Hello friends,
I am in process of creating external Economic Data Mart as a part of one of our projects. So can any one give me the links to find the resources which may help me in this.

Thanx

economic data are usually time-series based, and are rates as well as levels. any given time series needs to exist at all levels of granularity, from, say, daily frequency down to annual frequency.
the language that handles economic data best would be EPS, or Econometric Programing System, invnted by Data Resources, now absorbed by McGrawHill or S&P; you might do a search for an econometric software program. Feature of an econometric language is the abiity to create a vector mapped by dates at one level of granularity, and then using the languages CONVERT fucntion, roll it up to a lower frequency (weekly to monthly) or distribute it down to higher frequency using some choice of algorithm. You can do it in Focus, but you'll have to do all the heavy lifting yourself.
For you, I would envison several data marts, each at a different level of granulariy, each mapped by a date keyfield, and each separated by having datasets that could be converted using a single agg/disagg method. EG, all of your weekly level data that used a STOCK method of aggregation would be in one datamart, and all that used, say, an AVG method would be in another datamart. You could have alllevels of gran in one focus db, just different segments...higher segments for lower levels of detail.
The way EPS worked, you set the frequency of your workspace, (ah remember workspaces?) and then the only data that was available to you was all data that existed at that frequency. pretty cool. But unf. the genius author of this language is no longer living, and i don't think the product is available anymore
Another thing to remember about econometric data is the priority of the MISSING value.
in focus : 6 + 4 + missing = 10;
in econometrics: 6 + 4 + missing = missing;
whole different mental approach. Missing data would mean be definition that your resultant value could not be relied upon, insufficient information.

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