Q1: Describe the
kinds of big data collected by the organizations described in this case.
There
are mainly three kinds of big data collected by the organizations described in
this case.
1. British Library
o IBM
Bigsheets help the British Library to handle with huge quantities of data and
extract the useful knowledge.
o British
Library responsible for preserving British Web sites that no longer exist but
need to be preserved for historical purpose. Example, Web sites for past
politicians.
o IBM
BigSheets helps the British Library to process large amounts of data quickly
and efficiently.
2. New York City Police Department (NYPD)
o City
Crime and Criminal Data
o State
and federal law enforcement agencies are analyzing big data to discover hidden
patterns in criminal activity. The Real Time Crime Center data warehouse
contains millions of data points on city crime and criminals.
o IBM
and New York City Police Department (NYPD) work together to create the warehouse,
which contains data on over 120 million criminal complaints, 31 million
criminal crime records and 33 billion public records.
3. Vestas
o Turbine
Location and wind data for organizations to go green.
o Vesta’s
wind library currently stores data on perspective turbine location and global
weather system.
o Vestas
implemented a solution consisting of IBM InfoSphere BigInsights software
running on a high-performance IBM System x iDataPlex server.
Q2: List and describe the business intelligence
technologies described in this case.
1. IBM BigSheets
IBM
BigSheets is a cloud application used to perform ad hoc analytical at web scale
on unstructured and structured content. IBM Bigsheets is an insight engine that
helps extract, annotate, and visually analyze vast amounts of unstructured Web
data, delivering the results via a Web browser. For example, users can see
search results in a pie chart. State and federal law enforcement agencies are
analyzing big data to discover hidden patterns in criminal activity such as
correlations between time, opportunity, and organizations, or non-obvious
relationships between individuals and criminal organizations that would be
difficult to uncover in smaller data sets. IBM BigSheets built atop the Hadoop
framework, so it can process large amounts of data quickly and efficiency.
2. Real Time Crime Center (RTTC)
The
Real Time Crime Center (RTCC) is a centralized technology center for the New
York (NYPD) and Houston Police Departments. RTCC data warehouse contains
millions of data points on city crime and criminals and billions of public
records. The systems search capabilities allow the NYPD to quickly obtain data
from any of these data sources. Information on criminals. Such as suspect’s
photo with details of past offences or addresses with maps, can be visualized
in seconds on a video wall or install relayed to officers at a crime scene.
3. IBM InfoSphere BigInsights
IBM
InfoSphere BigInsights brings the power of Hadoop to the enterprise. Apache
Hadoop is the open source software framework, used to reliably managing large
volumes of structured and unstructured data. Vestas increased the size of its
wind library and is able manage and analyze location and weather data with
models that are much more powerful and precise. It implemented a solution
consisting of IBM InfoSphere BigInsights software running on a high-performance
IBM System x iDataPlex server.
Q3: Why did the
companies described in this case need to maintain and analyze? What business
benefits did they obtain?
1. The British
Library
The
British Library needed to maintain and analyze big data because Traditional
data management methods proved inadequate to archive billions of Web pages and
legacy analytics tools couldn’t extract useful knowledge from such quantities
of data.
2. New York Police Department (NYPD)
NYPD
need to maintain and analyze big data because:
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3. Vestas
Vestas
need to maintain and analyze big data because :
o Vestas
is the world’s largest wind energy company.
o Location
data are important to Vestas so that can accurately place its turbines.
o Areas
without enough wind will not generate the necessary power.
o Area
with too much wind may damage the turbines.
o Therefore,
Vesta relies on location-based data to determine the best spots to install
their turbines.
o Vesta’s
Wind Library currently stores 2.8 petabytes od data.
What business benefits did they obtain?
The
business benefits for maintaining and analyzing big data are as follows:
1. Competitive
advantages
2. Performance
Enhancement
3. Increase customer
satisfaction
4. Attract more
customer and generate more revenue
5. Improved
decision making (faster & accurate)
6. Excellence
operational
7. Reduced cost
and time spent
Q4: Identify three
decisions that were improved by using big data.
1. Optimal uses
of resources and operational time
By
using the big data, the companies can optimal uses of their resources to
enhance performance. Vestas can forecast optimal turbine placement in 15
minutes instead of three weeks, saving a months of development time for turbine
site.
2. Quick and effective decision making
Decision
making improves and can be quickly and effective by using big data. Visitor of
The British Library and NYPD can quickly and effective searches data from the
British Library Web sites. NYPD can make a faster decision to gather the
suspect’s detail by using The Real Time Crime Center.
3. Reduce
operational cost and other related cost
Company
quickly make the right decision and hence will eliminate wrong decision.
Example, Hertz was able quickly adjust staffing levels at its Philadelphia
office during those peak times, ensuring a manager was present to resolve any
issues.
Q5: What kinds of
organizations are most likely to need big data management and analytical tools?
Why?
1. Organizations
which responsible to store the huge information such as national library,
registration department, income tax and so on because these organizations
typically be a sources for government and the public.
2. Authorities
Organization such a police department, custom, immigration because they need to
store a big data about criminals and also public to use for safety of the
society.
3. Organization
to go green need the big data about the weather and location because the weath
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