This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
On Analyzing and Specifying Concerns for Data as a ServiceHong-Linh Truong
Providing data as a service has not only fostered the
access to data from anywhere at anytime but also reduced the
cost of investment. However, data is often associated with various
concerns that must be explicitly described and modeled in order
to ensure that the data consumer can find and select relevant
data services as well as utilize the data in the right way. In
particular, the use of data is bound to various rules imposed by
data owners and regulators. Although, technically Web services
and database technologies allow us to quickly expose data sources
as Web services, until now, research has not been focused on the
description of data service concerns, thus hindering the discovery,
selection and utilization of data services. In this paper, we analyze
major concerns for data as a service, model these concerns, and
discuss how they can be used to improve the search and utilization
of data services.
Big Data as a Service - A Market and Technology PerspectiveEMC
This white paper looks at what service providers can do to address the booming Big Data market and how solutions that leverage EMC technologies, such as Greenplum and Isilon, can be stepping stones on the path to providing Big Data in the cloud.
Data As Service (Team: 5, Project: 17) Pankaj Shipte
Data as service is a project we designed under the course of Cloud Computing in IIIT Hyderabad.
Credits:
1. Paritosh Garg (201201060)
2. Chetan Kasireddy (201201124)
3. Ankit Yadav (201405590)
4. Pankaj Shipte (201405614)
DataGraft: Data-as-a-Service for Open Datadapaasproject
Tutorial at "The Data Matters Series – Transforming Service Industry via Big Data Analytics", May 4, 2016, Cyberjaya, Malaysia
http://www.eventbrite.com/e/the-data-matters-series-transforming-service-industry-via-big-data-analytics-tickets-24617911837
On Analyzing and Specifying Concerns for Data as a ServiceHong-Linh Truong
Providing data as a service has not only fostered the
access to data from anywhere at anytime but also reduced the
cost of investment. However, data is often associated with various
concerns that must be explicitly described and modeled in order
to ensure that the data consumer can find and select relevant
data services as well as utilize the data in the right way. In
particular, the use of data is bound to various rules imposed by
data owners and regulators. Although, technically Web services
and database technologies allow us to quickly expose data sources
as Web services, until now, research has not been focused on the
description of data service concerns, thus hindering the discovery,
selection and utilization of data services. In this paper, we analyze
major concerns for data as a service, model these concerns, and
discuss how they can be used to improve the search and utilization
of data services.
Big Data as a Service - A Market and Technology PerspectiveEMC
This white paper looks at what service providers can do to address the booming Big Data market and how solutions that leverage EMC technologies, such as Greenplum and Isilon, can be stepping stones on the path to providing Big Data in the cloud.
Data As Service (Team: 5, Project: 17) Pankaj Shipte
Data as service is a project we designed under the course of Cloud Computing in IIIT Hyderabad.
Credits:
1. Paritosh Garg (201201060)
2. Chetan Kasireddy (201201124)
3. Ankit Yadav (201405590)
4. Pankaj Shipte (201405614)
DataGraft: Data-as-a-Service for Open Datadapaasproject
Tutorial at "The Data Matters Series – Transforming Service Industry via Big Data Analytics", May 4, 2016, Cyberjaya, Malaysia
http://www.eventbrite.com/e/the-data-matters-series-transforming-service-industry-via-big-data-analytics-tickets-24617911837
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
Introduction to Data Virtualization (session 1 from Packed Lunch Webinar Series)Denodo
This first session in a series of six ‘Packed Lunch’ webinars provides an overview of Data Virtualization technology, its applications and how it is adding business value to organizations around the world.
More information and FREE registrations to this webinar: http://goo.gl/z7mq2S
Landing page for the entire Packed Lunch webinar series: http://goo.gl/NATMHw
Attend & get unique insights into:
What Data Virtualization is and what sets it apart from traditional integration tools
How it both complements and leverages existing enterprise architectures
The Denodo Data Virtualization platform and its capabilities
Data Services and the Modern Data Ecosystem (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2YdstdU
Digital Transformation has changed IT the way information services are delivered. The pace of business engagement, the rise of Digital IT (formerly known as “Shadow IT), has also increased demands on IT, especially in the area of Data Management.
