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Time series guided analysis

Sales forecasting Forecasting Guided analytics Dashborad Store data
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In this workflow we have taken grocery dataset for 10 stores contains data for 50 different items. This workflow can be deployed for a guided analytics webportal, i.e. easy to use dashborad for time series inspecction and forecasting. Steps: * Data preparation: data loading, data exploration, data imputation * Selecting parameters and filtering data: selcting particular store, item , setting parameters for weekly/monthly stats visualizations * data visualizations: data inspection , weekly/monthly sales * seasonality inspection: seasionality inspection, seasonality removing, lag preparation * model training and evaluation: traing model on time series data, matics evaluation, line plot for performance

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.3
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.3

  • Go to item
    KNIME Expressions Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • Go to item
    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

  • Go to item
    KNIME JavaScript Views (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • Go to item
    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • Go to item
    KNIME Plotly Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.3

  • Go to item
    KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.3

  • Go to item
    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.3

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