While every organization is different, their “big data” is often very similar.
Hadoop, as a critical piece of the modern data architecture, can collect massive amounts of data across social media activity, clickstream data, server logs, financial transactions, videos, and sensor data from equipment in the field. This data was once thought of as low to medium value or even ‘exhaust data’: too expensive to store and analyze. Now, these big data sources are turning a conversation from “data analytics” to “big data analytics” because they hold significant business value.
If you are looking for the value of big data it is best start at the root of it all… the types of big data found in Hadoop.
Get started with this tutorial using Hortonworks Sandbox. More »
- Understand your customers’ sentiment with Social Media Data
How can you understand what customers are thinking, and how can you respond to sentiment, either positive or negative, in real time? Can you gain competitive advantage from knowing what consumers are saying about your competition online? This demonstration will show you how to analyze Twitter to gain insight into customer sentiment. More »
- Deliver responsive IT from events in Server Logs
If faced with an enterprise security breach, how could you use Hadoop to perform forensics and quickly respond to the situation? Can you analyze your server log data to identify and react to network issues, before you experience downtime? This video shows you how system administrators can use log data to identify and react to a DDoS attack. More »
- Gain granular customer segmentation with web Clickstream Data
Where are people bouncing from your website? Is there a reason they aren’t checking out their shopping carts? What areas of your website should improve? Do you truly understand what granular segments of your customer population is doing on your website? This demonstration will show you how to clickstream data to gain insight into granular customer segmentation. More »
- 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. In this example, Hadoop is used to analyze heating, ventilation and air conditioning data to maintain ideal office temperatures and minimize expenses. More »
- Optimize global logistics operations with Geolocation Data
The volume of geolocation data, transmitted by sensors, 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. More »