Big Data, Big Rew

ards

Chong Min Fatt P13D154P

Group Member Name:

Haji Nasseruddin Bin HJ Abdul Jabar P13D142P

Haji Zulkifflee Bin HJ Sofee P13D136PGST5083

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.

Data Volume Trend

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

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.

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.

3.Why did the companies described in this case need to maintain and analyze big data? What business benefits did they obtain?

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.

4. Identify three decisions that

were improved by using “big data.”

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.

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.

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Data Information Knowledge