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Time series guided analysis

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

Data Preparation Selecting parameters and filteringdata Data visualizations Seasonality inspection and datapreparation for modeling Model training and evaluation Problem statement: You are given 5 years of store-item sales data, and asked topredict 3 months of sales for 50 different items at 10 different stores.* We have taken 4 years of product sales dataset from kaggle which contanins historicalsales records of 10 stores and 50 products, from the year 2013 through 2017.* For the purpose of this task , we will only look at the sales of 'item' 1 from store 1.* you can deploy this to knime sever and use this workflow for a guided analyticforecasting* In knime analytics platform itself, you can click right on any component and click onInteractive view, to see dashborad view. on predictionson sales Return Seasonality Return Seasonality visualizationparameters select store select item Visualizations seasonality inspectionand data preparation model training model evaluation data preparation Data Preparation Selecting parameters and filteringdata Data visualizations Seasonality inspection and datapreparation for modeling Model training and evaluation Problem statement: You are given 5 years of store-item sales data, and asked topredict 3 months of sales for 50 different items at 10 different stores.* We have taken 4 years of product sales dataset from kaggle which contanins historicalsales records of 10 stores and 50 products, from the year 2013 through 2017.* For the purpose of this task , we will only look at the sales of 'item' 1 from store 1.* you can deploy this to knime sever and use this workflow for a guided analyticforecasting* In knime analytics platform itself, you can click right on any component and click onInteractive view, to see dashborad view. on predictionson sales Return Seasonality Return Seasonality visualizationparameters select store select item Visualizations seasonality inspectionand data preparation model training model evaluation data preparation

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Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: knoldus
Created at: 2020-07-12
On NodePit since: 2022-08-21
Last update: 2024-11-21
Created with KNIME version: v4.1.3
Tags: sales forecastingforecastingguided analyticsdashboradstore datalinear regressionknime

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