This document discusses Data as a Service (DaaS) in cloud computing. It defines DaaS and explains that it allows users to access data stored in the cloud from any location. The document outlines the components, architecture, pricing models, benefits and drawbacks of DaaS. It provides examples of companies that offer DaaS like Google, Windows Azure, and Amazon.

1. Data as a Service (DaaS)
In Cloud Computing
Presented by,
Khushbu M.
Joshi

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

9. DAAS Architecture

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 Easy and simple access and views
amount of data

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