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QlikView R Connector

QlikView R connector allows users to enhance QlikView experience with professional R project analytics. Seamless integration of Qlikview and R project allows users to perform complex calculations for planning and forecasting, and track patterns in analyzed data in QlikView itself. 

QlikView has the function of statistical analysis. But in most cases, it is not enough for making business decisions related to forcasting, since:  

  • Time series forecasting - a separate class of algorithms, which is selected by an expert according to the analyzed domain
  • For these purposes there are specialized statistical packages for statistical analysis and forecasting of time series on the market. For example, Statistica, ForecastPro, SPSS, and widely used Open Source project of R-Project.

QlikView R Connector is used for seamless integration of Qlikview and R projec, which allows users to perform complex calculations for planning and forecasting, and track patterns in analyzed data in QlikView itself. 

In R Connector for QlikView the following forecasting types are available:

  • econometric,
  • regression,
  • Box-Jenkins techniques, 
  • neural networks with the same regression
  • GRNN, etc. 

Project's calculating results, which are transmitted in QlikView, are a collection of a large number of statistical indicators:

  • smoothed historical data
  • forecast
  • confidence scores
  • mean-square error

QlikView and R-Project integration through QlikView R Connector allows quickly and efficiently build forecasts  in the hierarchy of goods, using the methodology of Bottom-up forecasting and top-down forecasting.

For ergonomic work, the analysis for time series forecasting is available in two modes:

  • batch forecast in the process of restarting the overall data that runs on a schedule for QlikView Server
  • interactive mode of forecast building. This mode allows the analyst to choose the available prediction methods, establish the required parameters and carry out a quantitative and qualitative evaluation of the results in on-line mode

 R Connector for QlikView advantages for business users:

  • Enhanced analytics. R Project enhances QlikView analytics with complex forecasting. With R Connector for QlikView you’ll be able to perform all types of statistical analysis: factorial, descriptive, regression, etc.
  • Unified interface. QlikView analytics and R Project forecasts are displayed in unified ergonomic QlikView interface.
  • Built-in or on-demand forecasts. With R Connector for QlikView users can choose their own forecasting approach. Prognostic calculations will be built in the QlikView application and calculated automatically; or users will make their own selection manually and will get the R system forecast in QlikView.
  • Responsive forecasts. Multilayer calculations take very little time due to ‘in-memory’ database and computational strength of matrix algebra

R Connector for QlikView advantages for technical users:

  • Seamless integration of QlikView and R Project.
  • Built-in tools for an easy and effective dynamic update of QlikView documents.
  • Debugging and logging tools. These tools are particularly important when R connector is set to automatic update of QlikView documents from its server.
  • Ability to develop macros in QlikView with the use of both VBS-scripting and R Language (A Computer Language for Statistical Data Analysis)
  • Ability to leverage the power of application libraries from different areas (time series analysis and forecasting, regression and cluster analysis, econometrics, etc.)
  • High level of performance and productivity.

 

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Clients

  • Karavay

     

    Analysis of the shipments and payments to the clients; plan vs. actual analysis of sales; visualization and marking the items on the map

  • http://www.vimos.ru

    Financial and corporate reporting; plan vs. actual analysis, forecast of the plan

  • Analysis of sales based on the principle "from the general to the particular"; assessing customers' sales compliance with the "ideal matrix"; analysis of the effectiveness of warehouse management, plan vs. actual analysis, implementation models to predict sales and purchases.

  • Macro Group

    Analysis of the effectiveness of customer service department, analysis of the the effectiveness of the procurement department, analysis of the effectiveness and quality of suppliers, analysis of internal and external logistics, analysis of key performance indicators, visualization of financial flows within the group of companies, analysis of  accounts receivable / payable management, analysis of the effectiveness of warehouse management.

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