KNIME: Getting Started¶
This week we focus on using the KNIME platform to implement a few basic data analysis workflows. KNIME is an open source analytics platform that provides a graphical interface and integrates with many other open source data analytics tools. From the creaters of KNIME:
Our KNIME Analytics Platform is the leading open solution for data-driven innovation, designed for discovering the potential hidden in data, mining for fresh insights, or predicting new futures. Organizations can take their collaboration, productivity and performance to the next level with a robust range of commercial extensions to our open source platform.
To begin, we cover getting up and running with KNIME by downloading and installing KNIME. Please visit https://www.knime.com/download to download KNIME and follow the instructions in the video below.
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from IPython.display import HTML
HTML('<iframe width="560" height="315" src="https://www.youtube.com/embed/yeHblDxakLk?rel=0&controls=0&showinfo=0" frameborder="0" allowfullscreen></iframe>')
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Installing Extensions¶
The extensions contain many useful additions to the KNIME platforms. For example, in the basic download we don’t have access to integrations with Python scripts. If we install the extensions, we will be able to utilize the Python Scripts extension and include Python scripts in our workflows.
[3]:
from IPython.display import HTML
HTML('<iframe width="560" height="315" src="https://www.youtube.com/embed/8HMx3mjJXiw?rel=0&controls=0&showinfo=0" frameborder="0" allowfullscreen></iframe>')
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