SQL-MapReduce Applications

Customer Use Cases

Aster Data customers use SQL-MapReduce to ask questions of their data that were previously impossible, or the results were so slow that they could not meet service level agreements. In these webcast tutorials, you will learn how customers are writing SQL-MapReduce functions for:

Fraud Detection
Graph Analysis
Sharing Behavior
Sessionization
Search Behavior
Transformations

You can learn more about additional MapReduce applications at www.mapreduce.org.

Fraud Detection
A large online gaming company catches cases of fraud that previous queries could not detect. And the company reduced its fraud analytics cycle time from one week to 15 minutes.


Graph Analysis
A social media company uses the SQL-MapReduce function nPath for graph analysis to understand how its users are connected and enahance the networks of its community.


Sharing Behavior
ShareThis uses SQL-MapReduce to reduce query times as it analyzes the items that people share online to understand sharing behavior.


Sessionization
A social network uses the SQL-MapReduce function "sessionize" to break user data into sessions based on the length of time between activity on the network. With sessionize, the SQL code dropped from more than 1000 lines to less than 100 and performance improved dramatically.


Search Behavior
An online media company uses the SQL-MapReduce function nPath to better understand the patterns its users follow after conducting a search so the company can improve search results.


Transformations
Where data transformations previously required multiple complex self joins, a media company now uses the SQL-MapReduce function nPath to make a single pass of its data, significantly simplifying the code while improving performance.


Read much more on SQL-MapReduce on our blog


The Best Insights Possible
Demo: Multi-channel
Customer Attrition
White Paper: A Revolutionary Approach for Advanced Analytics and Big Data Management
Whitepaper: Deriving Deep Insights from Big Datasets
Research Report: MapReduce and the Data Scientist