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What is the difference between view and materialized view
mri_sonam
- Dec 18th, 2008
ViewsA view takes the output of a query and makes it appear like a virtual table. You can use a view in most places where a table can be used.All operations performed on a view will affect data in the...
vijay
- Jul 13th, 2006
View?is a logical reference to a database table. But Meterial View is actual table and we can refresh data in time intervels. If you made any change in database table that change will effect into view but not meterialize view..
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What is source qualifier?
kalyani
- Mar 28th, 2007
Source qualifier is a transformation which extracts data from the source. Source qualifier acts as SQL query when the source is a relational database and it acts as a data interpreter if the source is a flatfile.
sandrag
- Feb 7th, 2007
Source qualifier is an transformation which every mapping should have , it defines the source metadata to the Informatica Repository.The source qualfier has different properties like filtering records , and joining of two source , and so on .
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What is Normalization, First Normal Form, Second Normal Form , Third Normal Form
Answer posted by Badri Santhosh on 2005-05-18 09:40:29: Normalization : The process of decomposing tables to eliminate data redundancy is called Normalization. 1N.F:- The table should caontain scalar or atomic values. 2 N.F:- Table should be in 1N.F + No partial functional dependencies 3 N.F :-Table should be in 2 N.F + No transitive dependencies
dstorkey
- Mar 24th, 2009
To paraphrase the oath, and help you remember, in 3rd normal form data in the table depends on the key, the whole key, and nothing but the key.
Jyothsna Tallapally
- May 10th, 2006
Normalization:It is the process of efficiently organizing data in a database.There are 2-goals of the normalization process: 1. Eliminate redundant data 2. Ensure data dependencies make sens...
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What does level of Granularity of a fact table signify
ibrarx
- Mar 7th, 2009
The level of granularity of a fact table signifies the smallest unit of analysis.
ravi kumar guturi
- Mar 9th, 2006
Granularity means nothing but it is a level of representation of measures and metrics.The lowest level is called detailed dataand highest level is called summary dataIt depends of project we extract fact table significanceBye
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What are Semi-additive and factless facts and in which scenario will you use such kinds of fact tables
divya29july
- Feb 11th, 2010
Factless Fact table:Consider an example of Product on promotion, the fact table will contain information of only the products that were on sale and sold but not of those that did not sell as the fact ...
siraj.khan
- Aug 3rd, 2007
Semi-additive facts are those facts which can be aggregate according to the context. so, it can contain a fact but the factless fact table does not contain fact's but it contains the dimmentions. It's a type of a dimmentions.
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Differences between star and snowflake schemas
Answered by sudhakar on 2005-05-09 18:32:18: star schema uses denormalized dimension tables,but in case of snowflake schema it uses normalized dimensions to avoid redundancy...
sk.rafee
- Apr 26th, 2006
Star schema uses denormalized dimension tables,but in case of snowflake schema it uses normalized dimensions to avoid redundancy...
Guest
- Feb 13th, 2006
Star Schema &n...
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What is the main differnce between schema in RDBMS and schemas in DataWarehouse....?
Sam Kolta
- Apr 17th, 2010
User It is just an account name for the user Owns a schema Have the same name Create user command, create the user User can be considered schema User can created without schema It is the account for t...
senthil kumar B
- Feb 13th, 2006
Diff b.w OLTP and OLAP :------------------------OLTP Schema :* Normalized * More no.of trans* Less time for queries execution* More no.of users* Have Insert,delete and update trans. OLAP (D...
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What is meant by metadata in context of a Datawarehouse and how it is important?
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kalpit
- Mar 10th, 2009
Metadata is the Information about the Data which is being stored in DWH , Why its imp : 1. To know the flow of source data into Data Warehouse, 2. In case if you have many star schema or many subjec...
thumatinagaraju
- Oct 24th, 2006
Meta data is stored in repository only not in dataware house .. but we r placing our repository in database in that way ur correct ,,but not directly stored in the dataware house plz check it mam
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Which automation tool is used in data warehouse testing?
