slides - Spatial Database Group

Report
The Netezza Data Appliance: A
Platform for High Performance Data
Warehousing
Based on - Too many cooks spoil the data warehouse broth Cut your
staffing costs By Eira Hayward
(http://www.theregister.co.uk/2011/11/16/data_warehouse_staffing)
By Group 19:Yuefeng Hou, Ankit Kinra
Costs of Data Warehousing
Hardware, software, and administration
 Hidden Costs: business units outside the
IT organization
 Getting data in and out, not productive,
keep the surrounding business intelligence
environment going

Challenges of Data Warehousing
Analyzing billions of data points and
petabytes of data through a sea of
ambiguity
 A huge amount of cost
 Inefficient use of manpower
 Preventing analysts from trying new things
 Waste opportunity, cost time and
resources, and put the company at risk

Netezza Data Warehouse and
Analytics Appliance
Highly flexible and robust warehouse
 Merges the traditional big data
approaches, coping with both structured
and unstructured data
 Simplifies the database environment
 Resource can be used in a more
productive manner
 Implementation and ownership costs are
much lower

Netezza Data Warehouse and
Analytics Appliance
A technology foundation able to sustain
performance as more users run
increasingly complex workloads and as
data volumes continue to grow
 Simple, reliable, and immediate
 Able to handle almost incomprehensible
workloads without complexity getting in
the way

Netezza Architecture Principles
Processing close to data source
 Platform for advanced analytics
 Appliance Simplicity
 Flexible configurations and extreme
scalability.

Integration Example for Netezza
A typical monthly task takes about two
weeks involves running financial
prediction models on millions of
customers when performed manually.
 Creation of C/C++ task reduces the time
on parallel Netezza architecture.
 Reduces time but increases debugging and
setting up time.
 Solution?

Integration Example for Netezza
(Cont.)
SAS Suite operations inside Netezza.
 Scoring accelerator removes manual
coding and has benefits of scalability and
high performance.
 Loading of data can be handled via
partner application suite called Kalido
which has many Automated Load
Routines which simplify the loading tasks.

Relation with course
Data Warehouse in chapter 29
 OLAP in chapter 29

References

Netezza Blogs by Thomas Dinsmore (URL:
http://thinking.netezza.com/blog/netezza-and-sas-integration-best-practices)

The Netezza Data Appliance Architecture: A Platform for High Performance Data
Warehousing and Analytics by Phil Francisco (URL
http://www.netezza.com/documents/whitepapers/Netezza_Appliance_Architecture_
WP.pdf )

Too many cooks spoil the data warehouse broth Cut your staffing costs By Eira
Hayward (URL http://www.theregister.co.uk/2011/11/16/data_warehouse_staffing )

Much Ado about Loading by John Evans (http://blog.kalido.com/ado-loading/)
Questions
?

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