Data Analytics with KNIME
KNIME Analytics Platform enables you to gain valuable insights by analyzing data and improving efficiency by automating repetitive data tasks, even without programming or special IT skills.The training has a modular structure and focuses on statistical basics, the use of the KNIME tool, and the topic of data preparation and data visualization in KNIME. KNIME is an open-source application for data analysis that can be used to automate data extract, transform, and load tasks, as well as sophisticated data analyses such as text mining, image processing, and machine learning intuitively and without programming knowledge. We will also show you how to link KNIME with other tools like Power BI. After the basic training, you will be supported in implementing practical applications in the form of learning transfers. Basics of low-code data analysis, data preparation and data visualizationIntuitive and productive handling of dataIntroduction and basics of KNIME Analytics PlatformStatistical & mathematical basicsPractical implementation of your use cases using so-called learning transfer sessionsAbility to make data-driven decisions & use data strategically
Basic training (presence or live-online)Di, 26.11.205 - Mi., 27.11.2025Introduction to data analyticsMotivation and characteristics of data-driven companiesTerms relating to data science, data mining, data analytics and business intelligenceData-driven mindset: development and significance in productionFrom data to insightsTerminology and basics concepts of data analysisIntroduction to KNIMEBasics of the KNIME Analytics platformStart, settings and optionsOverview of the graphical user interfaceImportant functionsBasic principle of nodes and visual workflowsK-AI: KNIME Artifical Intelligence, ChatbotStatistical basicsApplication of descriptive statisticsDependent/independent variablesScale levelsMeasures of position: mean, median and modeMeasures of dispersion: variance and standard deviation, range and normal distributionPitfalls in data analysis (e.g. causality vs. correlation)Preparation of dataRequirements for data qualityCommon data problemsData preparationStorytelling with dataExtract, Transform, Load (ETL) with KNIMEData import of machine data and other dataData check, detection of common data problemsMerging dataData cleansing, measures for data preparation, text functionsData formatsTable & workflow organizationData export and integration of other tools, e.g. Power BITime and date formatsText functionsReports and visualisationsVisualization elements and best practices in dashboard designUse of different chart typesData visualisation with Java Script Nodes in KNIMEOutlook and Q&A sessionData mining and process miningAutomation with loop functionPlug & play utilisation of existing workflowsExpert tipsClarification of open questions Learning transfer3.12. and 11.12.2025 (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.
| Veranstaltungs-Code | FB24-520649-60532648 |
