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KNIME for Microsoft Excel Users

Vu Hau by Vu Hau
January 8, 2023
in Business
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KNIME for Microsoft Excel Users
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KNIME for Microsoft Excel Users

Description

Contents

  • 1 Description
  • 2 Who this course is for:
  • 3 Requirements
  • 4 Download Links
    • 4.1 Related

You are an extensive Excel user?  You want to learn new and better ways of doing things with your data?

Then you are right here!

Let’s face it. Data cleaning is always a big hassle, especially if we are short on time and want to deliver crucial data analysis insights to our audience.

But how can we be more efficient in the ETL/ Data Prep process? How can this process be more FUN?

Meet KNIME!

A great tool which comes to our rescue. KNIME allows us to do data preparation / data cleaning in a very appealing drag and drop interface. (No coding experience is required yet it still allows us if we want to use languages like R, Python or Java. So, we can code if we want but don’t have to!). The flexibility of KNIME makes that happen.

In this course we lay the foundation for your successfull transition from Excel to KNIME

More specifically we learn

  • Reading and writing Excel data (file, files, sheet, sheets, locations, …)
  • Updating Excel sheets (append data, overwrite cells, …)
  • Covering KNIME‘s equivalent Excel Formulas (Vlookup, (Advanced) Filtering, …)
  • Formatting Excel Worksheets (Font, background color, borders

Further we will have an introduction to visualizations in KNIME

In particular

  • available visualization options
  • Required data shaping

Ready? Set! GO!

Who this course is for:

  • You want to transition from Excel to KNIME
  • You want to learn how to apply Excel formulas and logic in KNIME
  • You want to reduce the Excel stress and learn an alternative way to clean, transform and visualize your data

Requirements

  • I would encourage you to take my KNIME crashcourse for beginners first
  • KNIME can be installed for free

Last Updated 6/2022

Download Links

Direct Download

KNIME for Microsoft Excel Users.zip (2.3 GB) | Mirror

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