Implementing enterprise asset management solutions
Single Database for Spatial and Attribute Data
Database server technology enables spatial information to be efficiently stored, accessed,
managed and manipulated in the same manner as structured data. By effectively
managing spatial and attribute data in one physical database, server techology reduces
processing overhead and eliminates the complexity of coordinating and synchronizing
disparate sets of data.
The seamless information framework results in lower training fees, improved learning
curves, fewer design and programming iterations, and more efficient data administration.
Users can define and manipulate spatial data through SQL and gain access to standard
database features, such as a flexible n-tier architecture, object capabilities, Java virtual
machine, and robust data management utilities, ensuring data integrity, recovery, and
security features.
Centralizing Complexity
Regulatory mandates and public service activities impose unique challenges to public
institutions. Responding to citizen requests, designing network facilities, and managing
customer records all require utility departments to cooperate and exchange data. In the
past, client server architectures empowered departmental computing needs at the cost of
corporate-wide information requirements. The result was the distribution of complexity,
imposing unsustainable IT management burdens on local departmental IT personnel
(Figure 2). With today's technology, this information management can now be
centralized. Information resources can be managed centrally by small group of experts
while enabling users to view and edit information using a simple Web browser. Since
public departments maintain different types of location-based information (street
addresses, network assets, customer addresses, parcel numbers, road network, public
assets) they will all benefit from the increased ability to standardize and share this
information.
Figure 2: Centralizing Complexity
Figure 3: Centralizing Complexity
At all tiers of an IT architecture (data server, middle tier, client), spatial tools and
applications can be packaged as components plugging into any tier. For example, in the
Figure 3 above, a third party spatial tool and geocoder are embedded into the server. The
map rendering component is embedded into the middle-tier, using the application server
to push out compressed raster or live vector rendering operations to a thin client. The thin
client (web browser) invokes processes that are intelligently carried at the middle and
server tiers - increasing performance, optimizing processing, and minimizing the amount
of data transmitted along a network. This n-tier architecture builds on SQL, CORBA,
XML, and Java - all open standards redefining the new paradigm for enterprise
computing.
Conclusion
Storing spatial data in an enterprise-class server enables utilities to leverage advanced
database features like: parallel query, replication, partitioning, security, scalability, none
of which are supported in file-based or hybrid middle-ware systems. Spatial data can be
managed, queried, and displayed using SQL from any enterprise application like
financial, data warehouse, supply chain, CRM, and industry standard reporting tools.
Finally, centralizing management reduces the overhead of managing different systems,
eliminates training on different applications, and minimizes application integration costs.
Developers can leverage the spatial data to deploy Java components at the server tier for
unprecedented performance in a wide variety of utility applications.
