Database Reference
In-Depth Information
scientists to quickly examine, explore, and discover data relationships. It
provides security and governance capabilities to ensure that sensitive data
is protected and secured. BigInsights is prepackaged with development
tooling that makes it easier for technical teams to create applications without
first having to go through exhaustive training to become Hadoop experts.
We will describe IBM's Hadoop distribution in Chapter 5.
3. Stream Computing: IBM InfoSphere Streams
Stream computing enables organizations to immediately respond to chang-
ing events, especially when analyzing stored data isn't fast enough. It also
enables them to be more efficient in prefiltering and selectively storing high-
velocity data. IBM InfoSphere Streams (Streams) delivers this capability by
enabling organizations to analyze streaming data in real time. Streams has a
modular design that has unlimited scalability and can process millions of
events per second. It has the ability to analyze many data types simultane-
ously and to perform complex calculations in real time. We will describe
Streams and analytics in motion in Chapter 6.
4. Data Warehouse Appliance: IBM PureData System
for Analytics Powered by Netezza Technology
We often find enterprises struggling with the complexity of their data ware-
housing environments. Their data warehouses tend to be glutted with data
and not suited for one particular task. Gaining deep analytical insights might be
too complex or expensive. IBM addresses this pain point through an anaytics-
based IBM PureData System. The IBM PureData System for Analytics (the
new name for the latest generation Netezza appliance) is a purpose-built
appliance for complex analytical workloads on large volumes of structured
data. It's designed with simplicity in mind and needs minimal administra-
tion and no performance tuning. It uses a unique hardware-assisted query
processing mechanism that enables users to run complex analytics at blister-
ing speeds. We talk about this technology in Chapter 4.
5. Analytic Accelerators
One of the objectives of IBM's platform-based approach is to reduce time to
value for Big Data projects. The IBM Big Data platform achieves this by pack-
aging prebuilt analytics, visualization, and industry-specific applications as
part of the platform. The analytic accelerators contain a library of pre-built
