“Extract, transform, load (ETL) Frequently Asked Questions in various ETL (Extract, transform, load) Interviews asked by the interviewer. So learn Extract, transform, load (ETL) with the help of this ETL (Extract, transform, load) Interview questions and answers guide and feel free to comment as your suggestions, questions and answers on any ETL (Extract, transform, load) Interview Question or answer by the comment feature available on the page.”
A data warehouse can be thought of as a three-tier system in which a middle system provides usable data in a secure way to end users. On either side of this middle system are the end users and the back-end data stores.
Additve: A masure can participate arithmatic calulatons using all or any demensions.
Ex: Sales profit
Semi additive: A masure can participate arithmatic calulatons using some demensions.
Ex: Sales amount
Non Additve:A masure can't participate arithmatic calulatons using demensions.
Ex: temparature
There are various ways of Extracting Data from Source Systems.For example , You can use a DATA step, an Import Process .It depends with your input data styles. What kind of File/database it is residing in. Storing ur data in an ODS can be done thru an ODS stmt/export stmt/FILE stmt, again which depends on the file & data format ,You want your output to be in.
PowerCenter - ability to organize repositiries into a data mart domain and share metadata across repositiries.
PowerMart - only local repositiry can be created.
Aggregator Transformation
Expression Transformation
Filter Transformation
Joiner Transformation
Lookup Transformation
Normalizer Transformation
Rank Transformation
Router Transformation
Sequence Generator Transformation
Stored Procedure Transformation
Sorter Transformation
Update Strategy Transformation
XML Source Qualifier Transformation
Advanced External Procedure Transformation
External Transformation
Full Load: completely erasing the contents of one or more tables and reloading with fresh data.
Incremental Load: applying ongoing changes to one or more tables based on a predefined schedule
Refresh Load: the table will be truncated and data will be loaded again. Here we use to load static dimension table or type tables using this method.
Incremental Load: It is a method to capture on the newly created or updated record. Based upon the falg or Date this load will be performed.
Full Load: when we are loading the data for first time, either it may be a base load or history all the set of records will be loaded at a strech depends upon the volume.
Rejection of records either at the database due to constraint key violation or the informatica server when writing data into target table.These rejected records we can find in the badfiles folder where a reject file will be created for a session.we can check why a record has been rejected.And this bad file contains first column a row indicator and second column a column indicator.
These row indicators or of four types
D-valid data,
O-overflowed data,
N-null data,
T- Truncated data,
And depending on these indicators we can changes to load data successfully to target.
Explain your self
ETL - The process of extracting data from multiple sources.(ex. flat files,XML, COBOL, SAP etc) is more simpler with the help of tools.
Manual - Loading the data other than flat files and oracle table need more effort.
ETL - High and clear visibilty of logic.
Manual - complex and not so user friendly visibilty of logic.
ETL - Contains Meta data and changes can be done easily.
Manual - No Meta data concept and changes needs more effort.
ETL- Error hadling,log summary and load progess makes life easier for developer and maintainer.
Manual - need maximum effort from maintainance point of view.
ETL - Can handle Historic data very well.
Manual - as data grows the processing time degrads.
These are some differences b/w manual and ETL developement.
ETL tool is ment for extraction data from the legecy systems and load into specified data base with some process of cleansing data.
ex: Informatica,data stage ....etc
OLAP is ment for Reporting purpose.in OLAP data avaliable in Mulitidimectional model. so that u can write smple query to extract data fro the data base.
ex: Businee objects,Cognos....etc
1. PowerMart Designer
2. Server
3. Server Manager
4. Repository
5. Repository Manager
SAP Data can be loaded into Informatica in the form of Flat files.
Condition :
Informatica source qualifier column sequence must match the SAP source file.
ODS - Operational Data Store.
ODS Comes between staging area & Data Warehouse. The data is ODS will be at the low level of granularity.
Once data was poopulated in ODS aggregated data will be loaded into into EDW through ODS.
ODS: ODS is also a simalar small DWH which will help analyst to analysis the bussiness.It will have data for less number of days. generally it will be around 30-45 days. Like DWH here also we will primary keys will be genrated, error and reject handling will be done.
A few more ...
- Cognos Decision Stream
- Oracle Warehouse Builder
- Business Objects XI (Extreme Insight)
- SAP Business Warehouse
- SAS Enterprise ETL Server
Tools of SAS are :-
- SAS Information delivery portal.
- SAS data integration studio.
- Business Intelligence.
-SAS Enterprise Guide.
By using Aggregator transformation with first and last functions we can get first and last record.
Granularity , is the level of detail in which the fact table is describing, for example if we are making time analysis so the granularity maybe day based - month based or year based
he Latest Version is 7.2
informatica 8.0
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