KNIME – A Guide for Absolute Beginners: Learn data cleaning in a case study and learn how to do advanced data preparation with KNIME

Dan We

£7.99 ~~£37.99~~

5 (1 Ratings)

Video Jul 2021 2hrs 31mins 1st Edition

Dan We

£7.99 ~~£37.99~~

5 (1 Ratings)

Video Jul 2021 2hrs 31mins 1st Edition

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Key benefits

No coding required
Learn the basics and build a solid foundation during the case study
Learn how to prepare advanced data preparation with KNIME

Description

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. All the resources and supportive files for this course are available at https://github.com/PacktPublishing/KNIME-A-Guide-for-Absolute-Beginners

Who is this book for?

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.

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

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