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KNIME data cleaning challenges
Rating: 4.7 out of 5(15 ratings)
94 students

KNIME data cleaning challenges

Data cleansing with KNIME Data wrangling No coding ETL Tool Data preparation with KNIME
Created byDan We
Last updated 3/2025
English

What you'll learn

  • You improve your KNIME skills by solving data cleaning challenges
  • You learn and apply new KNIME nodes
  • You can transfer techniques you learn here to your own data problems
  • You continue your KNIME learning journey with me together

Course content

1 section • 16 lectures • 2h 45m total length

  • 1 What to expect here1:35

    Learn to tackle data cleaning challenges by applying data wrangling techniques to messy real-world data. Transfer knowledge to your own projects and have fun applying it while growing your skills.

  • Download the course resources here0:04
  • 3 Missing Project days data challenge17:38

    tackle a KNIME data cleaning challenge by generating complete date ranges per project, joining with costs, and filling gaps with the previous value using a loop and missing value steps.

  • 4 Splitting long text challenge13:59

    Explore splitting a long sentence into 100-character lines in KNIME data cleaning challenges by building a workflow with cell splitter, length, moving aggregation, and group by to concatenate lines.

  • 5 Approximate Match mapping challenge11:03
  • 6 Customer Weekday Weekend challenge16:13
  • 7 How to check for missing flow variables9:08
  • 8 Check available Info challenge12:41

    Explore the available information challenge in KNIME: read data, split by pipes, split comma-separated values into lists, remove brackets with regex, apply one-hot encoding, and group to show availability.

  • 9 Approximate Date Lookup challenge12:01
  • 10 Textprocessing string removal challenge11:25

    Explore a knime text processing challenge that removes target phrases from a source table using a dictionary replacer and entity-aware dictionary tagging to handle multi-word terms.

  • 11 keyword tagging challenge12:22
  • 12 misspelling_challenge12:25
  • 13 How to deal with date conversion issues12:08

    Learn to fix date conversion issues in knime by using string manipulation and regex to normalize date formats and convert them to dates with the string to date time node.

  • 14 Additional Video Molecule challenge21:54
  • Congratulations, thanks a lot and one favor to ask0:21
  • You want to learn more? Lets do it together0:55

Requirements

  • This course was requested by students and assumes prior knowledge with KNIME
  • If you have no prior knowledge with KNIME I highly recommend my KNIME - a crash course for beginners course first
  • no coding required
  • KNIME can be downloaded for free

Description

KNIME data cleaning challenges

The world of today and tomorrow is mainly driven by data. Companies need people with skills in data preparation and extraction.

Let's face it. Data is everywhere but it's messy. We spend hours and hours cleaning it using various tools (Excel, Python, R, ...)


What about spending less time, using a tool which requires no coding (allows it but does not require it!), which is fun to work with and has incredible data cleaning capabilities? That means, more fun and working faster!

This course is hands on and gives you the chance to learn and increase your skills in KNIME by facing data cleaning challenges

No matter if you are a business user working with data, a business user, a data analyst, data scientist or data engineer, KNIME is the right tool for you.


In this course we tackle various data cleaning examples and solve them together. The course was requested by students who wanted to see more hands on data challenges and assumes you have used KNIME before.

The goal is to learn KNIME nodes and concepts which can be transfered to your own data cleaning challenges.


If you have no prior knowledge then I highly recommend to take my  beginners course "KNIME - a crash course for beginners" first. There you learn all the basics in a complete case study to get you up to speed. Based on this knowledge you can improve your skills with this and my other KNIME courses you find here.


I am convinced the course content provides value and will help you in your daily work and / or future career in our data driven world.

Are you ready? Then let's go!

Who this course is for:

  • Data Analysts
  • Business Users
  • Data Scientists
  • Data Engineers

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