Data Warehousing Questions

Data Mart is a data repository which is served to a community of people who works on knowledge (also known as knowledge workers). The data resource can be from enterprise resources or from a data warehouse.

- Physical Data Integration is all about creating new system that replicates data from the source systems.

- This process is done to manage the data independent of the original system.

- Data Warehouse is the example of Physical Data Integration.

- The benefits of PDI include data version management, combination of data from various sources, like mainframes, flat files, databases.

- A separate system is needed for handling vast data volumes.

Data cleaning is also known as data scrubbing. Data cleaning is a process which ensures the set of data is correct and accurate. Data accuracy and consistency, data integration is checked during data cleaning. Data cleaning can be applied for a set of records or multiple sets of data which need to be merged.

Data cleaning is performed by reading all records in a set and verifying their accuracy. Typos and spelling errors are rectified. Mislabeled data if available is labeled and filed. Incomplete or missing entries are completed. Unrecoverable records are purged, for not to take space and inefficient operations.

The primary keys of entity tables are the foreign keys of dimension tables.

The Primary keys of fact dimensional table are the foreign keys of fact tablels.

At the time of updating the data warehouse, a lookup table is used. When placed on the fact table or warehouse based upon the primary key of the target, the update is takes place only by allowing new records or updated records depending upon the condition of lookup.

The materialized views are aggregate tables. It contains summarized data. For example, to generate sales reports on weekly or monthly or yearly basis instead of daily basis of an application, the date values are aggregated into week values, week values are aggregated into month values and month values into year values. To perform this process aggregate function is used.

Cascade:

- Cascade process involves taking values from various other prompts.

- The result is a single report.

- The result is used when a criteria is to be implemented.

Drill Through:

- Drill Through process is implemented when navigation from summary to detailed information.

- Drill Through has a parent and a child report.

- Data of another report can be seen based on the current details of data.

Star schema: A highly de-normalized technique. A star schema has one fact table and is associated with numerous dimensions table and depicts a star.

Snow flake schema: The normalized principles applied star schema is known as Snow flake schema. Every dimension table is associated with sub dimension table.

Differences:

- A dimension table will not have parent table in star schema, whereas snow flake schemas have one or more parent tables.

- The dimensional table itself consists of hierarchies of dimensions in star schema, where as hierarchies are split into different tables in snow flake schema. The drilling down data from top most hierarchies to the lowermost hierarchies can be done.

Data warehousing is a process of repository of electronic data of an organization. For the purpose of reporting and analysis, data warehousing is used. The essence concept of data warehousing is to provide data flow of architectural model from operational system to decision support environments.