Information Services

The Hadoop platform was designed to solve problems with inherent volumes and variety of data, including a mixture of unstructured and structured data. Hadoop benefits all companies that perform deep and computationally extensive analytics. Examples include:

• Customer experience analytics - Corporations need to provide more accurate and faster analytics around customer interactions by pulling from more data sources and processing the information faster.
• Customer lifecycle management - Many organizations have a need to perform true root-cause analysis of customer churn and to identify and implement targeted actions to help reduce turnover.
• Risk Management - Two of the largest areas for Hadoop usage across industries include fraud detection and data security. Fraud detection requires the ongoing processing of large and varied data sets to recognize fraud signatures. IT groups also need to protect the organization from internal and external threats. A growing number and variety of attacks require Hadoop deployments to deliver faster and more accurate detection and prevention solutions.
• Analytic-ready, low cost, scalable storage - Many use cases call for low cost, commodity hardware and Hadoop to store large amounts of data. This can include the storage of transactional data, social media data, sensor data, scientific data, emails, etc.