mithunmca

 Profile Answers by mithunmca 

• Mar 28th, 2007

 

 ODS :-Operational Data Store which contains data .
           ods comes after the staging area
eg:-
       In  our e.g lets consider that we have day level Granularity in the OLTP & Year level Granularity in the Data warehouse.
        If  the business(manager) asks for  week level Granularity then we have to go to the oltp and summarize  the day level to the week level which would be pain taking.So wat we do is that we maintain  week level Granularity in the ods for the data,for  abt  30 to 90 days.

Note : Ods information would contain cleansed data only. ie after staging area

Staging Area :-
                        It comes after the etl has finished.Staging Area consists of
                        1.Meta Data .
                        2.The  work area where we apply our complex business rules.
                        3.Hold the data and do calculations.
In other words we can say that its a temp work area.

siraj khan

• Aug 9th, 2007

 

The full form of ODS is Operational Data Store.ODS is a layer between the source and target databases..ODS is used to store the recent data.

Staging layer is also a layer between the source and target databases..Staging layer is used for cleansing purpose and store the data periodically. 

Vamshidhar

 Profile Answers by Vamshidhar 

• Jan 9th, 2009

 

ODS (Operational Data Source) is the first point in the Datawarehouse. Its store the real time data of daily transactions as the first instance of Date.

Staging Area, is the later part which comes after the ODS. Here the Data is cleansed and temporarily stored before loaded into the Datawarehouse.

ram

• Jun 11th, 2013

 

Yes, ODS is a Open Data Source where it contains real time data (because we should apply any changes on real time data right..!) so dump the real time data into ODS called Landing area later we get the data into staging area here is the place where we do all transformation.

Poomari Manoharan

• Jul 2nd, 2014

 

ODS is nothing but the Operational Data Store which holds the data when the business gets started. It means , it holds the history of data till yesterdays data(depends upon customer requirement). Sometimes, it holds the real time data also.

Staging is the area before ODS which holds only 15 / 30 / 45 / 90 days data based on customer requirement. In some of the project , staging is used as Pre-Production data. That depends.

Hope this might be helpful

Shraddha Goel

• Feb 18th, 2016

 

ODS comes before Staging.

Sirisha d

 Profile Answers by Sirisha d 

• Jan 30th, 2017

 

Staging area can be considered as a copy of the source .
Staging area contains exact copy of source data from which we can pull data to build a data warehouse or ODS by applying business rules and transformations and by integrating data.
ODS is operational Data Store, which contains integrated data with the table structures almost similar to source structures.
ODS contains more real time data.
The ODS load will be very frequent depending on the requirement compared to data warehouse load.
ODS holds data starting from the time of point of load and to a certain period of history (may be 30days/ 90days..) depending on business requirement.

Ankush

• May 17th, 2017

 

You mentioned ODS comes after staging area is not true i guess. Flow is like ODS->staging->DWH as per my knowledge. Kindly correct me if wrong.

Rajesh

• Aug 22nd, 2022

 

ODS is mainly used to integrate the data of different Sources having same functionality of the data into one integrated model. This model is mostly denormalized and will not be useful for reporting. Ex., To an educational agency, the student information, course, tuition information will be provided by different institution affiliated to that Agency/university. Not all the source files will be of same layout, but will have relevant data. A workforce technical college will have different level of Student info compared a regular 4 years college. The idea of ODS is to pull the data from all those institution file, collect them integrate them and make them to be useful for the next layer. PII information of a student can come from multiple files from a institution. de-identify them. integrate them so that EDW layer will not goto multiple files to pull the same info.