6 Replies Latest reply: May 3, 2016 4:54 PM by Altan Atabarut RSS

    Qlikview integration and modeling with R

    Harshad Borde

      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 ?
      8) 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,

        • Re: Qlikview integration and modeling with R
          Sinan Ozdemir

          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.

          • Re: Qlikview integration and modeling with R
            Altan Atabarut

            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...

            • Re: Qlikview integration and modeling with R
              Altan Atabarut

              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?

               

              8) 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...