and agility
BI Reports
Operational
Reports
Enterprise
Applications
SOA
Applications
Mobile
Applications
Constant
Change
How to align?
Integration Complexity
Siloed &
Complex
Hadoop
7
NoSQL
Cloud Apps
Data Warehouse
& Databases
Mainframe
RED HAT CONFIDENTIAL
XML, CSV
& Excel Files
Enterprise Apps
8. Business Objective
Turn Data into Actionable Information
Only
28%
Users have any meaningful
data access
Reduce costs for finding and
accessing highly fragmented data
Over
70%
BI project efforts lies in the
integration of source data
Improve time to market for new
products and services by simplifying
data access and integration
Deliver IT solution agility
necessary to capitalize on constantly
changing market conditions
Transform fragmented data into
actionable information that delivers
competitive advantage
8
RED HAT CONFIDENTIAL
9. Red Hat’s Big Data Strategy
●
Reduce Information Gap thru cost effectively making
ALL data easily consumable for analytics
Process
Integrate
Data to Actionable Information Cycle
9
RED HAT CONFIDENTIAL
Analytics
Data
Capture
10. Red Hat Big Data
Platform
Platform
RHEL
Platform Integration
&
Optimization
Hadoop
Integration
Middleware
JBoss Data
Virtualization
Fedora
Big Data SIG
Apache
Hadoop
Hadoop
Distributions
Hadoop On
Red Hat Storage
Storage
10
RED HAT CONFIDENTIAL
Hadoop
On
OpenStack
Cloud /
Virtualization
11. Red Hat Big Data
Platform
Platform
RHEL
Platform Integration
&
Optimization
Hadoop
Integration
Middleware
Fedora
Big Data SIG
JBoss Data
Virtualization
Apache
Hadoop
Hadoop
Distributions
Hadoop On
Red Hat Storage
Storage
11
RED HAT CONFIDENTIAL
Hadoop
On
OpenStack
Cloud /
Virtualization
12. What does Data Virtualization software do?
Turn Fragmented Data into Actionable Information
Data Virtualization software virtually
unifies data spread across various
disparate sources; and makes it
available to applications as a single
consolidated data source.
DATA CONSUMERS
BI Reports
The data virtualization software
implements 3 steps process to bridge
data sources and data consumers:
●
●
●
12
Connect: Fast access to data from
diverse data sources
Compose: Easily create unified
virtual data models and views by
combining and transforming data
from multiple sources.
Consume: Expose consistent
information to data consumers in
the right form thru standard data
access methods.
SOA Applications
Easy,
Real-time
Information
Access
Virtual Consolidated Data Source
Data Virtualization Software
•
•
•
Consume
Compose
Connect
Oracle DW
SAP
Hadoop
DATA SOURCES
RED HAT CONFIDENTIAL
Salesforce.com
Virtualize
Abstract
Federate
Siloed &
Complex
13. Turn Fragmented Data into Actionable Information
Mobile Applications
Data
Consumers
JBoss
Data Virtualization
ESB, ETL
BI Reports & Analytics
SOA Applications & Portals
Design Tools
Standard based Data Provisioning
JDBC, ODBC, SOAP, REST, OData
Consume
Easy,
Real-time
Information
Access
Dashboard
Unified Virtual Database / Common Data Model
Compose
Unified Customer
View
Unified
Product View
Unified
Supplier View
Optimization
Caching
Virtualize
Abstract
Federate
Security
Connect
Native Data Connectivity
Data
Sources
Metadata
Siloed &
Complex
Hadoop
13
NoSQL
Cloud Apps
Data Warehouse
& Databases
Mainframe
RED HAT CONFIDENTIAL
XML, CSV
& Excel Files
Enterprise Apps
14. JBoss Data Virtualization:
Supported Data Sources
Enterprise RDBMS:
• Oracle
• IBM DB2
• Microsoft SQL Server
• Sybase ASE
• MySQL
• PostgreSQL
• Ingres
Enterprise EDW:
• Teradata
• Netezza
• Greenplum
14
Hadoop:
• Apache
• HortonWorks
• Cloudera
• More coming…
Office Productivity:
• Microsoft Excel
• Microsoft Access
• Google Spreadsheets
Specialty Data Sources:
• ModeShape Repository
• Mondrian
• MetaMatrix
• LDAP
RED HAT CONFIDENTIAL
NoSQL:
• JBoss Data Grid
• MongoDB
• More coming…
Enterprise & Cloud
Applications:
• Salesforce.com
• SAP
Technology Connectors:
• Flat Files, XML Files,
XML over HTTP
• SOAP Web Services
• REST Web Services
• OData Services
15. Key New Features and Capabilities
●
Data connectivity enhancements
–
–
NoSQL (MongoDB – Tech Preview) and JBoss Data Grid
–
●
Hadoop Integration (Hive – Big Data),
Odata support (SAP integration)
Developer Productivity improvements
–
–
Enhanced column level security,
–
●
New VDB Designer 8 and integration with JBoss Developer Studio v7
VDB import/reuse, and native queries
Simplify deployment and packaging
–
–
●
Requires JBoss EAP only; included with subscription
Remove dependency with SOA Platform
Business Dashboard
–
15
New rapid data reporting/visualization capability
RED HAT CONFIDENTIAL
16. JBoss Data Virtualization – Use Cases
Self-Service
Business
Intelligence
The virtual, reusable data model provides business-friendly representation of data,
allowing the user to interact with their data without having to know the complexities of their
database or where the data is stored and allowing multiple BI tools to acquire data from
centralized data layer. Gain better insights from Big Data using JBoss Data Virtualization to
integrate with existing information sources.
