How Big data helps in customer insights and get the competitive edge.. from the Hadoop guys

From http://hortonworks.com/use-cases/

Integrating Hadoop into your data architecture can dramatically decrease the costs and improve the scale of data processing.
This in turn unlocks new opportunities to capture, refine and explore big data to extract insights that deliver new customer value,
competitive edge or business capabilities. Every business has unique big data though a lot of that data is similar in type.
If you are looking for the value of big data it is best to start at the root of it all…the types of big data found in Hadoop.

A)
Understand consumer sentiment with Social Media Data
How can you understand what customers are thinking, and how can you respond to sentiment in real time? Can
you gain competitive advantage from knowing what consumers are saying about your competition online? Social
media data can be stored and processed in Hadoop to gain insight into consumer sentiment.
http://hortonworks.com/sentiment

B)
Deliver responsive IT from events in Server Logs
How could you perform forensics and quickly respond to an enterprise security breach? Can you analyze your
server log data to identify and react to network issues, before you experience downtime? Server logs are being
mined in Hadoop for key moments in time that allow system administrators to identify and react to issues.
http://hortonworks.com/serverlogs

C)
Gain granular customer segmentation with web Clickstream Data
Where aren’t people checking out their shopping carts? What areas of your website should improve? Do you
truly understand what granular segments of customers are doing on your website? Now you can store years of
clickstream data and analyze it over time to gain these insights with Hadoop.
http://hortonworks.com/clickstream

D)
Enable predictive analytics from your Machine and Sensor Data
Assembly lines, office buildings, cell towers and jet engines all stream data that can be used to inform business
decisions. This machine or sensor data is real time and the massive volumes of it can now be explored using
Hadoop to perform predictive analytics. Wouldn’t it be easier to repair than replace that key instrument in the field?
http://hortonworks.com/sensor

E)
Optimize global logistics operations with Geolocation Data
The volume of geolocation data is increasing at an exponential rate. Hadoop reduces the cost to store and
process this geolocation data, opening the door to a quantum leap in data analytics. Now you can know where
everything you care about is (or has been) at every moment in time, going back for years.
http://hortonworks.com/geolocation
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