Automate Your Work with KNIME

Free up your creative energy – no more repetitive work in Excel. This 2-day hands-on course is designed to provide you with the knowledge necessary to automate MS Excel work using KNIME. Entirely visual with no programming required, KNIME allows users to visually create data flows, selectively execute some or all analysis steps, and later inspect the results, models, and interactive views.

Target Audience Anyone who works with MS Excel to produce reports and any other kind of repetitive task, including formulas, pivot tables, I/O from and to a variety of data sources. No technical knowledge prerequisites.

Content Introduction to KNIME. What is KNIME? Who uses it? What can we do with it? How does it compare to Excel? Installation and technical details. Demo. Hands-On KNIME Workflows. Reading and writing data from and to Text Files, Excel and Databases. Sorting, Columns Renaming. Filtering: Numerical, String and NULL filtering. Basic operations / Pivot tables / Text manipulation / File manipulation. Date/Time: Conversion, Field Extraction. Data quality: messy input data; implement basic and advanced verifications. Reproduce Excel’s V and HLookup. Implement joins across data sources. Workflow synchronisation / Automate send emails. Two case studies. Working with KNIME as a team. Node naming convention / KNIME Team Space / KNIME Server / Metanodes.

Practical info (e.g., cost) | Download flyer (pdf) en | Dates of our scheduled courses

KNIME Analytics Platform

This 2-day hands-on course provides an introduction to KNIME, the opportunity to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows.

Learn everything you need to get going – from installation, to navigating around the various sections, through to fully utilizing KNIME Analytics Platform.

Target Audience This course is designed primarily for those who have little to no previous experience with KNIME but is also useful for those who simply want to fine tune their knowledge.

Content Introduction to KNIME / Reading Data / Data Manipulation / Data Visualisation / Data Mining / Exporting & Deployment / Workflow Control / External Tools / Model Selection / Advanced Applications

Practical info (e.g., cost) | Download flyer (pdf) en | Dates of our scheduled courses

KNIME Server

This 1-day, hands-on course dives into the details of KNIME Server and Knime WebPortal. Learn how to exchange workflows and data between the server and the client, how to take advantage of the many server dedicated nodes and features when implementing a workflow, how to set access rights on workflows, data, and meta-nodes, share meta-nodes, execute workflows remotely and from the KNIME WebPortal, how to schedule report and workflow executions, and more.

Target Audience The course is designed for anyone interested in finding out more about the KNIME commercial platform and its functionalities.

Content KNIME product overview / Roles (Personas) involved in a data science project / Introduction to the use case / KNIME Server basic features / KNIME server advanced features / Summary and Q&A session

Practical info (e.g., cost) | Download flyer (pdf) en | Dates of our scheduled courses

Text Mining with KNIME

This 1-day, hands-on course focuses on the processing and mining of textual data with KNIME using the Text processing extension. Learn how to read textual data in KNIME, enrich it semantically, preprocess, and transform it into numerical data, and finally cluster it, visualise it, or build predictive models.

Target Audience The course is designed for people with basic knowledge of the KNIME Analytics Platform. Experience with text mining is not necessarily required.

Content Introduction to KNIME / Reading and importing textual data / Text pre-processing, semantic enrichment, and transformation / Text classification / Visualisation / Text clustering

Practical info (e.g., cost) | Download flyer (pdf) en | Dates of our scheduled courses

Practical Information

All courses can be customized to fit your skill level, goals, and schedule. For each course listed above, the following applies:

Price

CHF 990.– per person per day excl. VAT. Price varies depending on number of days and participants. Please enquire directly.

Language

Available in English and German.

Location & Duration

At our facilities in Zürich or at your company’s site. Sessions can be full or half days.

Anomaly Detection

Anomaly detection predicts when critical equipment parts will go bad – preventing failures and downtime.

Maintenance is a tricky business: you’re always treading that fine line between cost optimization and risk of equipment malfunction – with potentially catastrophic consequences.

Even modern predictive maintenance techniques benefit from data analytics: by knowing when the readings from sensors on critical machinery components are anomalous, failures can be predicted with enough lead time to take cost effective remedial action…

Competitive Pricing

Guided analytics provided automated pricing insights and suggestions for achieving the optimal price.

Great pricing decisions are critical for every company. A key input into pricing decisions is benchmarking against competitors using market research data. However, to be actionable on that data, one must be able to identify key competitors to review related pricing indexes and performance. In many companies there is a large range of products that need to be priced. Therefore, providing automated pricing insights and suggestions can be game changing.

This story demonstrates how a Guided Analytics Pricing Application assists analysts on various levels. Firstly, it automatically identifies key competitors based on pricing. Secondly, the selected baseline product can be benchmarked against these competitors to establish an understanding of its relation to the trade channel and market. A key industry performance metric is the price index – the competitor’s price compared to the…

Guided Analytics

Understanding customer satisfaction with text mining reviews and Net Promoter Scores (NPS).

The NPS, together with satisfaction ratings of customer touchpoints, is part of Customer Experience Management (CEM) in many companies. The NPS is not only used to evaluate customer satisfaction, but also to understand what pain points should be eliminated. By combining insights from sentiment and NPS score analysis, the CEM team can make better decisions when allocating resources to solve specific issues.

This story demonstrates how a Guided Analytics Customer Satisfaction Application enables the CEM team and other analysts to understand customer sentiment. The data science team creates a KNIME workflow using KNIME Analytics Platform and deploys it to KNIME Server. Analysts are then able to interact with various touchpoints and…

Guided Analytics

Customer Segmentation: Combining Data Science and Business Expertise.

In this white paper, you will learn how to:
Create a Customer Segmentation analytics heart

Create a Web User Interface to inject business experts’ knowledge into the final results

IoT

Big data, Smart Energy, and Predictive Analytics: This whitepaper focuses on smart energy data from the Irish Smart Energy Trials.

The first goal is to identify a few groups with common electricity behavior to create customized contract offers. The second goal is a reliable prediction of the overall energy consumption using time series prediction techniques.

Text Processing

An introduction to KNIME’s text processing feature.

This technical report explains the fundamentals of text processing feature in KNIME along with detailed descriptions and examples of all key node categories.

KNIME Workflow for Beginners

Cheat Sheet

This cheat sheet covers everything a beginner needs to know – from reading in data, to data exploration and transformation, through to analyzing and deployment.

Accesing your data in KNIME

Cheat Sheet

This cheat sheet covers everything you need to access your data and to bring it into the desired shape.