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Maintain Dimensions - ETL or Data Entry
For a Customer or Product Dimension with 500,000 rows changing daily an ETL solution is the only sensible way forward. But surely you shouldn't ETL every single Dimension table - especially if there's over a hundred of them, and they're are static, error prone or manually enhanced? What would you advise / normally do ?
mri_sonam
- Dec 17th, 2008
If you are designing a Data Warehouse how can you rely on manual process? better way is to use ETL wherever required or else just extract and load.But you should refresh all your dimensions regularly ...
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What is slicing and dicing? Explain with real time usage and business reasons of it's use
mri_sonam
- Dec 17th, 2008
The ability to move between different combinations of dimensions when viewing data with an OLAP browser/Report Browser.Multidimensional analysis tools organize the data in two primary ways: in multipl...
ucontactmadhu
- May 2nd, 2007
Hi, Slicing and Dicing is a feature that helps us in seeing the more detailed information about a particular thing. For eg: You have a report which shows the quarterly based performa...
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What is Replicate,Transparent and Linked cubes?
mri_sonam
- Dec 18th, 2008
Linked CubeA 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. ...
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What are the advantages data mining over traditional approaches?
mri_sonam
- Dec 18th, 2008
Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be ...
hussenshaik
- Sep 12th, 2008
Datamining is a process of looking information in different prospective that means, if you have data of sales of different products in different months we can find hiding data from same tables in the ...
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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 are the possible data marts in Retail sales.?
ABHI2411
- Jan 8th, 2009
The possible Data Marts in Retail Sales can be-1) Sales-Sales Order Management and Customer related.Accounts receivables2) Purchase-Purchase Order management and Vendor related.Accounts payables3) Fin...
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How do you connect two fact tables ? Is it possible ?
sixto.dsilva
- Sep 20th, 2008
As comment by lot of DWH gurus above, two fact tables can be connected only using conformed dimension, defination of conformed dimension:if one primary key of dimension is defined in two fact tables it is called conformed dimension.
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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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How data in datawarehouse stored after data has been extracted and transformed from hetrogeneous sources and where does the data go from datawarehouse.
sharuvijay
- Jan 29th, 2009
Data is stored in DW in a relational, aggregatted (if needed), denormalized fashion where the data can be easily analysed.
sixto.dsilva
- Sep 11th, 2008
Data will stored in fact's and dimensional tables, the relational database can be Oracle, Informatic or netezza, it purely depends upon the company which technology they want to go for.
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Transformation keys into generic key by system itself is called as
aquacooldude
- Feb 19th, 2009
The transformation of keys which are supposed to be used as primary key into generic key by the system is called as key restructuring. The problem is something like this, let us a say there was an ex...
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Explain Bill Inmon's versus Ralph Kimball's Approach to Data Warehousing.
Bill Inmon vs Ralph Kimball In the data warehousing field, we often hear about discussions on where a person / organization's philosophy falls into Bill Inmon's camp or into Ralph Kimball's camp. We describe below the difference between the two.Bill Inmon's paradigm: Data warehouse is one part of the overall business intelligence system. An enterprise has one data warehouse, and data marts source their...
tisha24
- Mar 3rd, 2009
Bill inmon's approach:--------------------------- Approach is "TOP DOWN approach". ;means Emphasize the data warehouse. Starts with designing an enterprise model f...
sithu
- Nov 19th, 2007
Bill inmon : Data warehouse à Data martRalph Kimbol : Data mart à Data warehouseCheers,Sithu, sithusithu@Hotmail.com
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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 is a level of Granularity of a fact table
ibrarx
- Mar 7th, 2009
The smallest unit of analysis is called as 'grain'. Also known as the atomic unit of analysis. Deciding the grain and then on basis of it, the aggregation level is called as the granularity of a fact table.
Santanu Patra
- Jun 29th, 2005
It also means that we can have (for example) data agregated for a year for a given product as well as the data can be drilled down to Monthly, weekl and daily basis...teh lowest level is known as the grain. going down to details is Granularity
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What type of Indexing mechanism do we need to use for a typical datawarehouse
Answered by on 2005-03-23 01:45:54: bitmap index
ibrarx
- Mar 7th, 2009
Hash Index - If we know that the hashing will result in uniform distribution and doesn't create hotspots (spikes-chaining).Bitmap Index - If the degree of cardinality is high for the attribute, me...
cetzhbo
- Jun 19th, 2007
Space requirements for indexes in a warehouse are often significantly larger than the space needed to store the data, especially for the fact table and particularly if the indexes are B*trees.Hence, y...
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What is data validation strategies for data mart validation after loading process
kalpit
- Mar 10th, 2009
Data validation is generally done manually in DWH, in this case if source and TGT are relational you need to create SQL scripts to validate source and target data, and if source is Flat file or non re...
uma
- May 3rd, 2006
Data validation is to make sure that the loaded data is accurate and meets the business requriments.Strategies are different methods followed to meet the validation requriments
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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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What is the differences between the static and dynamic caches?
ramakrishna.inf
- Apr 21st, 2009
Static cache - It doesn't reflect changes once data is cached is known as static cache.
Dynamic cache - It reflect to changes at the time of running the session if any updates happen in source data.jayadhar
- Sep 4th, 2006
static cache stores overloaded values in the memory and it wont change throught the running of the session where as dynamic cache stores the values in the memory and changes dynamically duirng the run...
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What is ER Diagram
Answered by Puneet on 2005-05-07 04:21:07: ER - Stands for entitity relationship diagrams. It is the first step in the design of data model which will later lead to a physical database design of possible a OLTP or OLAP database
sukhdev_ce
- Apr 30th, 2009
The ER Diagrams is the initial process to analaysis a database application, and understands the problems related or causes in future with the choosed database application, in this satge different comp...
clickharri
- Apr 22nd, 2008
Entity Relationship Diagrams are a major data modelling tool and will help organize the data in your project into entities and define the relationships There are three basic elements in ER models: Ent...
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ODS and Staging
What is the difference between ODS and Staging?
prat4all
- May 25th, 2009
ODS keeps the transactional data from where direct reporting is possible. The data in ODS can be partly denormalized.Staging area is the exact replica of the transactional database which acts as a source for datawarehouse processing.
shanavaz
- Nov 1st, 2008
ODS, Operational Data Store is majorly different from Staging in the below aspects: - Existing Records in the System can get updated based on necessary instructions & design. - It can be use...
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What is ETL
ETL is extraction,transformation and loading,ETL technology is used for extraction the information from the source database and loading it to the target database with the necessary transformations done in between.
rsp2709
- Jun 8th, 2009
ETL is a process that extracts data from one database, transforms it as per the destination database and loads it into another database. In the transformation process, data is actually standardized to...
jaggu_mandya
- Jan 16th, 2008
Data Acquisition technique is now called ETL(Extraction, Transformation and Loading)Extraction-The process of extracting the data from various sources. Sources can be file system, database, XML file, ...
Data Warehousing Basics
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