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. KNIME makes the data prep process efficient and easy. With KNIME, you can use the easy-to-use drag-and-drop interface, if you are not an experienced coder. But if you know how to work with languages such as R, Python, or Java, you can use them as well. This makes KNIME a truly flexible and versatile tool.
In this course, we start from the basics and learn KNIME in a (hopefully) fun and easy way by going through a case study together and prepare the data based on the requirements in the case study.
After completing our data prep, we will learn how to visualize data using tools such as Power BI and Tableau.
Finally, we also briefly cover the predictive analytics capabilities of KNIME and see how easy machine learning in KNIME can be.
By the end of this course, you will be able to use KNIME for data cleaning and data preparation without any code.
What You Will Learn
- Learn KNIME using a case study
- Prepare data in advance to visualize it later in tools such as Tableau or Power BI
- Extend your data analytics knowledge
- Perform simple to advanced ETL (Extraction - Transformation - Load)
- Clean and shape your data the way you need it
- Learn how to use machine learning/AI predictive analytics capabilities
This course is designed for aspiring data scientists and data analysts who want to work smarter, faster, and more efficiently. This course is also for anyone who wants to learn how to effectively clean data or encounter various data issues (for example, format) in the past and is looking for a solid solution. Note: Tableau Desktop and Microsoft Power BI Desktop are optional.
About The Author
Dan We: Daniel Weikert is a 33-year-old entrepreneur, data enthusiast, consultant, and trainer. He is a master’s degree holder certified in Power BI, Tableau, Alteryx (Core and Advanced), and KNIME (L1–L3).
He is currently working in the business intelligence field and helps companies and individuals obtain vital insights from their data to deliver long-term strategic growth and outpace their competitors.
He has a passion for learning and teaching. He is committed to supporting other people by offering them educational services and helping them accomplish their goals, gain expertise in their profession, or explore new careers.
Table of contents
Chapter 1 : Learn KNIME in a Fun and Easy Way - Through Solving a Case Study
- Welcome and Introduction
- Let Us Get Started with KNIME - the Interface
- Let Us Take a Look at Our Case Study Data
- Reading Data into KNIME - the Basics.
- Using Loops for Data Import - How to Be More Efficient in KNIME
- Data Cleaning and Saving Files with KNIME
- Webscraping in KNIME - Extracting Currency Exchange Rates from an API
- Joining and Cleaning Our Data in KNIME
- Final Data Cleaning and Preparation Steps for Visualizing Our Results
- Bonus - Saving the Data as a Hyper Format for Tableau
- Visualization - an Introduction on How to Visualize in Tableau or Power BI
- Predictive Analytics in KNIME - Machine Learning AI to Predict Customer Churn
- KNIME - Log Out and Final Words
- Title: KNIME – A Guide for Absolute Beginners
- Release date: July 2021
- Publisher(s): Packt Publishing
- ISBN: 9781801078108
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