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Qlikview integration and modeling with R

Hello Guys,

Before implementing Qlik - R integration, In my organization i need to get clarified few of my doubts. I am posting few questions, to get clear idea. I am a manager with exposure to Qlikview , not R.

Flow of the data will be like Database --> Qlikview (Real time) --> R (modeling ) --> Qlikview .

1) What is the cost : servers, licences, connectors, resources, hardware ...
2) Can it be instantly predictive ?
3) Is it used anywhere for commesial modeling ?
4) I want to have auto-made models, as well as designed-by-me models, as well as imporrted models. Is it possible ?
5) I want to version my models, and version my sets of data. We could say that I want to apply any model on any data set
6) What will happen when my model will change (every 6 month about). Do I have to redesign the data set ?
7) If i redesign the data set, will i be able to run a new model on a previous data sets. Yes or no, depending on what ?
😎 Can I tag some data sets, subsets, ...Can I add some comments , share my data sets with my colleagues for trainig or testing purposes ?
9) If I want to use SPSS with Qlikview , is it advisable ?

10) Do I need different data sets for different predictions (early claims, fraudulent claims ....)
11) Can i get some dashboard to measure the efficiency of my models (before / after)
12)  What is the limit of the system : number of variables, size of the data, ....


Thanks,

6 Replies
sinanozdemir
Specialist III
Specialist III

Hi,

I am not sure if you have already checked out the below link:

QlikView and R Integration for Predictive Analy... | Qlik Community

Hope this helps.

Not applicable
Author

Most of the consultancy firms use Alteryx and Qlik hand in hand just for this purpose.

For self-services analytics Qlik requires a lot of code writing.

An easy approach is to utilize Alteryx predictive capabilities is to get the Alteryx Starter Kit for QlikView...

Not applicable
Author

Also check out; Qlik | Alteryx

Kushal_Chawda

Not applicable
Author

Hi sinanozdemir‌  kush141087

Is this integration process possible on enterprise level ? I am having very large and dyanamic datasets which are updated in real time . Is there is limit of this system like in terms of number of variables and size of data?

Thanks

Not applicable
Author

I would normally expect the flow to be;

Database --> Alteryx workflows for data blending and R based predictions/estimations/clustering --> Alteryx based scoring (scheduled to be updated/rerun in a few moments or for each trigger) --> Discover your data in Qlik (Real time)

1) What is the cost : servers, licenses, connectors, resources, hardware...

  • 50K USD Server or if it's a small deployment 5K USD for scheduling, 5K USD per designer licenses...

2) Can it be instantly predictive?

  • It may learn near-real-time with new performance data being added...
  • it can definitely score real-time

3) Is it used anywhere for commercial modeling?

  • Alteryx is used by several well known financial institutions, banks, insurance firms, management consultancies
  • Pure R may be used as well... But you'll need exceptional experience with that..

4) I want to have auto-made models, as well as designed-by-me models, as well as imported models. Is it possible ?

  • Data preparation and target definitions should be made by you
  • Several modeling techniques are almost like automatic and error prone(like random forest)

5) I want to version my models, and version my sets of data. We could say that I want to apply any model on any data set.

  • "Applying any model on any data set" is a little bit too vague and does not sound so wise...

6) What will happen when my model will change (every 6 month about). Do I have to redesign the data set ?

  • May not need to redesign the data set... especially if hypothesis, observation and performance periods are not changed.
  • Calibrating models will fix the weightings accordingly, you can calibrate more frequently and it's probably is better to do so...

7) If i redesign the data set, will i be able to run a new model on a previous data sets. Yes or no, depending on what?

😎 Can I tag some data sets, subsets, ...Can I add some comments , share my data sets with my colleagues for training or testing purposes?

  • Yes in alteryx and some in SAS and SPSS

9) If I want to use SPSS with Qlikview, is it advisable?

  • Possible

10) Do I need different data sets for different predictions (early claims, fraudulent claims ....)

  • You may need a data set with a totally different attribute set
  • Should design it according to your business

11) Can i get some dashboard to measure the efficiency of my models (before / after)

  • Tracking the current gini and trend of predictive power for classification models would be wise
  • RMSE or similar for regression
  • CCC for clustering etc...

12)  What is the limit of the system : number of variables, size of the data, ....

  • For the row size, 20K rows is something like a statistical limit. may not matter much if you add more...
  • For the number of variables, finding more of orthogonal (uncorrelated in between) variables is always a good thing... but most models will use a small number of very effective/valuable key attributes... top 50 variable will most likely do...