Case 8: Big Data, Big Rewards

1. 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. First, IBM Bigsheets help the British Library to handle with huge quantities of data and extract the useful knowledge. 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. Third, Vestas implemented a solution consisting of IBM InfoSphere BigInsights software running on a high-performance IBM System x iDataPlex server.

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.

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

There are mainly three reasons. First, Traditional data management methods proved inadequate to archive millions of these Web pages, and legacy analytics tools couldn’t extract useful knowledge from such quantities of data.

Secondly, Law enforcement agencies can become more proactive in its efforts to fight crime patterns since information of suspects can be visualized in seconds on a video wall instantly relayed to officers at a crime scene.

Third and Finally, Vestas relies on location based data to determine the best spots to install their turbines. If there is no data available, it is difficult to accurately place its turbines for optimal wind power generation.

What business benefits did they obtain?

1.      Sustainable Competitive advantages

2.      Improve quality and performance

3.      Maintain customer relationship with high level of satisfaction

4.      Gather more customers to generate more profit

5.      Improved decision making (faster & accurate)

6.      Excellence operational

7.      Reduced cost and time spent

4. Identify three decisions that were improved by using big data.

•       Analyze consumer sentiment. For example, car rental giant Hertz gathers data

•       Reduce cost and time

•       Quick and efficient decision making

1.      What kinds of organizations are most likely to need big data management and analytical tools? Why?

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.

Online Analytical Processing (OLAP)

Supports multidimensional data analysis, enabling users to view the same data in different ways using multiple dimensions.

Data mining provides insight into corporate data that cannot be obtained with OLAP by finding patterns and relationships in large databases and inferring rules from them to predict future behavior.

Associations: occurrences to a single event

Sequences: events over time

Classification: description of group to which something belongs

Clustering: grouping together, but no groups are defined.

Forecasting: find patterns

Text mining & Web mining tools used to extract key elements of unstructured data sets, discover patterns and relationships, and summarize the information.