This is series of posts describing how you can use Big Data and related technologies to enable both business and customers to gain still unknown pieces of information. The articles explores different Big Data technologies and explain how you can use each one to get desired results.
It takes an example of typical eCommerce platform where a customer can browse different products. The technologies depict the approach and some sample examples to achieve relevant business and customer value using these Big Data technologies. Business can use same for Real time data analytics, Business Intelligence and also to understand customer behaviour on the site. It also enables business for relevant customers targetting.
- Customer product search clicks analytics using big data,
- Flume: Gathering customer product search clicks data using Apache Flume,
- Hive: Query customer top search query and product views count using Apache Hive,
- ElasticSearch-Hadoop: Indexing product views count and customer top search query from Hadoop to ElasticSearch,
- Oozie: Scheduling Coordinator/Bundle jobs for Hive partitioning and ElasticSearch indexing,
- Spark: Real time analytics for big data for top search queries and top product views
- HBase: Generating search click events statistics for customer behavior
The articles also explain code pieces shared on github. The repository provides you hands on these technologies,