General Datawarehousing Interview Questions and Answers (1)
What's A Data warehouse
A Data warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated. This makes it much easier and more efficient to run queries over data that originally came from different sources". Another definition for data warehouse is: " A data warehouse is a logical collection of information gathered from many different operational databases used to create business intelligence that supports business analysis activities and decision-making tasks, primarily, a record of an enterprise's past transactional and operational information, stored in a database designed to favour efficient data analysis and reporting (especially OLAP)". Generally, data warehousing is not meant for current "live" data, although 'virtual' or 'point-to-point' data warehouses can access operational data. A 'real' data warehouse is generally preferred to a virtual DW because stored data has been validated and is set up to provide reliable results to common types of queries used in a business.
Data Warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated....This makes it much easier and more efficient to run queries over data that originally came from different sources.
Typical relational databases are designed for on-line transactional processing (OLTP) and do not meet the requirements for effective on-line analytical processing (OLAP). As a result, data warehouses are designed differently than traditional relational databases.
Data Warehousing is concerned with the activities involved with creating a DataRepository where you store all the facts you know about some large enterprise or activity, and then analyse the data in different ways,to look for patterns on the data.
Typically this is done by large retail organisations, trying to identify patterns in buying behaviour so they can sell more stuff to the poor unsuspecting customer.
What is ODS?
1. ODS means Operational Data Store.
2. A collection of operation or bases data that is extracted from operation databases and standardized, cleansed, consolidated, transformed, and loaded into an enterprise data architecture. An ODS is used to support data mining of operational data, or as the store for base data that is summarized for a data warehouse. The ODS may also be used to audit the data warehouse to assure summarized and derived data is calculated properly. The ODS may further become the enterprise shared operational database, allowing operational systems that are being reengineered to use the ODS as there operation databases.
What is a dimension table?
A dimensional table is a collection of hierarchies and categories along which the user can drill down and drill up. it contains only the textual attributes.
What is a lookup table?
A lookUp table is the one which is used when updating a warehouse. When the lookup is placed on the target table (fact table / warehouse) based upon the primary key of the target, it just updates the table by allowing only new records or updated records based on the lookup condition.
Why should you put your data warehouse on a different system than your OLTP system?
A OLTP system is basically " data oriented " (ER model) and not " Subject oriented "(Dimensional Model) .That is why we design a separate system that will have a subject oriented OLAP system...
Moreover if a complex querry is fired on a OLTP system will cause a heavy overhead on the OLTP server that will affect the daytoday business directly.
The loading of a warehouse will likely consume a lot
of machine resources. Additionally, users may create
querries or reports that are very resource intensive
because of the potentially large amount of data
available. Such loads and resource needs will
conflict with the needs of the OLTP systems for
resources and will negatively impact those production systems.
(Continued on next part...)