Real-time data warehousing is a combination of two things: 1) real-time activity and 2) data warehousing. Real-time activity is activity that is happening right now. The activity could be anything such as the sale of widgets. Once the activity is complete, there is data about it.

Data warehousing captures business activity data. Real-time data warehousing captures business activity data as it occurs. As soon as the business activity is complete and there is data about it, the completed activity data flows into the data warehouse and becomes available instantly. In other words, real-time data warehousing is a framework for deriving information from data as the data becomes available.

Level of granularity means level of detail that you put into the fact table in a data warehouse. For example: Based on design you can decide to put the sales data in each transaction. Now, level of granularity would mean what detail are you willing to put for each transactional fact. Product sales with respect to each minute or you want to aggregate it upto minute and put that data.

Data Marts are designed to help manager make strategic decisions about their business. Data Marts are subset of the corporate-wide data that is of value to a specific group of users.
There are two types of Data Marts:

1.Independent data marts – sources from data captured form OLTP system, external providers or from 
data generated locally within a particular department or geographic area. 

2.Dependent data mart – sources directly form enterprise data warehouses.

Conformed dimensions are the dimensions which can be used across multiple Data Marts in combination with multiple facts tables accordingly.

Conventional Load:
Before loading the data, all the Table constraints will be checked against the data. 

Direct load:(Faster Loading)
All the Constraints will be disabled. Data will be loaded directly.Later the data will be checked 
against the table constraints and the bad data won't be indexed.