Data Services exploits widely adopted interoperability standards, providing a strong framework for information exchange but also has enabled growth of robust systems of engagement that can now exploit information that was normally locked away in some internal silo with Data Virtualization.
We will discuss how a business can easily support and manage a Data Service platform, providing a more flexible approach for information sharing supporting an ever-diverse community of consumers.
Watch this on-demand webinar as we cover:
- Why Data Services are a critical part of a modern data ecosystem
- How IT teams can manage Data Services and the increasing demand by businesses
- How Digital IT can benefit from Data Services and how this can support the need for rapid prototyping allowing businesses to experiment with data and fail fast where necessary
- How a good Data Virtualization platform can encourage a culture of Data amongst business consumers (internally and externally)
Cloud Modernization and Data as a Service OptionDenodo
Watch here: https://bit.ly/36tEThx
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. Dealing with bureaucracy, different languages and protocols, and the definition of ingestion pipelines to load that data into your data lake can be complex. 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 – one that is real-time, agile and doesn’t rely on physical data movement.
- Learn how logical data architecture can enable organizations to transition data faster to the cloud with zero downtime and ultimately deliver faster time to insight.
- Explore how data as a service and other API management capabilities is a must in a hybrid cloud environment.
Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)Denodo
Watch full webinar here: https://bit.ly/3dudL6u
It's not if you move to the cloud, but when. Most organisations are well underway with migrating applications and data to the cloud. In fact, most organisations - whether they realise it or not - have a multi-cloud strategy. Single, hybrid, or multi-cloud…the potential benefits are huge - flexibility, agility, cost savings, scaling on-demand, etc. However, the challenges can be just as large and daunting. A poorly managed migration to the cloud can leave users frustrated at their inability to get to the data that they need and IT scrambling to cobble together a solution.
In this session, we will look at the challenges facing data management teams as they migrate to cloud and multi-cloud architectures. We will show how the Denodo Platform can:
- Reduce the risk and minimise the disruption of migrating to the cloud.
- Make it easier and quicker for users to find the data that they need - wherever it is located.
- Provide a uniform security layer that spans hybrid and multi-cloud environments.
An Introduction to Data Virtualization in 2018Denodo
Watch full webinar on demand here: https://goo.gl/Rdrc1w
"Through 2020, 50% of enterprises will implement some form of data virtualization as one enterprise production option for data integration" according to Gartner. It is clear that data virtualization has become a driving force for companies to implement an agile, real-time and flexible enterprise data architecture.
Attend this session to learn:
• What data virtualization actually means and how it differs from traditional data integration approaches
• The all important use cases and key patterns of data virtualization
• What to expect in the upcoming sessions in the Packed Lunch Webinar Series, which will take a deeper dive into various challenges solved by data virtualization in big data analytics, cloud migration and various other scenarios
Agenda:
• Introduction & benefits of DV
• Summary & next steps
• Q&A
This presentation explains the Integrator's Dilemma and and how the SnapLogic Integration Cloud can help.
To learn more, visit: http://www.snaplogic.com/.
Denodo Data Virtualization Platform: Security (session 5 from Architect to Ar...Denodo
Everyone wants to keep their data safe from prying eyes (or even worse). The Denodo Platform has comprehensive security mechanisms to protect your data. This webinar will take a detailed look at how the Denodo Platform provides security.
Agenda:
Security Levels
Security capabilities
User and Role based Security
Security Protocols
Integration with External Security Systems
Ten Pillars of World Class Data VirtualizationDenodo
This presentation describes how to achieve a successful and mature enterprise data virtualization solution. You will learn the key attributes to look for in an enterprise DV platform, the journey to maturity from an implementation perspective and how a solution can impact your fast data-driven business outcomes.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/tHWXuO.
