Big data is being generated from everything around us constantly through digital processes, social media, systems, sensors, and mobile devices. It is arriving at an alarming velocity, volume, and variety. Businesses can extract meaningful value from big data by using optimal processing power, analytics capabilities, and skills to react faster to problems, satisfy customers, and change work processes. Managers can detect emerging issues, pinpoint troubled areas, discover patterns and relationships in the data, and summarize information more quickly and easily to save time and money. The British Library and Vestas use Hadoop to efficiently process large amounts of data. Hertz uses sentiment analysis to determine customer satisfaction, while law enforcement agencies use web mining and analytics to predict future crime patterns.

1. BigData,BigRewards

2. Chong Min Fatt P13D154P
Group Member Name:
Haji Nasseruddin Bin HJ Abdul Jabar P13D142P
Haji Zulkifflee Bin HJ Sofee P13D136P
GST5083

3. What is Big Data?
Big data is being generated by everything around us at all
times. Every digital process and social media exchange
produces it. Systems, sensors and mobile devices transmit
it. Big data is arriving from multiple sources at an
alarming velocity, volume and variety. To extract
meaningful value from big data, you need optimal
processing power, analytics capabilities and skills.

5. Data Volume Trend

6. 1.Describe the kinds of
“big data” collected by
the organizations
described in this case.

7. British Library: It collects data from typical library resources like books, periodicals,
and newspapers. In addition, it must store and collect data from Web sites that no
longer exist but must be preserved for historical purposes. Data from over 6 billion
searches must also be stored.
Law enforcement agencies: Collect data on criminal complaints, national crime
records, and public records.
Vestas Wind Energy: Collects data from 43,000 turbines in 66 countries; collects
location-based data to help determine the best location for turbines; currently stores
2.8 petabytes of data and includes approximately 178 parameters, such as
barometric pressure, humidity, wind direction, temperature, wind velocity, and other
company historical data; plans to add global deforestation metrics, satellite images,
geospatial data, and data on phases of the moon and tides.
Hertz: Gathers data from Web surveys, emails, text messages, Web site traffic
patterns, and data generated at all of Hertz’s 8300 locations in 146 countries.

8. New text-mining software described in the case can shorten data
analysis to hours or minutes and produce better results. Businesses
can react faster to solve problems, satisfy customers, and change work
processes. Managers can detect emerging issues and pinpoint troubled
areas of the business at many different managerial levels. Managers
can discover patterns and relationships in the data and summarize the
information more quickly and more easily thereby saving time and
money.
The British Library and Vestas use Hadoop so it can process large
amounts of data quickly and efficiently. Hertz uses sentiment analysis
to determine customer satisfaction. Law enforcement agencies use
Web mining techniques to help determine potential criminal acts. They
also use analytics to predict future crime patterns.
2. List and describe the business intelligence
technologies described in this case.

10. The British Library is able to
maintain historical records of
events and provide users with
more information about its past.
It can now process information
requests more quickly and easily.
The technology it uses provides
an insight engine that helps
extract, annotate, ad visually
analyze vast amounts of
unstructured Web data, delivering
the results via a Web browser.
Criminals and criminal
organizations are increasingly
using the Internet to coordinate
and perpetrate their crimes. New
tools allow agencies to analyze
data from a wide array of sources
and apply analytics to predict
future crime patterns.
Vestas is able to collect more data
that can reduce the resolution of
its grid patterns from 17 x 17 miles
to 32 x 32 feet to establish exact
wind flow patterns at particular
locations. That further increases
the accuracy of its turbine
placement models.
Hertz stores all of its data centrally
instead of within each branch,
reducing time spent processing
data and improving company
response time to customer
feedback and changes in
sentiment.

12. Vestas used its big data to help find the best places to install its
wind turbines. It is able to manage and analyze location and
weather data with models that are much more powerful and
precise. The new technology enables the company to forecast
optimal turbine placement in 15 minutes instead of three weeks,
saving a month of development time for a turbine site and
enabling customers to achieve a return on investment much more
quickly.
Hertz used it data analysis generated from different sources
to determine the cause of delays at its Philadelphia locations
and adjusted staffing levels during peak times and ensuring
a manager was present to resolve any issues.
Law enforcement agencies use their data analysis to predict
future crime patterns and become more proactive in its
efforts to fight crime and stop it before it occurs.

13. 5. What kinds of
organizations
are most likely
to need “big
data”
management
and analytical
tools? Why?
Organizations that have an active
presence on the Web or on social
media sites need to use big data
management and analytical tools
to process the numerous
unstructured data that can help
them make better, more timely
decisions. Businesses that
generate big data from
manufacturing, retailing, and
customer service need the tools
that the technology can provide.

15. ThankYou
Data Information Knowledge