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Archive for March, 2014

 

Using Big Data to Identify and Prevent Crimes

Thursday, March 27th, 2014 by

Predictive analytics tools have helped major corporations gain consumer insights, using them to drive profit growth and marketing campaigns. On the other end of the spectrum, law enforcement agencies on the national and municipal levels are using Big Data to identify and predict criminal behavior. Surveillance capabilities aside, the new techniques may discourage so-called “bad behavior” throughout the United States.

A Neighborhood Watch sign in a community.

A Neighborhood Watch sign in a community.

An example of success 
The Wisconsin State Journal reported that Madison, Wisc., police authorities consulted with analysts in the surrounding areas in anticipating a December crime wave that would sweep the University of Wisconsin’s College Court area. Apparently, once students leave for winter break in December, law enforcement officials receive numerous burglary reports.

The news source noted that three crime analysts are employed by the Madison Police Department. Operating through a cloud server, the professionals are able to help officers prioritize their efforts. The unit has been with the organization for nearly 10 years, garnering headline-worthy attention when one analyst helped a detective identify patterns in a string of bank robberies that occurred earlier this year.

Caleb Kelbig, one of the data experts working with the authorities, told police in Madison and surrounding cities that the perpetrator could hit 1 of 11 possible targets on the afternoon of March 5 or 6. Amazingly, the robber appeared at one of the locations in Middleton, Wisc., at about 2:30 pm on March 5.

Prioritizing intentions, citing appropriate uses
Jignesh Patel, an expert in Big Data use and a professor at UW-Madison, noted that cloud computing has made predictive analytics tools easier to use. Developments in IT have also opened up new avenues through which digital information can be collected. For example, smartphone software has contributed significantly to the data-gathering trend.

(more…) «Using Big Data to Identify and Prevent Crimes»

What do P-Diddy & NoSQL have in common?

Thursday, March 20th, 2014 by

Ad networks are hungry to solve for the real-time information needed to support bidding and ad serving, but the solution to their challenges isn’t coming from Oracle. The solution is coming from the “bad boy” of the database world, NoSQL. NoSQL offers the low latency, scalability, and multi-data-center replication perfect for feeding the Big Data appetite of digital advertising. With so many potential use cases, GoGrid is gathering a panel of NoSQL leaders to discuss the future of their technologies and how they envision NoSQL becoming mainstream. Inspired by the original “bad boy,” Sean “P-Diddy” Combs, this meetup coincides with the first night of ad:tech San Francisco 2014.

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For IT professionals, there isn’t a better opportunity to learn about Cassandra, Couchbase, Riak, MongoDB, and MemSQL than hearing from the exciting minds responsible for the development of the technology itself. Come by 111 Minna in San Francisco on Wednesday, March 26, to engage in a panel discussion with the leaders of Basho, Couchbase, DataStax, MemSQL, and GoGrid on how you can leverage their solutions to create real value and solve the complex use cases in your business. And be sure to grab a drink at the open bar and some great food while you’re at it! Attendance is free, but registration is required. Here are the details:

March 26, 2014
5:30 – 7:30 pm
111 Minna Gallery
111 Minna Street
San Francisco, CA 94105
1-415-974-1719

Space is limited, so register today.