The RNC recently tackled a massive data migration that will help them scale tremendously to support national campaigns at every level of government. Convergence Consulting Group supported the RNC in migrating their data from legacy on prem. systems to a Microsoft Azure Cloud data warehouse. The RNC and its partners can now utilize Microsoft Power BI to expose the data from anywhere with a few simple clicks. See some examples of recent polling data in the presentation. Questions? Contact us at (813) 265-3239.
Sn wf12 amd fabric server (satheesh nanniyur) oct 12Satheesh Nanniyur
Big Data has influenced the data center architecture in ways unimagined before. This presentation explores the Fabric Compute and Storage architectures to enable extreme scale-out, low power, high density Big Data deployments
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
SnapLogic provides a Data Integration platform that takes integration to another level, by combining the power of dynamic programming languages with standard Web interfaces to solve today's most pressing problems in application integration. SnapLogic has an intuitive visual designer that runs in your browser and connects to highly scalable web based Integration server that you can run on premise or in the cloud.
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.
Getting Started with Data Virtualization – What problems DV solvesDenodo
Experts and analysts agree that data virtualization's strategic role in enterprise architecture for increasing agility and flexibility in the delivery of information. In this presentation, you will find how data virtualization enables organizations to access, manage, and integrate data from a wide variety of data sources.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/IS9RGK.
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
Introduction to Data Virtualization (session 1 from Packed Lunch Webinar Series)Denodo
This first session in a series of six ‘Packed Lunch’ webinars provides an overview of Data Virtualization technology, its applications and how it is adding business value to organizations around the world.
More information and FREE registrations to this webinar: http://goo.gl/z7mq2S
Landing page for the entire Packed Lunch webinar series: http://goo.gl/NATMHw
Attend & get unique insights into:
What Data Virtualization is and what sets it apart from traditional integration tools
How it both complements and leverages existing enterprise architectures
The Denodo Data Virtualization platform and its capabilities
Data Services and the Modern Data Ecosystem (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2YdstdU
Digital Transformation has changed IT the way information services are delivered. The pace of business engagement, the rise of Digital IT (formerly known as “Shadow IT), has also increased demands on IT, especially in the area of Data Management.
Data Services exploits widely adopted interoperability standards, providing a strong framework for information exchange but also has enabled growth of robust systems of engagement that can now exploit information that was normally locked away in some internal silo with Data Virtualization.
We will discuss how a business can easily support and manage a Data Service platform, providing a more flexible approach for information sharing supporting an ever-diverse community of consumers.
Watch this on-demand webinar as we cover:
- Why Data Services are a critical part of a modern data ecosystem
- How IT teams can manage Data Services and the increasing demand by businesses
- How Digital IT can benefit from Data Services and how this can support the need for rapid prototyping allowing businesses to experiment with data and fail fast where necessary
- How a good Data Virtualization platform can encourage a culture of Data amongst business consumers (internally and externally)
Cloud Modernization and Data as a Service OptionDenodo
Watch here: https://bit.ly/36tEThx
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. Dealing with bureaucracy, different languages and protocols, and the definition of ingestion pipelines to load that data into your data lake can be complex. 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 – one that is real-time, agile and doesn’t rely on physical data movement.
- Learn how logical data architecture can enable organizations to transition data faster to the cloud with zero downtime and ultimately deliver faster time to insight.
- Explore how data as a service and other API management capabilities is a must in a hybrid cloud environment.
Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)Denodo
Watch full webinar here: https://bit.ly/3dudL6u
It's not if you move to the cloud, but when. Most organisations are well underway with migrating applications and data to the cloud. In fact, most organisations - whether they realise it or not - have a multi-cloud strategy. Single, hybrid, or multi-cloud…the potential benefits are huge - flexibility, agility, cost savings, scaling on-demand, etc. However, the challenges can be just as large and daunting. A poorly managed migration to the cloud can leave users frustrated at their inability to get to the data that they need and IT scrambling to cobble together a solution.
In this session, we will look at the challenges facing data management teams as they migrate to cloud and multi-cloud architectures. We will show how the Denodo Platform can:
- Reduce the risk and minimise the disruption of migrating to the cloud.
