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08_​Database_​Jam_​Session

Database Jam Session
This workflow jams on data from six databases, i.e MySQL, MongoDB, MS SQL Server, MariaDB, Oracle,PostgreSQL.The use case is a Next Best Offer, modeling the likelihood of a customer to buy a second product. Insert Credentials Connect to DB, Select Table, Import Data MySQL MongoDB MS SQL Server MariaDB Oracle PostgreSQL Build and Evaluate predictive model Goal: predict variable "Target" Measure Input Feature Influence Append mapranking numberData fromold + new systemOld Web datainto WebActivitydeduplicatelowercase(products)70% vs. 30%CustomerKeyby influencesum(# splits) /sum(# candidates)level 0, 1, 2CustomerDemographicsSentiment mapPostgreSQLCustomerProductsMS SQL ServerSentiment evaluationMySQLOld Web SystemOracleMariaDBTargettrain onTargetMongoDBNew Web Systemon CustomerKeyon CustomerKeyon CustomerKeyCompare Targetwith predictionBackward FeatureElimination Cell Replacer Concatenate Column Rename GroupBy String Manipulation JSON to Table Partitioning Double To Int Sorter Math Formula DB Table Selector DB Reader DB Table Selector DB Reader PostgreSQLConnector DB Table Selector DB Reader Microsoft SQLServer Connector DB Table Selector DB Reader MySQL Connector DB Table Selector DB Reader Oracle Connector DB Connector MySQL MS SQL Server Maria DB Oracle PostgreSQL Number To String Random ForestLearner Random ForestPredictor MongoDB MongoDB Connector MongoDB Reader Joiner Joiner Joiner Scorer This workflow jams on data from six databases, i.e MySQL, MongoDB, MS SQL Server, MariaDB, Oracle,PostgreSQL.The use case is a Next Best Offer, modeling the likelihood of a customer to buy a second product. Insert Credentials Connect to DB, Select Table, Import Data MySQL MongoDB MS SQL Server MariaDB Oracle PostgreSQL Build and Evaluate predictive model Goal: predict variable "Target" Measure Input Feature Influence Append mapranking numberData fromold + new systemOld Web datainto WebActivitydeduplicatelowercase(products)70% vs. 30%CustomerKeyby influencesum(# splits) /sum(# candidates)level 0, 1, 2CustomerDemographicsSentiment mapPostgreSQLCustomerProductsMS SQL ServerSentiment evaluationMySQLOld Web SystemOracleMariaDBTargettrain onTargetMongoDBNew Web Systemon CustomerKeyon CustomerKeyon CustomerKeyCompare Targetwith predictionBackward FeatureElimination Cell Replacer Concatenate Column Rename GroupBy String Manipulation JSON to Table Partitioning Double To Int Sorter Math Formula DB Table Selector DB Reader DB Table Selector DB Reader PostgreSQLConnector DB Table Selector DB Reader Microsoft SQLServer Connector DB Table Selector DB Reader MySQL Connector DB Table Selector DB Reader Oracle Connector DB Connector MySQL MS SQL Server Maria DB Oracle PostgreSQL Number To String Random ForestLearner Random ForestPredictor MongoDB MongoDB Connector MongoDB Reader Joiner Joiner Joiner Scorer

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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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On NodePit since: 2019-07-12
Last update: 2024-04-26
Created with KNIME version: v4.5.1
Tags: databasecredentialsMySQLMongoDBOracleMariaDBPostgreSQLMS SQL Serverwill they blendonboardingdata engineering

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