Combine datasets using KNIME’s merging techniques, which include concatenation, lookups, and joins. These methods reduce manual errors and ensure consistent data preparation. You will learn to automate these workflows, saving time and effort.

Concatenation, Lookups, and Joins

Concatenate and Lookup tasks

Hands-on data merging in KNIME

Concatenating tables

Lookups with Dictionaries

Joining different data

Master aggregation and pivoting to summarize and restructure data for deeper insights. Explore advanced tools to manage multiple files, automate processes, and handle large datasets.

Introduction to Aggregating and Pivoting

Calculate the total sales with Row Aggregator

Aggregate data with GroupBy and Pivot nodes

Simple aggregations

Multi-level aggregations

Complex aggregations

Explore advanced tools to manage multiple files, automate processes, and handle large datasets.

Advanced data reading and writing with KNIME

Choosing the correct file writing node in KNIME

Hands-on advanced data reading and writing

Importing multiple CSV files

Writing data KNIME's .table

Transferring files

Advanced Data Reading and Writing

Use database operations to filter, join, and update data at the source to ensure speed and accuracy. Optimize your workflows, and keep your data ready for analysis and reporting.

Introductie tot databasebewerkingen in KNIME

Opties

DB Filter-node

DB Joiner-node

DB Reader-node

Gegevens bewerken in databases

Praktische databasetaken in KNIME

Verbinding maken met databases

Gegevens filteren in databases

Twee databasetabellen joinen

Terugschrijven naar databases

Gefeliciteerd!

Introduction to Database Operations

Exercises and Datasets

DataCamp vs. Local Experience

Ben je klaar om je dataworkflows te vernieuwen en handmatige, foutgevoelige taken te schrappen? Deze cursus is gemaakt voor professionals die datamanipulatie willen automatiseren met KNIME, ook zonder programmeerervaring. Je leert data uit meerdere bronnen samenvoegen en transformeren, inzichten samen te vatten met pivots, bestandsverwerking te stroomlijnen en efficiënt met databases te werken. Aan het einde kun je krachtige workflows bouwen die tijd besparen, de nauwkeurigheid verbeteren en de productiviteit verhogen. Perfect voor analisten, citizen data scientists en iedereen die met data werkt!


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    <p>In today’s fast-paced world, data professionals need tools to automate repetitive tasks and handle diverse datasets efficiently. KNIME provides a no-code platform to transform, analyze, and manage data seamlessly. This course is designed to empower you with practical KNIME skills, from basic data merging to advanced database operations, enabling you to enhance productivity and accuracy.</p>

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    <h2>Master data merging and aggregation</h2>

    <p>Start your journey by learning to merge datasets using concatenation, lookups, and joins. You’ll build workflows that ensure consistent and accurate data handling. Progress to aggregation techniques like pivots and groupings, unlocking valuable insights by restructuring and summarizing your data.</p>

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    <h2>Streamline file handling and database management</h2>

    <p>Dive into advanced data input and output workflows, including importing multiple files, automating file management with Utility nodes, and writing data in formats like Excel, CSV, and KNIME-native .table. Discover the power of database-level operations, such as filtering and joining, to process data with speed and precision.</p>

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    <h2>Build confidence in data automation</h2>

    <p>By the end of this course, you will advance your KNIME skills to confidently automate workflows, streamline data processes, and tackle complex datasets effectively. Whether you’re an analyst, citizen data scientist, or data engineer, this course provides the skills to boost productivity and easily uncover insights.</p>  

Data Transformation in KNIME

Optimaliseer datamanipulatie met KNIME: beheers samenvoegen, aggregatie, databaseworkflows en automatisering.

Datamanipulatie in KNIME

KNIME-basisprincipes

Haal alleen rijen op waar de afdeling "Marketing" is.

Filter medewerkers op basis van hun indiensttredingsdatum na 2020.

Combineer de employee- en payroll-tabellen met behulp van het employee ID.

Voeg klantbestelgegevens samen met verzendrecords op basis van het ordernummer.

Importeer geselecteerde data in KNIME voor verdere analyse.

Breng de gefilterde medewerkerstabel naar KNIME als gegevens tabel.

Gegevens bewerken in databases

Datamanipulatie in KNIME

Praktische interactieve oefening