- Make it easier and quicker for users to find the data that they need - wherever it is located.
- Provide a uniform security layer that spans hybrid and multi-cloud environments.
An Introduction to Data Virtualization in 2018Denodo
Watch full webinar on demand here: https://goo.gl/Rdrc1w
"Through 2020, 50% of enterprises will implement some form of data virtualization as one enterprise production option for data integration" according to Gartner. It is clear that data virtualization has become a driving force for companies to implement an agile, real-time and flexible enterprise data architecture.
Attend this session to learn:
• What data virtualization actually means and how it differs from traditional data integration approaches
• The all important use cases and key patterns of data virtualization
• What to expect in the upcoming sessions in the Packed Lunch Webinar Series, which will take a deeper dive into various challenges solved by data virtualization in big data analytics, cloud migration and various other scenarios
Agenda:
• Introduction & benefits of DV
• Summary & next steps
• Q&A
This presentation explains the Integrator's Dilemma and and how the SnapLogic Integration Cloud can help.
To learn more, visit: http://www.snaplogic.com/.
Denodo Data Virtualization Platform: Security (session 5 from Architect to Ar...Denodo
Everyone wants to keep their data safe from prying eyes (or even worse). The Denodo Platform has comprehensive security mechanisms to protect your data. This webinar will take a detailed look at how the Denodo Platform provides security.
Agenda:
Security Levels
Security capabilities
User and Role based Security
Security Protocols
Integration with External Security Systems
Ten Pillars of World Class Data VirtualizationDenodo
This presentation describes how to achieve a successful and mature enterprise data virtualization solution. You will learn the key attributes to look for in an enterprise DV platform, the journey to maturity from an implementation perspective and how a solution can impact your fast data-driven business outcomes.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/tHWXuO.
The RNC recently tackled a massive data migration that will help them scale tremendously to support national campaigns at every level of government. Convergence Consulting Group supported the RNC in migrating their data from legacy on prem. systems to a Microsoft Azure Cloud data warehouse. The RNC and its partners can now utilize Microsoft Power BI to expose the data from anywhere with a few simple clicks. See some examples of recent polling data in the presentation. Questions? Contact us at (813) 265-3239.
Sn wf12 amd fabric server (satheesh nanniyur) oct 12Satheesh Nanniyur
Big Data has influenced the data center architecture in ways unimagined before. This presentation explores the Fabric Compute and Storage architectures to enable extreme scale-out, low power, high density Big Data deployments
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
SnapLogic provides a Data Integration platform that takes integration to another level, by combining the power of dynamic programming languages with standard Web interfaces to solve today's most pressing problems in application integration. SnapLogic has an intuitive visual designer that runs in your browser and connects to highly scalable web based Integration server that you can run on premise or in the cloud.
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.
Getting Started with Data Virtualization – What problems DV solvesDenodo
Experts and analysts agree that data virtualization's strategic role in enterprise architecture for increasing agility and flexibility in the delivery of information. In this presentation, you will find how data virtualization enables organizations to access, manage, and integrate data from a wide variety of data sources.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/IS9RGK.
Denodo DataFest 2016: Enterprise View of Data with Semantic Data LayerDenodo
Watch the full session: Denodo DataFest 2016 sessions: https://goo.gl/kPmzWU
Gaining an enterprise view of the data across different independent lines of businesses is difficult when the operations, systems, and data are inherently siloed. VSP Global is a conglomerate operating different businesses across eyewear insurance, manufacturing, and retail. They are integrating the silos using a semantic data layer.
In this presentation, the Enterprise Data Architect at VSP Global, Tim Fredricks will present:
• The challenges associated with data siloed across different LOBs
• How to build a semantic data layer using data virtualization
• Centralizing business rules in the data virtualization layer
This session also includes a panel discussion with:
• Tim Fredricks, Enterprise Data Architect at VSP Global
• Rick Hart, Director of Global Technology Solutions at BioStorage Technologies
• Jeff Veis, VP Big Data Platform Marketing at HPE
• Mike Litzkow, Sales Director at Denodo (as moderator)
This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6
This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6
Tracxn Startup Research: Data as a Service Landscape, August 2016Tracxn
The top three funded sub-sectors till date are market intelligence (149 investments, $1.3B), financial data providers (158 investments, $1.2B), and geospatial data providers.
