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Data as a Service (DaaS)
In Cloud Computing
Presented by,
Devyani B.Vaidya
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
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
Components Of Cloud
Computing
 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.
 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.
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
 DaaS is other offering service from
Cloud providers to its client to use
provider's 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
provider's database cloud.
The sites that provides data as a
service
 Google
 Windows Azure
 Amazon
DAAS Architecture
 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.
 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.
DaaS: Pricing Model
1. Volume-based Model
a. Quantity-based pricing and
b. Pay per call
2. Data type-based Model
Traditional Approach Vs.
DaaS
Data As Goods Data As Service
Bulk onetime download Dynamic access
Dated with the time of download Always latest update
Need for storage Storage is provided
Complex access when a large
amount of data
Easy and simple access and views
Benefits
 Agility
 Cost-effectiveness
 Data quality
 Faster/ Easy access
 Larger storage
 Large number of users
 Scalability/ Flexibility
 Reliability
 Maintenance
Drawbacks
 Reliance of the customer on the
service provider's ability to avoid
server downtime
 Generally data is not available for
download
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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Data As A Service

  • 1. Data as a Service (DaaS) In Cloud Computing Presented by, Devyani B.Vaidya
  • 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. 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. Components Of Cloud Computing  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.  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. 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.  DaaS is other offering service from Cloud providers to its client to use provider's 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 provider's database cloud.
  • 8. The sites that provides data as a service  Google  Windows Azure  Amazon
  • 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.  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. DaaS: Pricing Model 1. Volume-based Model a. Quantity-based pricing and b. Pay per call 2. Data type-based Model
  • 13. Traditional Approach Vs. DaaS Data As Goods Data As Service Bulk onetime download Dynamic access Dated with the time of download Always latest update Need for storage Storage is provided Complex access when a large amount of data Easy and simple access and views
  • 14. Benefits  Agility  Cost-effectiveness  Data quality  Faster/ Easy access  Larger storage  Large number of users  Scalability/ Flexibility  Reliability  Maintenance
  • 15. Drawbacks  Reliance of the customer on the service provider's ability to avoid server downtime  Generally data is not available for download
  • 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