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Data as a service

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Refer google/publicdata for the real time execution.

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Data as a service

  1. 1. Data as a Service (DaaS)In Cloud Computing Presented by, Khushbu M. Joshi
  2. 2. Agenda Introduction Components Of Cloud Computing Data as a Service (DaaS) DaaS Architecture DaaS: Pricing Model Traditional Approach Vs. DaaS Benefits Drawbacks Demonstration of how google provides DaaS References
  3. 3. Introduction Cloud Services ◦ Consumer and business products, services and solutions that are delivered and consumed in real-time over the internet Cloud Computing ◦ Delivery of computing as a service rather than product. ◦ An emerging IT development, deployment and delivery model that enables real-time delivery of broad range of IT products, services and solutions over the internet
  4. 4. Components Of CloudComputing IaaS (Infrastructure as a Service) ◦ Consumers control and manage the systems in terms of the operating systems, applications, storage, and network connectivity, but do not themselves control the cloud infrastructure.
  5. 5.  PaaS (Platform as a Service) ◦ Consumers purchase access to the platforms, enabling them to deploy their own software and applications in the cloud. SaaS (Software as a Service) ◦ Consumers purchase the ability to access and use an application or service that is hosted in the cloud.
  6. 6. Data as a Service A service provider that enables data access on demand to users regardless of their geographic location. Similar to SaaS Information is stored in the cloud and is accessible by a wide range of systems and devices Two ways to use data-as-a-service: ◦ by outsourcing your own data or ◦ taking advantage of public data managed by a third party
  7. 7.  DaaS is other offering service from Cloud providers to its client to use providers database infrastructure on the basis of what they use. Instead of spending money on setting up of database environment on your premises, we can take the benefit of providers database cloud.
  8. 8. The sites that provides data as aservice Google Windows Azure Amazon
  9. 9. DAAS Architecture
  10. 10.  Gather: ◦ Includes retrieving and organizing data input files of different formats. Process: ◦ Shapes the data through normalizing and prepares specialized views of the data. Publish: ◦ Uses maps to extract data from the RDBMS into a variety of formats that are consumed by the end users.
  11. 11.  Pervasive Data Integrator: ◦ is a graphical alternative to shell or Python scripting that provides logging and configuration services to Map Designer. ◦ Used in typical loading and transforming process ◦ Prvesive’s map designer creates code of map ◦ Stored procedures are invoked by Pervasive Process Designer.
  12. 12. DaaS: Pricing Model1. Volume-based Model a. Quantity-based pricing and b. Pay per call2. Data type-based Model
  13. 13. Traditional Approach Vs.DaaS Data As Goods Data As ServiceBulk onetime download Dynamic accessDated with the time of download Always latest updateNeed for storage Storage is providedComplex access when a large Easy and simple access and viewsamount of data
  14. 14. Benefits Agility Cost-effectiveness Data quality Faster/ Easy access Larger storage Large number of users Scalability/ Flexibility Reliability Maintenance
  15. 15. Drawbacks Reliance of the customer on the service providers ability to avoid server downtime Generally data is not available for download
  16. 16. References www.google.com/publicdata www.wikipedia.com http://bekwam.blogspot.com/2010/12/ building-data-as-service- architecture.html http://snipplr.com/ http://pixlr.com/editor/ http://cssdesk.com/ http://www.squidoo.com/guide-to- cloud-computing

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