Big-Data-as-a-Service (BDaaS) in an enterprise environment requires meeting the often contradictory goals of (1) providing your data scientists, analysts, and data engineers with a self-service consumption model; (2) delivering agile and scalable on-demand infrastructure for the rapidly evolving ecosystem of big data frameworks and application software; while (3) ensuring enterprise-grade capabilities for isolation, security, monitoring, etc.
In this presentation at our BDaaS meetup in Santa Clara, Tom Phelan (chief architect and co-founder of BlueData) reviewed these goals and how to resolve the potential contradictions. He also discussed the infrastructure, application, user experience, security, and maintainability considerations required before selecting (or designing and building) a Big-Data-as-a-Service platform for an enterprise big data deployment.
More info on this BDaaS meetup can be found at: http://www.meetup.com/Big-Data-as-a-Service/events/233999817
The market is moving toward an As-a-Service delivery model that provides plug-in, scalable, consumption-based business services that deliver the business outcomes that every organization demands—increased revenue or decreased costs. Early movers are at a tremendous advantage, while large incumbents may be at risk if they do not aggressively pursue As-a-Service capabilities.
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
TUW- 184.742 Analyzing and Specifying Concerns for DaaSHong-Linh Truong
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
TUW - 184.742 Data marketplaces: models and conceptsHong-Linh Truong
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
Analytic Platforms in the Real World with 451Research and Calpont_July 2012Calpont Corporation
Matt Aslett, 451 Research, and Bob Wilkinson, VP Engineering for Calpont, discuss the emergence of the analytic platform, its place the new ecosystem for Big Data, considerations for selection, and applied use cases of Calpont’s analytic platform, InfiniDB, in Telco and Mobile Advertising.
Interoperability for Intelligence Applications using Data-Centric MiddlewareGerardo Pardo-Castellote
Presentation at the May 2012 Intelligence Workshop held in Rome Italy.
Interoperability is key to reducing cost in the development and maintenance of applications that span multiple providers or must be supported over long periods of time. This presentation describes the role of network middleware technologies in such systems and how the use of a data-centric middleware, such as OMG DDS, makes developing such systems easier and more cost-effective.
TUW- 184.742 Emerging Dynamic Distributed Systems and Challenges for Advanced...Hong-Linh Truong
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Use of the Data-Distribution Service (DDS) --a publish-subscribe middleware standard from OMG -- as a communication infrastructure for Event Processing Engines.
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
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
The Practice of Big Data - The Hadoop ecosystem explained with usage scenarioskcmallu
What's the origin of Big Data? What are the real life usage scenarios where Hadoop has been successfully adopted? How do you get started within your organizations?
Database Architechs is a database-focused consulting company for 17 years bringing you the most skilled and experienced data and database experts with a wide variety of service offering covering all database and data related aspects.
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016StampedeCon
This session will detail best practices for architecting, building, operating and managing an Analytics Data Lake platform. Key topics will include:
1) Defining next-generation Data Lake architectures. The defacto standard has been commodity DAS servers with HDFS, but there are now multiple solutions aimed at separating compute and storage, virtualizing or containerizing Hadoop applications, and utilizing Hadoop compatible or embedded HDFS filesystems. This portion will explore the options available, and the pros and cons of each.
2) Data Ingest. There are many ways to load data into a Data Lake, including standardized Apache tools (Sqoop, Flume, Kafka, Storm, Spark, NiFi), standard file and object protocols (SFTP, NFS, Rest, WebHDFS), and proprietary tools (eg, Zaloni Bedrock, DataTorrent). This section will explore these options in the context of best fit to workflows; it will also look at key gaps and challenges, particularly in the areas of data formats and integration with metadata/cataloging tools.
