GROUP 1 : DATO’ NABIL ABD KADIR SAYNUL ISLAM MOHAMMAD GHAZALI MOHD DAUD

BIG DATA, BIG REWARDS

In 2012, the amount of digital information is expected to reach 988 exa bytes Big Data refers to the massive amounts of data that collect over time that are difficult to analyze and handle using common database management tools. Big Data includes business transactions, , messages, photos, surveillance videos and activity logs. Scientific data from sensors can reach mammoth proportions over time, and Big Data also includes unstructured text posted on the Web, such as blogs and social media.

Historical data – British Library Responsible for preserving British Websites that no longer exist but need to be preserving for historical purposes. Eg : Website for past politicians IBM BigSheets helps the British Library to process large amounts of data quickly and efficiently

City Crime & Criminals Data - NYPD Real Time Crime Centre in New York City data warehouse collected 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 onover 120 million criminal complaints, 31 million criminal crime records and 33 billion public records.

Turbine Locations and Wind Data - Vestas Vesta’s wind library currently stores data on perspective turbine location and global weather system. Vesta implemented IBM Info Sphere Biglnsight software running on a high perfomance IBM System xiData Plex server.

Consumer Sentiment Data - Hertz A car rental Hertz using Big Data solution to analyze consumer sentiment from Web surveys, s, text messages, Website traffic patterns and data generated at all of Hertz’s 8,300 locations on 146 countries. Hertz was able to reduce time spent processing data and improve response time to customer feedback and changes in sentiment.

IBM BigSheets  IBM BigSheets is a cloud application used to perform ad hoc analytics at web-scale on unstructured and structured content.  IBM BigSheets 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.  IBM BigSheets built stop the Hadoop framework so it can process large amounts of data quickly and efficiency.

Real Time Crime Centre (RTCC)  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 instantly relayed to officers at a crime scene.

IBM InfoSphere BigInsights  IBM InfoSphere BigInsights brings the power of Hadoop to the enterprise. Apache TM Hadoop® is the open source software framework used to reliably managing large volumes of structured and unstructured data.  Vestas increased the size of 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.

The British Library  They 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 criminal occurred. -Help NYPD to obtain sources of the suspects such as suspects photo, past offences or addresses with maps which can be visualized in seconds on a video wall.

Vestas  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.  Areas 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.

HERTZ  Car rental giant Hertz need to maintain and analyze 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 Phildelphia during specific time of the day -Enhanced Hertz’s performance and increased customer satisfaction.

The business benefits for maintaining and analyzing data are as follows:  Performance enhancement  Increase customer satisfaction  Attract more customers and generate more revenue  Improved decision making faster and accurate  Excellence operation  Reduced cost and time spent  Competitive advantage

1.Optimal Uses Of Resources and Operational Time Companies can optimal uses their resources to enhance performance. Vestas can forecast optimal turbine placement in 15 minutes instead of there 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. Visitors of The British Library and NYPC can quickly and effectively searches data from the British Library Web sited. NYPD can make a faster decision to gather the suspects 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.

 Organizations which responsible to score that 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 need the big data to predict the weather and location data, very useful for the companies to accurately make decision. Thus Vestas needed the data about location and wind to locate their turbines.