The document discusses how various organizations are leveraging big data to drive operational efficiency and gain competitive advantages. It describes how the British Library uses IBM BigSheets to analyze vast amounts of unstructured web data, and how law enforcement agencies analyze big data to discover hidden patterns in criminal activity. Vestas uses location-based data analyzed with IBM InfoSphere BigInsights to determine optimal wind turbine placement. Hertz analyzes consumer sentiment data to reduce processing time and improve customer response. Overall, the document explains how maintaining and analyzing big data can provide benefits like enhanced decision making, reduced costs, increased satisfaction, and competitive edges.

1. G S T 5 0 8 3
INFORMATION SYSTEMS & ELECTRONIC COMMERCE
Group Members
BIG DATA, BIG REWARDS

2. Company Background
• Big data datasets that are too large to be gathered, stored, managed and
analyzed by typical database software tools – can generate plenty of value for
organizations of all sizes and types.
• Organizations that are able to harness the power of big data can drive both
operational efficiency and quality, leading to cost and labor savings and a
competitive edge.
• Leveraging big data can also help companies streamline processes, fighting fraud
and reducing errors.

3. Question 1 :
Describe the kinds of big data collected by the organizations described in this
case.
There are mainly four kinds of big data collected by the organizations described in
this case. :-
1. First, IBM Big sheets help the British Library to handle with huge quantities of
data and extract the useful knowledge British Library responsible for
preserving British Web sites that no longer exist but need to be preserved for
historical purpose. IBM BigSheets helps the British Library to process large
amounts of data quickly and efficiently
2. Second, 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. 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. 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.

4. CONT’S
3.Third, Vestas implemented a solution consisting of IBM InfoSphere BigInsights
software running on a high-performance IBM System x iDataPlex server. Vesta’s
wind library currently stores data on perspective turbine location and global
weather system. Vestas implemented a solution consisting of IBM InfoSphere
BigInsights software running on a high-performance IBM System x iDataPlex
server.
4.Forth, Hertz A car rental Hetrz using big data solution to analyze consumer
sentiment from Web surveys, emails, text message, Web site traffic patterns and
data generated at all of Hertz’s 8300 locations in 146 countries. Hertz was able to
reducing time spent processing data and improving company response time to
customer feedback and changes in sentiment.

5. Question 2 :
List and describe the business intelligence technologies described in this case.
• 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.
• 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.
• The Real Time Crime Center data warehouse contains millions of data points on city
crime and criminals.
• Vestas relies on location-based data to determine the best spots to install their
turbines.
• It implemented a solution consisting of IBM InfoSphere BigInsights software
running on a high-performance IBM System x iDataPlex server.

6. Question 3 :
Why did the companies described in this case need to maintain and analyse ?
What business benefits did they obtain?
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.
New York Police Department (NYPD)
NYPD need to maintain and analyze big data because:
Allow the NYPD quickly respond on the criminals occurred.
Help NYPD to obtain sources of the suspects, such as suspect’s photo, past offences
or addresses with maps, can be visualized in seconds on a video wall.

7. Vestas
Vestas need to maintain and analyze big data because :
• Vestas is the world’s largest wind energy company.
• Location data are important to Vestas so that can accurately place its turbines.
• Areas without enough wind will not generate the necessary power.
• Area with too much wind may damage the turbines.
• Therefore, Vesta relies on location-based data to determine the best spots to
install their turbines.
• Vesta’s Wind Library currently stores 2.8 petabytes od data.
CONT’S

8. Hertz
Car rental giant Hertz need to maintain and analyze big data because :
• Reducing time spent processing data.
• Improving company response time to customer feedback.
• Hertz was able to determine that delays were occurring for returns in
Philadelphia during specific time of the day.
• Enhanced Hertz’s performance and increased customer satisfaction.
CONT’S

9. 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 customers and generate more revenue
5.Improved decision making (faster & accurate)
6.Excellence operational
7.Reduced cost and time spent
CONT’S

10. Question 4 :
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 makes 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.

11. Question 5:
What kinds of organizations are most likely to need big data management
and analytical tools? Why?
• 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.
• 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.
• Organization to go green need the big data about the weather and location
because the weather and location data are very useful for the companies to
accurately make a decision.
• In this case, Vestas needed the data about location and wind to locate their
turbines

12. THANK YOU