360◦
Unified
View
Deliver a complete view of master & transactional data in real-time. The virtual data layer
serves as a unified, enterprise-wide view of business information that improves users’ ability
to understand and leverage enterprise data.
Agile SOA
Data
Services
A data virtualization layer deliver the missing data services layer to SOA applications. JBoss
Data Virtualization increases agility and loose coupling with virtual data stores without the
need to touch underlying sources and creation of data services that encapsulate the data
access logic and allowing multiple business service to acquire data from centralized data
layer.
Regulatory
Compliance
Data Virtualization layer deliver the data firewall functionality. JBoss Data Virtualization
improves data quality via centralized access control, robust security infrastructure and
reduction in physical copies of data thus reducing risk. Furthermore, the metadata
repository catalogs enterprise data locations and the relationships between the data in
various data stores, enabling transparency and visibility.
16
RED HAT CONFIDENTIAL
17. Big Data integration
use case
Retail Customer Use Case
Gain Better Insight from Big Data for Intelligent Inventory Management
●
Objective:
–
●
Right merchandise, at right time and price
JBoss
BRMS
Problem:
–
●
Analytical Apps
Data Driven
Decision
Management
Cannot utilize social data and sentiment
analysis with their inventory and purchase
management system
Solution:
–
Leverage JBoss Data Virtualization to
mashup Sentiment analysis data with
inventory and purchasing system data.
Leveraged BRMS to optimize pricing and
stocking decisions.
Consume
Compose
Connect
JBoss Data Virtualization
Hive
Purchase Mgmt
Application
Inventory
Databases
Sentiment
Analysis
17
RED HAT CONFIDENTIAL
18. Better Together - Big Data and Data Virtualization
Hadoop not another Silo - Customers Combine Multiple Technologies
●
Combine structured and unstructured analysis
–
●
Combine high velocity and historical analysis
–
●
Analyze and react to data in motion; adjust models with deep
historical analysis
Reuse structured data for analysis
–
18
Augment data warehouse with additional external sources, such as
social media
Experimentation and ad-hoc analysis with structured data
RED HAT CONFIDENTIAL
19. Better Together - Big Data and Data Virtualization
BI Analytics
(historical, operational, predictive)
SOA Composite Applications
Data Integration
JBoss Data Virtualization
Capture & Process
In-memory Cache
JBoss Data Grid
Messaging and Event Processing
JBoss A-MQ and JBoss BRMS
J
Structured Data
19
Streaming
Data
RED HAT CONFIDENTIAL
Hadoop
Semi-Structured
Data
Red Hat Storage
Red Hat Enterprise Linux & Virtualization
Integrate & Analyze
Capture, Process and Integrate Data Volume, Velocity, Variety
20. Consider...
Inconsistent,
Incomplete
Information
Uninformed,
Delayed Decisions
Costly Business Risk
and Exposure
How would your organization change…
●
●
●
20
If data were readily reusable in place rather than
requiring significant effort to build new intermediary data
tiers?
If data could be repurposed quickly into new applications
and business processes?
If all applications and business processes could get all of
the information needed in the form needed, where
needed and when needed?
RED HAT CONFIDENTIAL
21. Red Hat JBoss Middleware
Business Process
Management
•
•
JBoss BRMS
JBoss BPM Suite
Application
Integration
•
•
•
JBoss A-MQ
JBoss Fuse
JBoss Fuse Service Works
Data Integration
Foundation
ACCELERATE
21
•
•
•
•
JBoss Data
Virtualization
JBoss EAP
JBoss Web Server
JBoss Data Grid
INTEGRATE
RED HAT CONFIDENTIAL
AUTOMATE
JBoss Operations Network
JBoss Developer Studio
JBoss Portal
•
•
•
Management
Tools
Development
Toolsh
User Interaction
23. Demo Scenario
●
Objective:
–
●
Determine if sentiment data from the
first week of the Iron Man 3 movie is a
predictor of sales
Problem:
–
●
Excel Powerview and
DV Dashboard to
analyze the
aggregated data
Cannot utilize social data and
sentiment analysis with sales
management system
Consume
Compose
Connect
Solution:
–
JBoss Data Virtualization
Leverage JBoss Data Virtualization to
mashup Sentiment analysis data with
ticket and merchandise sales data on
MySQL into a single view of the data.
