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alexandros17
Partner - Champion III
Partner - Champion III

When I should use Direct Discovery?

Hi All,

could you give me some scenarios in which it is possible to use Direct Discovery?

Thanks

1 Solution

Accepted Solutions
Not applicable

Alessandro,

I can imagine that you set up such an architecture when you MUST do it: you cannot do another way. Because the performances are not as good as a standard application (certainly by far, as we got with H OLAP architectures in the past : part of the data was in the cubes, part was in the relational databases)

I would say you will use it:

- for real time data: like production process for example (you need to fetch the most up to date data)

- when you do not have the right to perform a partial load (access right)

- we can imagine also that the volume of data is too big. 90% of the business requests will be done on 20% of data stored in QV: you accept to fetch some data "outside" for a particular question in a particular sheet

I am interested much by the answers by other members.

Fabrice


View solution in original post

2 Replies
Not applicable

Alessandro,

I can imagine that you set up such an architecture when you MUST do it: you cannot do another way. Because the performances are not as good as a standard application (certainly by far, as we got with H OLAP architectures in the past : part of the data was in the cubes, part was in the relational databases)

I would say you will use it:

- for real time data: like production process for example (you need to fetch the most up to date data)

- when you do not have the right to perform a partial load (access right)

- we can imagine also that the volume of data is too big. 90% of the business requests will be done on 20% of data stored in QV: you accept to fetch some data "outside" for a particular question in a particular sheet

I am interested much by the answers by other members.

Fabrice


Anonymous
Not applicable

Adding some thoughts:

- Only one direct table is possible (at least in current version).  That means that the data model doesn't use fact table concatenated from multiple facts.  In case of multiple, you have to do it on the DB level (back to cubes).