Data Analytics with KNIME

Basic training (presence or live-online)
Mi., 14.05. - Do., 15.05.2025

Introduction to data analytics

• Motivation and characteristics of data-driven companies
• Terms relating to data science, data mining, data analytics and business intelligence
• Data-driven mindset: development and significance in production
• From data to insights
• Terminology and basics concepts of data analysis

Introduction to KNIME

• Basics of the KNIME Analytics platform
• Start, settings and options
• Overview of the graphical user interface
• Important functions
• Basic principle of nodes and visual workflows
• K-AI: KNIME Artifical Intelligence, Chatbot

Statistical basics

• Application of descriptive statistics
• Dependent/independent variables
• Scale levels
• Measures of position: mean, median and mode
• Measures of dispersion: variance and standard deviation, range and normal distribution
• Pitfalls in data analysis (e.g. causality vs. correlation)

Preparation of data

• Requirements for data quality
• Common data problems
• Data preparation
• Storytelling with data

Extract, Transform, Load (ETL) with KNIME

• Data import of machine data and other data
• Data check, detection of common data problems
• Merging data
• Data cleansing, measures for data preparation, text functions
• Data formats
• Table & workflow organization
• Data export and integration of other tools, e.g. Power BI
• Time and date formats
• Text functions

Reports and visualisations

• Visualization elements and best practices in dashboard design
• Use of different chart types
• Data visualisation with Java Script Nodes in KNIME

Outlook and Q&A session

• Data mining and process mining
• Automation with loop function
• Plug & play utilisation of existing workflows
• Expert tips
• Clarification of open questions

Learning transfer
Mi., 21.05. and Do., 29.05.2025 (2 times 0.5 days 09:00-12:30)

• Specific problems and questions from users related to the use of KNIME and the implementation of use cases are discussed and solved directly. 
• Participants receive intensive support and guidance during the practical exercises. They will also receive tips for implementation, and individual questions will be addressed.
• Specific questions are collected in the appointment's introductory training session, which the trainer prepares for, and then dealt with in the learning transfer units.