Recently i have been asked question like some one has done setting in their server that QV application will through timeout error after 60 minutes and an application which is having huge data sets and they dont want to do incremental load as data in tables changes so we cant really use incremental load
If this is a interview question then I am not sure what is the context this is asked. But if you have a huge volumes of data, the time out can happen.
Coming to the "not able to do incremental load because the table changes part", incremental load can update and delete record. There is something called direct query that can be used to fetch data directly from the data base but i would not advise that.
I guess one possible solution is doing data partition and reloading the whole set of partitioned data over time but like @pradosh_thakur said, incremental load techniques are quite flexible and you can implement it in almost every single scenario - you can even combine partitioned data with incremental load techniques.
By data partition I mean, in some cases, you can aggregate your data by a field or fields. The most common case is a Date field. So you can save your data like this: By Year Sales_2010.qvd Sales_2011.qvd ..... Sales_2019.qvd
By YearMonth Sales_201001.qvd Sales_201002.qvd ..... Sales_201902.qvd
By Category/YearMonth Sales_Local_201001.qvd Sales_Local_201002.qvd ..... Sales_Local_201902.qvd Sales_International_201902.qvd
This way, when you detect that something changed in your data, you can isolate which QVD to perform a full reload or incremental load - but again, that depends on your data structure and how it evolves over time.