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TUW- 184.742 Data as a Service – Concepts, Design & Implementation, and Ecosystems
1. Advanced Services Engineering,
WS 2012
Data as a Service – Concepts, Design &
Implementation, and Ecosystems
Hong-Linh Truong
Distributed Systems Group,
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://www.infosys.tuwien.ac.at/staff/truong
ASE WS 2012 1
2. Outline
Data provisioning and data service units
Data-as-a-Service concepts
DaaS design and implementation
DaaS ecosystems
ASE WS 2012 2
3. Data versus data assets
Data
Data Assets
Data
collection,
assessment
and
enrichment
Data concerns
Data
management
and
provisioning
ASE WS 2012
3
4. Data provisioning activities and
issues
Collect Store Access Utilize
• Data sources • Query and • Interface • Alone or in
• Ownership backup • Public versus combination
• Quality capabilities private with other
assessment • Local versus access data sources
and cloud, • Access • Redistribution
enrichment distributed granularity
versus • Pricing and
centralized licensing
storage model
Non-exhausive list! Add your own issues!
ASE WS 2012 4
5. Stakeholders in data provisioning
Data Provider
• People
(individual/crowds/org
anization)
• Software, Things
Service Provider
Data Assessment • Software and people
• Software and
people
Data
Data Consumer
Data Aggregator/Integrator • People, Software,
• Software Things
• People + software
ASE WS 2012 5
6. Recall – Service Unit
Consumption,
ownership, Service
provisioning, price, etc. model
Service
unit
„basic
component“/“basic
function“ modeling Unit
Concept
and description
What about service units providing data?
ASE WS 2012 6
7. Data service unit
Service
model
Data
Data
service
unit
Unit
Concept
Can be used for private
or public
Can be elastic or not
ASE WS 2012 7
8. Data service units in clouds/internet
Provide data capabilities rather than provide
computation or software capabilities
Providing data in clouds/internet is an increasing
trend
In both business and e-science environments
Bio data, weather data, company balance
sheets, etc., via Web services
ASE WS 2012 8
9. Data service units in
clouds/internet
data data
data
Data service unit Data service unit Data service unit
data
People Things
Internet/Cloud
ASE WS 2012 9
10. Discussion time
SO DATA SERVICE UNIT IS
BIG OR SMALL? PROVIDING
REALTIME OR STATIC DATA?
ASE WS 2012 10
11. NIST Cloud definitions
“This cloud model promotes availability and is
composed of five essential characteristics,
three service models, and four deployment
models.”
Source: NIST Definition of Cloud Computing v15, http://csrc.nist.gov/groups/SNS/cloud-computing/cloud-def-v15.doc
ASE WS 2012 11
12. Data as a Service -- characteristics
Built atop NIST‘s definition
On-demand self-service
Capabilities to provision data at different granularities
Resource pooling
Multiple types of data, big, static or near-realtime,raw data and
high-level information
Broad network access
Can be access from anywhere
Rapid elasticity
Easy to add/remove data sources
Measured service
Measuring, monitoring and publishing data concerns and usage
ASE WS 2012 12
13. Data as a Service – service models
and deployment models
Data-as-a-Service – service models
Data publish/subcription Database-as-a-Service
middleware as a service (Structured/non-structured
querying systems)
Sensor-as-a-Service Storage-as-a-Service
(Basic storage functions)
deploy
Private/Public/Hybrid/Community Clouds
ASE WS 2012 13
15. Discussion time
WHAT ELSE DO YOU THINK
CAN BE INCLUDED INTO DAAS
MODELS?
