There are 4 associated videos that will help you understand four scenarios used in the patterns & practices Developing big data solutions on Microsoft Azure HDInsight guide:
- Scenario 1: Iterative exploration: A common big data analysis scenario is to explore data iteratively, refining the processing techniques used until you discover something interesting or find the answers you seek. In this example of the iterative exploration use case and model, HDInsight is used to perform some basic analysis of data from Twitter.
- Scenario 2: Data warehouse on demand: In a data warehousing scenario, HDInsight is used as a data source for big data analysis and reporting. This scenario also discusses how you can minimize running costs by shutting down the cluster when it's not is use.
- Scenario 3: ETL automation: In this scenario, HDInsight is used to perform an Extract, Transform, and Load (ETL) process on data to filter and shape it, and then populate a database table.
- Scenario 4: BI integration: This scenario explores ways in which big data batch processing with HDInsight can be integrated into a business intelligence (BI) solution in a corporate environment. The emphasis in this scenario is on the challenges and techniques associated integrating data from HDInsight into a BI ecosystem based on Microsoft SQL Server and Office technologies.
For more info, see Designing big data solutions using HDInsight.