By Michael Berthold (KNIME). As first published in InfoWorld.
With new Integrated Deployment extensions, data scientists can capture entire KNIME workflows for automatic deployment to production or reuse
04 May 2020 — rs
I know you are still using Excel sheets to transform and/or analyze your data! I know, because most of us still use it to some extent. There is nothing wrong with using Excel. Excel spreadsheets are a great tool to collect and transform small amounts of data. However, when the game becomes harder and requires larger amounts of data, Excel starts showing its limitations.
27 Apr 2020 — Jeany 
Express Yourself!
All individuals are unique and so are our data needs. From simple csv files to REST APIs to Google’s BigQuery or using customized shared components, KNIME Analytics Platform offers many ways to access and analyze your data. Today, we will demonstrate how to access all of these aforementioned data sources through the use case of analyzing and annotating gene expression data.
06 Apr 2020 — Martyna
Accessing scientific datasets in Google Bigquery
The availability of scientific datasets in Google BigQuery opens new possibilities for the exploration and analysis of public life sciences data. Especially the Google Cloud Platform (GCP) provides a place where SQL queries can be easily and intuitively created in order to explore huge datasets extremely fast.
30 Mar 2020 — paolotamag 
Author: Paolo Tamagnini (KNIME)
One of the key challenges of utilizing supervised machine learning for real world use cases is that most algorithms and models require lots of data with quite a few specific requirements.
23 Mar 2020 — admin 
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Author: Martyna Pawletta (KNIME)
We are often asked if it’s possible to work with ontologies in KNIME Analytics Platform.
With “work with ontologies” people can mean many different things but let's focus today on one particular ontology and basic tasks including reading and querying ontologies to create an interactive tool at the end. For this purpose, today, we dive into the world of chemistry to use the ChEBI ontology (Chemical Entities of Biological Interest).
