Faqs on DW - Page6

What are the possible data marts in Retail sales?

Product information, sales information

What is the definition of normalized and de-normalized view and what are the differences between them?

Normalization is the process of removing redundancies.
De-normalization is the process of allowing redundancies.

What is meant by metadata in context of a Datawarehouse and how it is important?

Meta data is the data about data; Business Analyst or data modeler usually capture information about data - the source (where and how the data is originated), nature of data (char, varchar, nullable, existence, valid values etc) and behavior of data (how it is modified / derived and the life cycle ) in data dictionary a.k.a metadata. Metadata is also presented at the Datamart level, subsets, fact and dimensions, ODS etc. For a DW user, metadata provides vital information for analysis / DSS.

Differences between star and snowflake schemas?

Star schema
A single fact table with N number of Dimension
Snowflake schema
Any dimensions with extended dimensions are know as snowflake schema

What is the datatype of the surrogate key?

Datatype of the surrogate key is either integer or numeric or number

What is degenerate dimension table?

Degenerate Dimensions: If a table contains the values, which r neither dimension nor measures is called degenerate dimensions. Ex: invoice id, empno

What is Dimensional Modeling?

Dimensional Modeling is a design concept used by many data warehouse designers to build their datawarehouse. In this design model all the data is stored in two types of tables - Facts table and Dimension table. Fact table contains the facts/measurements of the business and the dimension table contains the context of measurements i.e., the dimensions on which the facts are calculated.

What are the methodologies of Datawarehousing?

Every company has methodology of their own. But to name a few SDLC Methodology, AIM methodology are standard ones other methodologies are AMM, World class methodology and many more.

What is a linked cube?

Linked cube in which a sub-set of the data can be analyzed into great detail. The linking ensures that the data in the cubes remain consistent.

What is the main difference between Inmon and Kimball philosophies of data warehousing?

Both differed in the concept of building the datawarehouse.
According to Kimball, Kimball views data warehousing as a constituency of Data marts. Data marts are focused on delivering business objectives for departments in the organization. And the data warehouse is a conformed dimension of the data marts. Hence a unified view of the enterprise can be obtained from the dimension modeling on a local departmental level.
Inmon beliefs in creating a data warehouse on a subject-by-subject area basis. Hence the development of the data warehouse can start with data from the online store. Other subject areas can be added to the data warehouse as their needs arise. Point-of-sale (POS) data can be added later if management decides it is necessary.

Kimball–First Datamarts–Combined way —Datawarehouse

Inmon—First Datawarehouse–Later—-Datamarts