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Once the data is collected from the users, it is persisted in data stores. BI processes then aggregate, filter, and scrub the user-generated data and present the collective intelligence data in the form of insight. A list of users that clicked a particular video provides little insight into the behavior of the system. However, presenting aggregated information like this video was viewed 100,000 times in the past day provides some insight that users of a system have provided you implicitly. Taking the video example further, you can then run more complex algorithms to find behavior correlations like users who viewed this video also viewed this one.

It can easily support thousands of transactions per second CICS was one of the first containers, a concept familiar to Spring and Java EE users, even though CICS itself debuted in 1969! A CICS installation is very expensive, and although IBM still sells and installs CICS, many other solutions have come along since then These solutions are usually specific to a particular environment: COBOL/CICS on mainframes, C on Unix, and, today, Java on any number of environments The problem is that there s very little standardized infrastructure for dealing with these types of batch processing solutions Very few people are even aware of what they re missing because there s very little native support on the Java platform for batch.

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After following these steps, the list page will be displayed using the newly created view. To see what views have been created for a list and to edit these views, select the List Settings command from the Settings group of the List Tools - List ribbon. The Views section at the bottom of the List Settings page will show you what views exist, which is the default, and in what folders of the list they are available.

processing. Businesses that need a solution typically end up writing it in-house, resulting in fragile, domain-specific code. The pieces are there, however: transaction support, fast I/O, schedulers such as Quartz, and solid threading support, as well as a very powerful concept of an application container in Java EE and Spring. It was only natural that Dave Syer and his team would come along and build Spring Batch, a batch processing solution for the Spring platform. It s important to think about the kinds of problems this framework solves before diving into the details. A technology is defined by its solution space. A typical Spring Batch application typically reads in a lot of data and then writes it back out in a modified form. Decisions about transactional barriers, input size, concurrency, and order of steps in processing are all dimensions of a typical integration. A common requirement is loading data from a comma-separated value (CSV) file, perhaps as a business-to-business (B2B) transaction, perhaps as an integration technique with an older legacy application. Another common application is nontrivial processing on records in a database. Perhaps the output is an update of the database record itself. An example might be resizing of images on the file system whose metadata is stored in a database or needing to trigger another process based on some condition.

Note The architecture of deriving collective intelligence from user-generated data is a complex topic that is not covered in this book. This book focuses on the BI of the client. If you are interested in additional information on this topic, please visit the accompanying web site of this book (www.silverlighbusinessintelligence.com).

Note Fixed-width data is a format of rows and cells, quite like a CSV file. CSV file cells are separated by commas or tabs however, and fixed-width data works by presuming certain lengths for each value. The first value might be the first nine characters, the second value the next four characters after that, and so on.

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