Databases Reference
In-Depth Information
false-positive rate. With these results, security staff can make confident decisions about responding
to a threat—such as how many officers to deploy and which tactics to use—and can also thwart any
plans intruders have to breach the property.
Finally, in addition to meeting the lab's requirements for extensibility, interoperability, and scal-
ability, the solution saves the lab costs associated with data storage because data does not have to be
stored before being analyzed. Dr. Philp states:
Capturing approximately 42 terabytes of data each day adds up fast and would be challenging and
costly to store. InfoSphere Streams offers advantages, especially when you have to capture data
continuously in real time and analyze it as it passes by. Organizations can realize huge savings in
storage. Given the data processing and analytical challenges addressed using our Adelos Sensor
Array, InfoSphere Streams is the right solution for us and our customers. We look forward to grow-
ing our strategic relationship with IBM across various sectors and markets to help revolutionize the
concept of “sensor as a service.”
Stream analytics will be a mandate for working with data on the wire. This case study shows the
overall approach that was designed for solving the problem at TerraEchos. Similar techniques can be
used for financial services—credit card fraud, trading floor systems, and retail banking—where the
data processing before a fraud or illegal situation arises is of the highest priority.
Case study 3: The right prescription: improving patient outcomes
with Big Data analytics
This case study is on managing patients proactively and increasing quality of healthcare, while reduc-
ing risk for both the patient and the provider. This is a case study from Teradata-Aster on the Big
Data platform. The author would like to thank them for sharing this interesting case study.
Summary
Aurora Health Care had a major initiative to improve the patient care outcome by using predictive
analytics from all the data available in the organization.
Business objective
The objective is to increase the effectiveness of treatment and contain costs by identifying and match-
ing predictive health patterns.
Challenges
●
Improve the quality of patient care by integrating patient records for a more comprehensive view
of the patient's overall health.
●
No data warehouse infrastructure.
●
Slow queries.
●
No reporting infrastructure.
●
Gigabytes of clickstream data in flat files.
