Question

whats the purpose of data warehouse design ?

how is dimensional data models implemented in a database covering relation implementation and multidemensional implementation.

Answer 1

Whats the purpose of data warehouse design?

Answer:- Purpose of data warehouse design lies somewhere in its definition itself i.e. database created by combining data that is gathered through various sources that can be different types and formats( e.g. text, sql, xml, etc.).

A data warehouse is designed with the purpose of including business decisions by llowing data consolidation, analysis, and reporting at different aggregate levels. Data is populated into the DW by extraction, transformation, and loading.

Now what you will do after storing such huge amount of data from different sources into a single database, you will analyse the data which you have accumulated and try to answer queries which were not possible er were performance intensive earlier.

Data warehouse is a process of collecting data,transforming it, loading into single database and then using a BI( Business Intelligence ) tool to answer your analytical queries and preiction of any further questions that may arise are helpful to your domain or business

Below are few reasons:-

1. Improving Visibility of Data.
2. Improved Performance.
3. Increase Data Quality.
4. Faster and More advanced Reporting.

how is dimensional data models implemented in a database covering relation implementation and multidemensional implementation.

Answer:- Steps for dimensional data models implement in a database :-

1. step:- Implementing business objective: Sales, HR, Marketing, etc. are sme examples as per the need of the organisation. it is the mosr important step of data modeling the selection of business objective also depends on the quality of data available for that process.
2. step:- Identifying Granularity: granularity is the lowest level of detail for business problem and its solution is describes by grain.
3. step:- Identifying Dimensions and its Attributes: dimensions are objective or things. it categorize and describe data warehouse facts and measures in a way that support meningful answers to business questions.
4. step:- Identifying the Fact: the measurable data is hold by the fact table. Most of the fact table rows are numerical values like price or cost per unit, etc.
5. step:- Building of Schema: we implement the dimension model in this step. A schema ia database structure. there are two popular schemas: Star schema and Snoeflake schema.

Relational database implemention:- a relational database stores data in tables. Tables are organized into columns, and each column stores one type of data(integer, real number, character strings, etc.) The data for a single "instance" of a table is stored as a row.

Multidimensional database implemention:- this are used mostly for OLAP (online analytical processing) and data warehousing. Thet can be used to show multiple dimensions of data to users. A multidimensional is created for multiple relational databases.