ASE WS 2012 15
16. DaaS design & implementation –
APIs
Read-only DaaS versus CRUD DaaS APIs
Service APIs versus Data APIs
They are not the same wrt concerns
SOAP versus REST
Example: infochimps
ASE WS 2012 16
17. DaaS design & implementation –
service provider vs data provider
The DaaS provider is separated from the data
provider
Consumer DaaS provider Data
provider
DaaS
Consumer
DaaS
DaaS
Sensor
ASE WS 2012 17
19. DaaS design & implementation –
structures
Three levels
DaaS Data Data Items
Resource
• Service • Data APIs • Data APIs
APIs for for data
• Data APIs particular items
for the resources
whole • Data APIs
resource for data
items
DaaS and data providers have the right to
publish the data
ASE WS 2012 19
20. DaaS design & implementation –
structures (2)
Data resource
Data
items
Consumer
Data Data
Data items items
assets
Consumer
Data resource Data resource
Data resource Data resource
DaaS
ASE WS 2012 20
21. DaaS design & implementation –
patterns for „turning data to DaaS“ (1)
data Build Data Deploy DaaS
Service Data
APIs Service
Examples: using WSO2 data service
ASE WS 2012 21
22. DaaS design & implementation –
patterns for „turning data to DaaS“ (2)
Storage/Database
-as-a-Service
data DaaS
Examples: using
Amazon S3
ASE WS 2012 22
23. DaaS design & implementation –
patterns for „turning data to DaaS“ (3)
data
Storage/Databa
se/Middleware DaaS
Things
One thing 10000... things
Examples: using
COSM/Pachube
ASE WS 2012 23
24. DaaS design & implementation –
patterns for „turning data to DaaS“ (4)
data
Storage/Database/
Middleware DaaS
People
Examples: using Twitter
ASE WS 2012 24
25. DaaS design & implementation –
not just „functional“ aspects (1)
Profiling
Cleansing
Enrichment Integration ...
Data Assessment
/Improvement
data .... .... DaaS data assets
APIs, Querying, Data Management, etc.
Data
concerns
Quality of Ownership
data Price
License ....
ASE WS 2012 25
26. DaaS design & implementation –
not just „functional“ aspects (2)
Understand the DaaS ecosystem
Specifying, Evaluating and Provisioning Data
concerns and Data Contract
In follow-up
lectures
ASE WS 2012 26
27. Discussion time
WHAT ARE OTHER PATTERNS
IN „TURNING DATA TO
DAAS“?
ASE WS 2012 27
28. DaaS ecosystems
Data Assessment and Enrichment
Marco Comerio, Hong Linh Truong, Carlo Batini, Schahram Dustdar: Service-oriented data quality engineering and
data publishing in the cloud. SOCA 2010: 1-6
ASE WS 2012 28
29. Examples of service units in DaaS
ecosystems
Platforms/services Capabilities
Strikeiron clean, verify and validate data.
Jigsaw clean, verify and validate
business contact.
PostcodeAnywhere capture, clean, validate
and enrich business data.
Trillium Software Quality clean and standardize data
Uniserv Data Quality Solution X profile and clean data
Adeptia Integration Solution integrate data
Marco Comerio, Hong Linh Truong, Carlo Batini, Schahram Dustdar: Service-oriented data quality engineering and
data publishing in the cloud. SOCA 2010: 1-6
ASE WS 2012 29
30. DaaS ecosystem –
profiling/enriching example
http://www.strikeiron.com/
ASE WS 2012 30
31. Cloud-based conceptual architecture
for data quality and enrichment
Marco Comerio, Hong Linh Truong, Carlo Batini, Schahram Dustdar: Service-oriented data quality engineering and
data publishing in the cloud. SOCA 2010: 1-6
ASE WS 2012 31
32. Discussion time
WHY DO YOU NEED TO STUDY
DAAS CONCEPTS, DESIGN
AND IMPLEMENTATION, AND
ECOSYSTEMS?
ASE WS 2012 32
33. Exercises
Read mentioned papers
Check characteristics, service models and
deployment models of mentioned DaaS (and
find out more)
Identify services in the ecosystem of some DaaS
Write small programs to test public DaaS, such
as COSM/Pachube, Microsoft Azure and
Infochimps
Turn some data to DaaS using existing tools
ASE WS 2012 33
34. Thanks for
your attention
Hong-Linh Truong
Distributed Systems Group
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://www.infosys.tuwien.ac.at/staff/truong
ASE WS 2012 34