hi all
this is rather a more theoritical question than a practical one.when we import table defination as ODBC we specify the DSN,user name,password and table name.so the column defination is imported and stored in the repository.but there is an option to create the table in the database from DataStage interface.in such a case we specify the DDL and table is created.in that case no meta data is imported and stored in the repository.so how the engine works i could not understand.please guide me that is it mandatory to import everything before using that in the job??
we w dont import and manually specify the table definations what will be the problem.
importing ODBC
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Its not mandate to import the Table definition for the job to process. By importing the table definition, you are storing a copy of the layout in the Datastage metadata repository. So you can re use it, and will ease your job to specify the metadata for a large tables.
Impossible doesn't mean 'it is not possible' actually means... 'NOBODY HAS DONE IT SO FAR'
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When you click the GetSQLInfo button, or when you click the Create DDL button, the ODBC stage interrogates the data source for its syntax rules. This means that the table definition created is syntactically legitimate (most of the time - some drivers report inaccurately).
Whenever you generate metadata, it is recommended best practice to click Save on the Columns grid to store the table definition into the Repository. Change the category from Saved\StageName to ODBC\DSN ideally during the Save dialog, and remember to visit the Repository to add a short description to the saved table definition, so as to make life easier for future developers and maintainers.
Whenever you generate metadata, it is recommended best practice to click Save on the Columns grid to store the table definition into the Repository. Change the category from Saved\StageName to ODBC\DSN ideally during the Save dialog, and remember to visit the Repository to add a short description to the saved table definition, so as to make life easier for future developers and maintainers.
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Any contribution to this forum is my own opinion and does not necessarily reflect any position that IBM may hold.
Any contribution to this forum is my own opinion and does not necessarily reflect any position that IBM may hold.
Because it is one of Ray's patented Premium Posts.
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"You can never have too many knives" -- Logan Nine Fingers
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Search for Data Element will reveal more. A Data Element is like a luggage tag for data; you can record, for example, that this ten digit number is a tax ID, whereas this ten digit number is a telephone number and yet another is a part number. In short, business metadata.
Let's say you have a data element called Money. Then Usage Analysis can quickly show all the jobs (and Transforms) that process money.
With tools like IBM WebSphere Business Glossary now in the mix, I predict that the use of Data Elements to map business metadata to technical metadata, and therefore more rigorously to define business rules (including silly-sounding ones like preventing BI tools from presenting average telephone numbers) will be on the increase.
Let's say you have a data element called Money. Then Usage Analysis can quickly show all the jobs (and Transforms) that process money.
With tools like IBM WebSphere Business Glossary now in the mix, I predict that the use of Data Elements to map business metadata to technical metadata, and therefore more rigorously to define business rules (including silly-sounding ones like preventing BI tools from presenting average telephone numbers) will be on the increase.
IBM Software Services Group
Any contribution to this forum is my own opinion and does not necessarily reflect any position that IBM may hold.
Any contribution to this forum is my own opinion and does not necessarily reflect any position that IBM may hold.