2. Integrated Data Services
Data services are created to integrate as well as to
service-enable a collection of data sources.
The underlying sources are often heterogeneous in
Consumers of a data service see what appears to be
one coherent, service enabled data source rather than
being faced with a hodgepodge of disparate schemas
and data access APIs.
3. Integrated Data Services Cont..
4. Integrated Data Services Cont..
5. Integrated Data Services Cont..
Uses Xquery in a graphical user interface to integrate
and generate result data in an optimized manner:
for $cust in ics:getAllCustomers( )
where $cust/State = ’Rhode Island’
Supports read, create, update, and delete methods for
operating on data instances.
Also supports relationship methods to navigate from one
object instance (for example, a customer) to related
object instances (for example, complaints)
Method’s visibility can be designated as being one of
accessible by outside applications, usable only from
within other data services, or private to one particular
6. Cloud Data Services
Cloud Data Services is a universal platform for
data storage and management
Benefits of Cloud Data Services:
9. Cloud Data Models contd..
Key-value stores :The simplest kind of data storage
services is key-value stores that offer atomic CRUD
operations for manipulating serialized data structures
(objects, files) that are
identifiable by a key.
Examples present in market are:
10. Cloud Data Models contd..
Sparse tables: Storage management services for
structured and semi-structured data.
A sparse table is a collection of data records, each one
having a row and a set of column identifiers, so that at
the logical level records behave like the rows of a table.
Example of Sparse Tables:
11. Cloud Data Models contd..
RDBMSs: Users can install an entire database system in
the cloud. However, there is also a push toward
providing a database management system itself as a
service. In that case, administrative tasks such as
installing and updating DBMS software and performing
backups are delegated to the cloud service provider.
Example of Sparse Tables:
o Amazon RDS
12. Advance Technical Issue
Data service updates and transactions
Must have transactional properties
Data services that integrate data from multiple sources
face additional challenges
Another challenge, faced both by singlesource and multisource data services, is the
mapping of updates made to the external
model to correspondingly required updates to
the underlying data source.
13. Advance Technical Issue
Data consistency in the cloud
Data services security
14. Emerging Trends
Query formulation tools.
Data service query optimization
Cloud data service security