Book Image

KNIME Essentials

By : Gábor Bakos
Book Image

KNIME Essentials

By: Gábor Bakos

Overview of this book

KNIME is an open source data analytics, reporting, and integration platform, which allows you to analyze a small or large amount of data without having to reach out to programming languages like R. "KNIME Essentials" teaches you all you need to know to start processing your first data sets using KNIME. It covers topics like installation, data processing, and data visualization including the KNIME reporting features. Data processing forms a fundamental part of KNIME, and KNIME Essentials ensures that you are fully comfortable with this aspect of KNIME before showing you how to visualize this data and generate reports. "KNIME Essentials" guides you through the process of the installation of KNIME through to the generation of reports based on data. The main parts between these two phases are the data processing and the visualization. The KNIME variants of data analysis concepts are introduced, and after the configuration and installation description comes the data processing which has many options to convert or extend it. Visualization makes it easier to get an overview for parts of the data, while reporting offers a way to summarize them in a nice way.
Table of Contents (11 chapters)

Using HiLite


There is no direct option to handle the HiLite information within the report, but you can easily work around this.

First, you can add a new table where you have the highlighted rows filtered by the HiLite Filter node. This way, you need to use this other table to signal (for example, with highlights) what was "HiLited". This has an advantage, in that it does not require manual steps, but it might be a good idea to add a new column to the result and rejoin it with the original table before sending the data to the report editor.

Another option is using Interactive HiLite Collector. Its output can contain different information based on different groups. So in the reporting data, you can choose between multiple visualizations; you can even combine them. The drawback is that it requires to be set manually after each reset of the node with the same column names/values.