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02. Data Manipulation - Solution

Data Manipulation - Solution

Solution to the exercise 2 for KNIME User Training
- Concatenate data from two different sources
- Bring values from a reference table to the actual table using the Cell Replacer node
- Modify String values
- Join data from multiple tables
- Remove duplicates in the data

Activity: Data Manipulation & Aggregation Activity II - Filter out duplicate rows - Make sure that all product names in the product data spreadsheet are writtenin lower case letters - Remove the column Sentiment Rating (Table Manipulator) - Calculate the mean age of the customers per product (GroupBy node) Activity I - Part 2 - Replace the written sentiment values with thenumeric sentiment scores Activity I - Part 1 - Concatenate web activity data from the old andnew systems Activity I - Part 3 - Join all data into one table using a series of joiner nodes(use "Customer Key" as the joining column) Numeric sentimentscoresCombine oldand new systemChange product valuesto lower caseWebActivity.sqliteWebActivityRemove duplicaterowsexclude Sentiment Ratingand Web ActivityOld Web DataSentiment Rating+Sentiment DescriptionDemographicsand Historyfrom SAS fileProducts<-> CustomerKeySentiment Evaluation from KNIMEAdd sentiment analysisAdd Demographics dataadd product dataMean customer ageper productRemove column SentimentRating Cell Replacer Concatenate String Manipulation SQLite Connector DB Reader DB Table Selector DuplicateRow Filter Column Filter CSV Reader CSV Reader CSV Reader Excel Reader Table Reader Joiner Joiner Joiner GroupBy Table Manipulator Activity: Data Manipulation & Aggregation Activity II - Filter out duplicate rows - Make sure that all product names in the product data spreadsheet are writtenin lower case letters - Remove the column Sentiment Rating (Table Manipulator) - Calculate the mean age of the customers per product (GroupBy node) Activity I - Part 2 - Replace the written sentiment values with thenumeric sentiment scores Activity I - Part 1 - Concatenate web activity data from the old andnew systems Activity I - Part 3 - Join all data into one table using a series of joiner nodes(use "Customer Key" as the joining column) Numeric sentimentscoresCombine oldand new systemChange product valuesto lower caseWebActivity.sqliteWebActivityRemove duplicaterowsexclude Sentiment Ratingand Web ActivityOld Web DataSentiment Rating+Sentiment DescriptionDemographicsand Historyfrom SAS fileProducts<-> CustomerKeySentiment Evaluation from KNIMEAdd sentiment analysisAdd Demographics dataadd product dataMean customer ageper productRemove column SentimentRating Cell Replacer Concatenate String Manipulation SQLite Connector DB Reader DB Table Selector DuplicateRow Filter Column Filter CSV Reader CSV Reader CSV Reader Excel Reader Table Reader Joiner Joiner Joiner GroupBy Table Manipulator

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