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04.2_​ELT_​Usage

The company tracks the usage of the website and stores the information about each session.
- Various data are collected, e.g., session start, duration, # clicks, etc., as well as the session satisfaction score (optional)
- The company calculates averaged statistics for each customer, e.g., total # visits, average satisfaction, etc., and updates the "statistics" table on the database
- Session satisfaction score column has missing values which need to be imputed, e.g., with machine learning predictions.

We access the usage data from Hive and personal data (anonymized & updated in sessions 1 & 2) and contracts data from the PostgreSQL database. We perform in-database processing, read the data into Spark, enrich the usage data with the personal and contract data to predict missing values better, and continue working with the relatively big usage data on Spark. We export the final status of the workflow. In the case some processes fail, we notify responsible people via an automated email.


Transform Session 4 OrchestrationExercise 04.2 ELT Usage This workflow doesn't have any exercises. It already contains configured error handling and orchestration nodes. Their configuration is analogous to the configuration of the nodes in exercise 04.1_ETL_Customers.You can move to the exercise 04.3_Orchestration. There, you will trigger the execution of this workflow. NOTE. Parameters providedhere will be used during thisworkflow development andwill be ignored when thisworkflow is called from the04.3 Orchestration workflow.The parameters provided inthe caller workflow will beused instead.Status: failureImport parametersfrom the callerStatus: successTry (VariablePorts) Catch Errors(Var Ports) Variable Creator WorkflowService Input Variable Creator ParametersConfiguration Missing ValueImputation Access &Transformation Saving WorkflowService Output Transform Session 4 OrchestrationExercise 04.2 ELT Usage This workflow doesn't have any exercises. It already contains configured error handling and orchestration nodes. Their configuration is analogous to the configuration of the nodes in exercise 04.1_ETL_Customers.You can move to the exercise 04.3_Orchestration. There, you will trigger the execution of this workflow. NOTE. Parameters providedhere will be used during thisworkflow development andwill be ignored when thisworkflow is called from the04.3 Orchestration workflow.The parameters provided inthe caller workflow will beused instead.Status: failureImport parametersfrom the callerStatus: successTry (VariablePorts) Catch Errors(Var Ports) Variable Creator WorkflowService Input Variable Creator ParametersConfiguration Missing ValueImputation Access &Transformation Saving WorkflowService Output

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

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Created by: Lada.Rudnitckaia
Created at: 2021-09-30
On NodePit since: 2023-04-14
Last update: 2024-04-27
Created with KNIME version: v4.7.2
Tags: EducationData engineeringData engineerBest practicesSparkELT

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