Explain the difference between data mining and data warehousing.

Correct Answer: 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

Correct Answer: Consignment stock is the material which is lying in the premises but is not owned by the company It has no value assigned to it until it is taken into own stock Once it is used in production or to be sold, it is taken into own stock

Correct Answer: LSMW is widely used by EDI programmers EDI Programmers connect the SAP system to Non SAP system During this Data migration is a necessity When data migrates from source to destination the destination code is differrent from the source code So what LSMW does is * Converts the data in to batch files * Then converts the batch files in to source code batch files * And then mirgates data Standard Interfaces like BAPI or Idoc are used in this process

Correct Answer: In an Interactive Report, user can define maximum 20 secondary lists

Correct Answer: BDC ----> Batch Data Communication Methods of BDC-----> Direct Input method, Batch Input Session method, Call transaction method

Correct Answer: Business facts or measures and foreign keys are persisted in fact tables which are referred as candidate keys in dimension tables Additive values are usually provided by the fact tables which acts as independent variables by which dimensional attributes are analyzed Attributes that are used to constrain and group data for performing data warehousing queries are persisted in the dimension tables

Correct Answer: OLTP stands for OnLine Transaction Processing Applications that supports and manges transactions which involve high volumes of data are supported by OLTP system OLTP is based on client-server architecture and supports transactions across networks OLAP stands for OnLine Analytical Processing Business data analysis and complex calculations on low volumes of data are performed by OLAP An insight of data coming from various resources can be gained by a user with the support of OLAP

Correct Answer: Dimensional modeling is often used in Data warehousing In simpler words it is a rational or consistent design technique used to build a data warehouse DM uses facts and dimensions of a warehouse for its design A snow and star flake schema represent data modeling

Correct Answer: 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

Correct Answer: View: - Tail raid data representation is provided by a view to access data from its table - It has logical structure can not occupy space - Changes get affected in corresponding tables Materialized view - Pre calculated data persists in materialized view - It has physical data space occupation - Changes will not get affected in corresponding tables