Social Networking

Social network services are increasingly becoming a part of everyday life, connecting people who share interests and activities from around the world. Gaining collective intelligence about the site via massive amounts of traffic data enables companies to increase the value of the network by providing more relevant content, connection recommendations, and by preventing spam.

Aster provides the analytic horsepower required on a massive scale for applications such as:

  • Web analytics – path analysis, attribution, user engagement, segmentation, and more. This is critical in making relevant site design decisions to deliver the right content and advertisements to the most relevant user segments, improving their site experience.
  • Recommendation engines – recommend people or networks to connect with based on similar interests (i.e., similarity scores).
  • Abuse prevention – detect activity correlated with spammers or fraud to prevent it from happening, or have the abuser removed from the network.

Get more details on how to solve some of the common social networking data issues:

Social Networking Issue Technical Causes
Takes too long to update spam detection rules Loading Performance, Query Performance
There is not enough data detail or history for sufficient analysis Data Growth
There is simply too much data to load into warehouse quickly Data Loading
Too expensive to scale as site membership grows Scaling
Too hard to scale data warehouse as network membership and activity increases Scaling
Data warehouse is hard to manage Administration
Top Picks
Whitepaper: New MapReduce Whitepaper
Webcast: Bringing Big Data Analytics to the Enterprise - 11/12, with Merv Adrian
Webinar: Service Oriented 'Analytics' - 11/19, with James Kobelius
MySpace gained a full understanding of what is happening online, immediately reflecting what people are doing on an hourly basis, both to give marketing efforts an edge and to identify customer issues before they spiral out of control.

MySpace
Aber Whitcomb, CTO