Data Warehousing Basics

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    What is a Data Warehousing?

    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...


    • Mar 10th, 2017

    The complete process of ETL activities (Extract, Transform and Load) and BI (Business Intelligence for generating reports) are called Data Warehousing.


    • Jan 25th, 2017

    Datawarehousing is a process of Designing a database Schema, ETL process and Reporting.


    What is the difference between Datawarehouse and Datawarehousing


    • Jan 25th, 2017

    Datawarehouse: Datawarehouse is a container consists of Subject-oriented, Time variant, Non-volatile and Integrated collection of data which is a Historical data. Datawarehousing: Datawarehousing i...

    Rahul Kumar

    • Oct 12th, 2011

    Hey Opbang Ur statement "Datawarehousing is not just having a single data warehouse", with datawarehousing it is understood that business decision can be taken and lots of information and analysis rep...


    What is a lookup table


    • Jan 25th, 2017

    Lookup for some related data in Database or Flatfiles or Database View based on key column

    Johnson Weltch

    • Dec 16th, 2016

    This was great to know more about lookup table in database. You may also go through this informative article on look up table to get brief knowledge about Lookup table in database:
    Lookup table in SQL Server at sqlmvp org


    What are the Different methods of loading Dimension tables


    • Jan 25th, 2017

    There are 2 types of data loading.
    1. Initial Loading: Data loading for the first time in to Table/Database is called Initial Loading.

    2. Incremental Loading: Inserting new data and updating existing data which comes with new values is Incremental Loading.

    mukul konch

    • Aug 16th, 2014

    The data in the dimension tables may change over a period of time. Depending upon how you want to treat the historical data in dimension tables, there are three different ways of loading the (slowly)...


    What is a Star Schema

    Answer posted by Chintan on 2005-05-22 18:34:55: A relational database schema organized around a central table (fact table) joined to a few smaller tables (dimension tables) using foreign key references. The fact table contains raw numeric items that represent relevant business facts (price, discount values, number of units sold, dollar value, etc.)


    • Jan 25th, 2017

    A Fact table is surrounded by multiple Dimension tables and which is look like STAR in graphical design is called "STAR Schema".


    • Sep 16th, 2011

    Star schema defined as,A fact table is surrounded my many multiple dimension tables.
    (it means all dimension tables directly maintains relationship with the fact tables in this schema)


    What is data cleaning? how is it done?


    • Jan 25th, 2017

    Data Cleansing is the process of converting inconsistent data into consistent data and removing unwanted data.


    • Sep 28th, 2014

    It is a first step of data warehousing . there we are validating and verifying data come from number of source than load in ODS it called delta loading or staging area or cleaning stage.


    What is surrogate key ? Where we use it explain with examples?

    Star Read Best Answer

    Editorial / Best Answer

    Answered by: saravanan

    • Dec 2nd, 2005

    Surrogate key is a unique identification key, it is like an artificial or alternative key to production key, bz the production key may be alphanumeric or composite key but the surrogate key is always single numeric key. Assume the production key is an alphanumeric field if you create an index for this fields it will occupy more space, so it is not advisable to join/index, bz generally all the datawarehousing fact table are having historical data. These factable are linked with so many dimension table. if it's a numerical fields the performance is high


    • Oct 16th, 2016

    A surrogate key is any column or set of columns that can be declared as the primary key instead of a "real" or natural key. Sometimes there can be several natural keys that could be declared as the primary key, and these are all called candidate keys.So a surrogate is a candidate key.


    • Feb 1st, 2016

    Thank you for your advice


    What is the Difference between OLTP and OLAP

    Answered by swetha on 2005-03-30 12:00:33: OLTP  Current data Short database transactions Online update/insert/delete Normalization is promoted High volume transactions Transaction recovery is necessary   OLAP Current and historical data Long database transactions Batch update/insert/delete Denormalization is promoted Low...


    • Aug 30th, 2016

    OLTP: Original Source of data
    Running on fundamental business task

    OLAP: Data coming from various OLTP sources
    Problem Solving, Decision Making


    • Jan 16th, 2015

    Very useful answer.


    Can a dimension table contains numeric values?


    • Aug 17th, 2016

    Yes, A dimension Table can have numeric data types and information. For example. the surrogate key columns which are numeric. and in a scenario if a product has min discount and max discount column...


    What is rapidly changing dimension?


    • Apr 16th, 2016

    No, Actually there is something called Rapidly Changing Dim or Fast Growing Dim, it is the Dim that contains an attribute that changes frequently. and one solution is to move this attribute to a new mini dim with a separate foreign key in the fact table.

    dipanshu handoo

    • May 26th, 2012

    A dimension is considered to be a rapidly changing dimension if one or more of its attributes changes frequently in many rows. For a rapidly changing dimension, the dimension table can grow very large from the application of numerous Type 2 changes.


    Pushdown Optimization

    What is push down optimization ? what is its use and importance in data warehousing ?


    • Nov 1st, 2015

    I need brief explaination about
    * Source side pushdown optimization
    * Target side pushdown optimization
    * Full pushdown optimization

    Sreedhar Lokaray

    • Nov 3rd, 2011

    Pushdown Optimization is a new feature introduced from Informatica 8. To increase session performance, the integration service pushes transformation logic to the source or target database. Based on t...


    Question about the design

    I am a programmer, VB .NET.
    I have a Question about the design tools in this photo.
    Whether the list box is used?or tree view?
    What tools are used?
    Thank you.


    What is SCD1 , SCD2 , SCD3


    • Feb 20th, 2015

    SCD1: in SCD1, no history is maintained.
    SCD2: whole history is maintained.
    SCD3: just the current and last record is stored.


    • Nov 22nd, 2013

    The value of dimensions is used change very rarely, That is called Slowly Changing dimensions.

    they are 3 types


    scd1:it used Replace the old values overwrite by new values
    scd2:Creating Additional records
    scd3:Its maintain just previous and recent


    What are the vaious ETL tools in the Market


    • Nov 17th, 2014

    I dont see Boeings TwisterDataFramework. It is used extensively in the US Government and I thought it would be reviewed here.

    Ashutosh Shukla

    • May 4th, 2012

    1. Oracle Warehouse Builder (OWB) 11gR1 Oracle 2. Data Services XI 3.2 SAP Business Objects 3. IBM Information Server (Datastage) 9.1 IBM 4. SAS Data Integration Studio 4.21 SAS Institute 5. Pow...


    HLD, LLD , Mapping Documents

    what is high level document(HLD),lowlevel document(LLD),MAPPING documents ? what is the stuff they contains?


    • Nov 13th, 2014

    High Level Design document will prepare by the Data Modeling people to generate the required data warehouse schema for the ETL purpose. LLD : Low Level Design is the design document which will be use...

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