Santosh
- Jul 3rd, 2015
Datagaps ETL Validator has a lot of inbuilt features for ETL Testing automation. We are using it.
ora.amar
- Aug 5th, 2014
We can use Data Validation option DVO provided by informatica corporation to automate etl testing.
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What are non-additive facts
sharuvijay
- Jan 28th, 2009
Non Additive facts cannot be aggregrated along with dimenstion in the fact table. For eg. Age, weather
vineela
- Jul 18th, 2007
Non additive facts are the facts that do not participate in arithmetic caliculations. for example in stock fact table there will be opening and closing balances along with qty sold and amt etc. but opening and closing balances were never used in arithmetic calculations.
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Why are OLTP database designs not generally a good idea for a Data Warehouse
Answer posted by Shri Dana on 2005-04-06 19:04:05: OLTP cannot store historical information about the organization. It is used for storing the details of daily transactions while a datawarehouse is a huge storage of historical information obtained from different datamarts for making intelligent decisions about the organization.
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What is a linked cube?
A cube can be stored on a single analysis server and then defined as a linked cube on other Analysis servers. End users connected to any of these analysis servers can then access the cube. This arrangement avoids the more costly alternative of storing and maintaining copies of a cube on multiple analysis servers. linked cubes can be connected using TCP/IP or HTTP. To end users a linked cube looks like...
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Explain the situations where snowflake is better than star schema
DWAlchemist
- Apr 11th, 2008
A snowflake schema is a way to handle problems that do not fit within the star schema. It consists of outrigger tables which relate to dimensions rather than to the fact table.The amount of spac...
ghoshkunal123
- Feb 5th, 2008
Star schema is good for simple queries and logic. But snowflake schema is good for complex queries and logic. Snowflake schema is nothing but an extension of the star schema in which the dimension tables are further normalized to reducy redundancy. Hope this helps.
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Explain ODS and ODS types.
chand.abinitio
- Sep 27th, 2010
ODS is defined as subject-oriented and integrated data and volatile
repository of data.
Contains current or near to current data
could be used for day to day reporting/ low-level analysis
updatable data store
contains detail data, no summarization
data in homogeneous form.
jaggu_mandya
- Jan 11th, 2008
It is designed to support Operational Monitoring. It is subject oriented,integrated database which holds the current,detailed data.data here is volatile
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What is DATA integration
OM PRAKASH JHA
- Sep 7th, 2010
Data integration involves data combining in different residing in different sources and providing users with a unified view of these data.This process becomes significant in a variety of situations bo...
tisha24
- Oct 22nd, 2009
Data from different sources (like flatfiles, CSV, oracle, db2,teradata, mainfraes etc.) are extracted and transformed in to a single specific pattern (unique structure) and is know as integration of d...
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Bridge Table
What is the use of bridge table. Can give a simple example?
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Editorial / Best Answer
Sirini- Member Since Jun-2009 | Jun 14th, 2009
An example of a Bridge table would be relationship table between student_master and courses_master. A Student may participate in multiple courses and obviously in a course there will be multiple students. In this scenario to maintain relationships between student_master and courses_master we need another table, which may be called, Student_courses. This table will have all relationships between Students and Courses.A bridge table is a table that only contains the keys between the two tables in a many-to-many relationship. These tables typically consist of mostly key fields, the primary keys of the two tables needing the many to many relationships. Sometimes there are more data elements, but often there are only two columns, both foreign keys.
vijsarav11
- Oct 19th, 2009
Hi all... This is my view on bridge tables:Bridge table in simple can be called as reference tables. As the name indicates, this table can be used to link two tables with 1 reference id...
tisha24
- Oct 7th, 2009
A table which maintained to define the relationship between two different tables is known as bridge tables. For example, say there are two tables one table with employee information (an employee table...
Data Warehousing Basics
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