Hive
SOURCE 1: Hive/Hadoop
contains twitter data
including sentiment
23
RED HAT CONFIDENTIAL
SOURCE 2: MySQL data
that includes ticket and
merchandise sales
24. Demonstration System Requirements
• JDK
– Oracle JDK 1.6, 1.7 or OpenJDK 1.6 or 1.7
• JBoss Data Virtualization v6 Beta
– http://jboss.org/products/datavirt.html
• JBoss Developer Studio
– http://jboss.org/products
• JBoss Integration Stack Tools (Teiid)
– https://devstudio.jboss.com/updates/7.0-development/integration-stack/
• Slides, Code and References for demo
– https://github.com/DataVirtualizationByExample/Mashup-with-Hive-andMySQL
• Hortonworks Data Platform (A VM for testing Hive/Hadoop)
– http://hortonworks.com/products/hdp-2/#install
• Red Hat Storage
– http://www.redhat.com/products/storage-server/
24
RED HAT CONFIDENTIAL
61. Why Red Hat for Big Data?
●
Transform ALL data into actionable information
–
Cost Effective, Comprehensive Platform
–
Community based Innovation
–
Enterprise Class Software and Support
Process
Integrate
Data to Actionable Information Cycle
61
RED HAT CONFIDENTIAL
Information
Data
Capture
62. Red Hat Big Data
Platform
Platform
RHEL
Platform Integration
&
Optimization
Hadoop
Integration
Middleware
JBoss Data
Virtualization
Fedora
Big Data SIG
Apache
Hadoop
Hadoop
Distributions
Hadoop On
Red Hat Storage
Storage
62
RED HAT CONFIDENTIAL
Hadoop
On
OpenStack
Cloud /
Virtualization
Today the collaboration between Red Hat and SAP continues.Engineers from both companies are working towards a common target — enhancing the interoperability of JBoss Enterprise middleware with the existing SAP landscape. Specifically, Red Hat and SAP are collaborating on development efforts for tools that are designed to simplify the integration of SAP data and business processes with other enterprise data and applications.The aim of such integration, of course, is a more intelligent enterprise — one that can maximize the value of your data assets in accelerating business decisions.
To remember the pragmatic definition of big data, think SPA — the three questions of big data:Store. Can you capture and store the data?Process. Can you cleanse, enrich, and analyze the data? Access. Can you retrieve, search, integrate, and visualize the data?
Easy data accessibility thru standard interfaces e.g SQL, Web Services etc.Exposes non-relational sources as relationalRead and write data in placeReal time accessNo data replication/duplication requiredSo lets define what are the attributes of Data Virtualization solution. The first thing that data virtualization product does is virtualizes the data, regardless of where it is. It makes the data look as if it was in one place. So applications don’t need to know where the data is, because the data virtualization software does that for you.The second thing that data virtualization does is federating the data. You’re running a query which spans multiple databases or data warehouses. You want that query to run sufficiently and with optimum performance. So in order to do that, you need a variety of techniques, like caching, like pushdown optimization, you need to have knowledge of the source databases to make this whole environment run as smoothly and efficiently as possible.Thirdly, it abstracts the data into the format of choice. It conforms the data so that it’s in a consistent format, and that’s regardless of the native structure or syntax of the data. And one point I should make here is that you want to be able to – you don’t want a tool which will force you to have a particular format. What you want is a format that suits your business, rather than one which is imposed on you. So you need to have, the data virtualization tool itself needs to be agile and flexible, in the sense of being able to provide a data format that suits you.And then the fourth thing you have a requirement for is to present the data in a consistent fashion. And it doesn’t matter whether it’s a business intelligence application, it’s a mash-up, it’s a regular application; whatever it is, you want to be able to present the data in a consistent format to the business, to participating applications. Imagine if all the up-to-date data you need to take informed action, is available to you on demand as one unified source. This is the capability provided by Data Virtualization software.
Easy data accessibility thru standard interfaces e.g SQL, Web Services etc.Exposes non-relational sources as relationalRead and write data in placeReal time accessNo data replication/duplication requiredThe data virtualization software provides 3 step process to connect data sources and data consumers:Connect: Fast Access to data from disparate systems (databases, files, services, applications, etc.) with disparate access method and storage models. Compose: Easily create reusable, unified common data model and virtual data views by combining and transforming data from multiple sources.Consume: Seamlessly exposing unified, virtual data model and views available in real-time through a variety of open standards data access methods to support different tools and applications.JBoss Data Virtualization software implements all three steps internally while isolating/hiding complexity of data access methods, transformation and data merge logic details from information consumers.This enables organization to acquire actionable, unified information when they want it and the way they want it; i.e. at the business speed.
To remember the pragmatic definition of big data, think SPA — the three questions of big data:Store. Can you capture and store the data?Process. Can you cleanse, enrich, and analyze the data? Access. Can you retrieve, search, integrate, and visualize the data?