Warehouse Manager

A load manager extracts data from the source system. Fast load the extracted data into temporary data store. Perform simple transformations into structure similar to the one in the data warehouse.

Following are the different types of Datawarehousing:

☛ Enterprise Datawarehousing

☛ Operational Data Store

☛ Data Mart

Snowflake schema which has primary dimension table to which one or more dimensions can be joined. The primary dimension table is the only table that can be joined with the fact table.

Following needs to be done when the database is shutdown:

☛ Close the database

☛ Dismount the database

☛ Shutdown the Instance

VLDB is abbreviated as Very Large Database and its size is set to be more than one terabyte database. These are decision support systems which is used to server large number of users.

Dimensional Modeling is a concept which can be used by dataware house designers to build their own datawarehouse. This model can be stored in two types of tables – Facts and Dimension table.

Fact table has facts and measurements of the business and dimension table contains the context of measurements.

Foreign keys of dimension tables are primary keys of entity tables. Foreign keys of fact tables are the primary keys of the dimension tables.

Dimensional model consists of dimension and fact tables. Fact tables store different transactional measurements and the foreign keys from dimension tables that qualifies the data. The goal of Dimensional model is not to achieve high degree of normalization but to facilitate easy and faster data retrieval.

Ralph Kimball is one of the strongest proponents of this very popular data modeling technique which is often used in many enterprise level data warehouses.

Aggregate tables are the tables which contain the existing warehouse data which has been grouped to certain level of dimensions. It is easy to retrieve data from the aggregated tables than the original table which has more number of records.

This table reduces the load in the database server and increases the performance of the query.

Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. A data warehouse is often built to enable Data Analytics

Conformed fact is a table which can be used across multiple data marts in combined with the multiple fact tables.

Real-time datawarehousing captures the business data whenever it occurs. When there is business activity gets completed, that data will be available in the flow and become available for use instantly.

Some applications include:

☛ financial services

☛ banking services

☛ customer goods

☛ retail sectors

☛ controlled manufacturing