SAP HANA Data Warehouse

Using SAP HANA system for data warehousing has started trending across the top organization for several reasons. Let it be its incredible speed or a vast range of built-in features. As data warehousing involves crucial discipline concentration on the integration and management of databases over a period of time, it is very important that the system should contain reliable and effective architecture. SAP HANA fulfills every need of security and consistency for a strong data warehouse. There is no one way to do data warehousing, and every methodology will have ways of handling problems like integration, data quality, access control, time dependency and data volume in a consistent way.

SAP's data warehousing modeling and management application using SAP HANA system are pretty interesting and effective.

Schema in Data Warehouse

Schemas in Data Warehouse are defined as the logical description of tables in the Data Warehouse. They are created by concatenating multiple dimension tables and fact tables to meet the definite business logics. The database uses the relational model to store data. Whereas the data warehouses generally use schemas to meet business logics. Basically, there are 3 types of schemas used in the data warehouses. They are,

• Star Schema
• Snowflakes Schema
• Galaxy Schema

Star Schema

Star Schema involves clubbing every Dimension to one single Fact table. So that, each Dimension can be represented by only one dimension and is not further normalized. Dimension Table contains set of attribute that is used to analyze the data. For instance, if we have a Fact table that has Primary keys for all the tables and measures units to do analysis, each Dimension table is connected to Fact table as Fact table has Primary Key for each Dimension Tables that is used to join two tables. Every Facts and Measure in Fact Table are used for analysis purpose along with attribute in Dimension tables.

Snowflakes Schema

In Snowflakes schema, a specific range of Dimension tables are further, normalized and Dim tables are integrated into a single Fact Table. Normalization technique is used to arrange attributes and tables of the database to minimize the data redundancy. These normalization procedures involve breaking a table into less redundant smaller tables without losing any information and smaller tables are joined to Dimension table.

Galaxy Schema

Galaxy Schema in SAP Data warehousing involves multiple Fact tables and Dimension tables. Each Fact table stores primary keys of few Dimension tables and measures/facts to do the analysis.