Behavioral Analytics Starter Kit is a cloud lab for developers where they can learn how to create powerful behavioral analytics applications using Hadoop and Mahout, and deploy them on Amazon Cloud with Qubell Adaptive PaaS. This starter kit presents a complete example of a common application of behavioral analytics - a Product Recommendation engine for an eCommerce store.
Below is an example of the web store displaying its product recommendations.

Behavioral Analytics Starter Kit supports the following main use cases out of the box:
- Deploy web store
- See how recommendations work on the web store
- Deploy recommendation engine
- Review recommendation algorithm
- Generate synthetic transaction log
- Generate product recommendations based on transaction log
- Push new recommendations to the web store
- Use monitoring tool Ganglia to monitor the cluster
Here is a brief outline of the steps required to successfully see the product recommendations.


- Amazon AWS account- Your own
- Qubell express account- Free, register at qubell.com
- Sample web store: Broadleaf Commerce- is distributed with the kit and available under Apache 2.0.
- Recommendation engine: Cloudera Hadoop- is distributed with the kit.
- Machine learning library: Apache Mahout
- Monitoring: Ganglia
- Product catalog: Magento Commerce
- Chapter 1- Overview and Frequently Asked Questions
- Chapter 2- Getting Started
- Chapter 3- Working with the Web Store
- Chapter 4- Working with Recommendation Engine
- Chapter 5- To See the Recommendations
- Chapter 6- Summary and What's Next?
- Glossary
- Troubleshooting
- Grid Dynamics- http://www.griddynamics.com
- Qubell- http://qubell.com/
- Amazon EC2- http://aws.amazon.com/ec2/
- Broadleaf Commerce- http://www.broadleafcommerce.org/
- Qubell Support- https://qubell.zendesk.com/home
- Qubell Documentation- http://docs.qubell.com/
- Link to the Starter Kit- http://qubell.com/starter-kits/BASK/
- Amazon EC2 Security Set up- http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-network-security.html#adding-security-group-rule
- Email for questions- [email protected]
- Research Paper: "PFP: Parallel FP-Growth for Query Recommendation"- http://infolab.stanford.edu/~echang/recsys08-69.pdf
- Home of Apache Hadoop Project- http://hadoop.apache.org/
- Parallel Frequent Pattern Mining- https://cwiki.apache.org/confluence/display/MAHOUT/Parallel+Frequent+Pattern+Mining
Starter Kit is provided under the Apache 2.0 license.
