Architecting analysis of Structured and unstructured data

For Analysis of Structured data maintained in Data warehouse. Datawarehouse structured data has following characteristics:

Subject oriented , Integrated, NonVolatile(data does not change),Time variant(historical data varies on time).
read more definitions from guide:

But unstructured data follows characteristics of 5V volume,variety,variability,value,velocity of data. So There is no structure to data in form of fixed columns and rows. So data warehouse needs to incorporate and drive intelligence taking this 5V challenge. read more

For Unstructured data we have technology like Hadoop with HIVE acting as datawarehouse.

Apache Hadoop ecosystem covers most unstructured data analysis tools and technology namely

Apache Hadoop hive: datawarehouse of unstructured data using hadoop.
Apache Hadoop Hbase: SQL like query support to access hadoop covered data.
Apache Hadoop HDFS: distributed database Hadoop filesystem.
Apache Hadoop Mahout: Analytics engine on top of Hadoop ecosystem.

Trend of favouring Real time data quick Feedback rather than Batch processing. Hadoop is good for batch processing large parallel loads

Cloud Computing relation to Business Intelligence and Datawarehousing
Read :

Cloud Computing and Unstructured Data Analysis Using
Apache Hadoop Hive
Also it compares Architecture of 2 Popular BI Tools.

Cloud Data warehouse Architecture:

Future of BI
No one can predict future but these are directions where it moving in BI.