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IX - Anonmyizartion

Solution of the 9th JUST KNIME IT Challenge

Points to remember:The entire solution has been inspired from the KNIME solutionand it is not my own work, Problem Statement:You would like to post a question on the KNIME forum, but you have confidential data that you cannot share. In this challenge you will create a workflow whichremoves (or transforms) any columns that reveal anything confidential in your data (such as location, name, gender, etc.). After that, you should shuffle theremaining columns' rows such that each numeric column maintains its original statistical distribution but does not have a relationship with any other column.Rename these columns as well, such that in the end of your workflow they do not have any specific meaning. My Learning:Data AnonymizationNodes: Data Explorer, Target Shuffling, Table Difference Finder Filtering Out String ValuesNode 10Node 16Node 17Node 18 Column Filter Data Explorer Read Input-FIFA file Shuffing the columns- Anonymization Comparing Results Points to remember:The entire solution has been inspired from the KNIME solutionand it is not my own work, Problem Statement:You would like to post a question on the KNIME forum, but you have confidential data that you cannot share. In this challenge you will create a workflow whichremoves (or transforms) any columns that reveal anything confidential in your data (such as location, name, gender, etc.). After that, you should shuffle theremaining columns' rows such that each numeric column maintains its original statistical distribution but does not have a relationship with any other column.Rename these columns as well, such that in the end of your workflow they do not have any specific meaning. My Learning:Data AnonymizationNodes: Data Explorer, Target Shuffling, Table Difference Finder Filtering Out String ValuesNode 10Node 16Node 17Node 18 Column Filter Data Explorer Read Input-FIFA file Shuffing the columns- Anonymization Comparing Results

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