KNIME for Beginners: No-Code Data Cleaning & ETL Case Study

Explore the Knime interface, create folders and workflows in local space, and build, configure, and run nodes in the workflow editor to manage data.

Explore knime's classic interface and the modern user interface, learn how to switch between them, access the knime explorer, use fuzzy search to find notes, and manage workflows.

Explore Knime through a hands-on case study by analyzing twelve csv transaction files, product and sales rep data, and region mappings, handling comma decimals and missing rows.

KNIME crash course teaches importing 12 Excel files, consolidating transactional and product data into one table, and enriching with web currency data for a case study.

KNIME course shows how to import 12 transaction csv files into one table using the csv reader node configured to read files in a folder with proper delimiter and filters.

Master loops in KNIME to read multiple files by iterating file paths with a list files and folders node, a loop start and end, and a variable-driven CSV reader.

In Knime, learn how to clean the sales area in the sales rep sheet with a region dictionary using a lookup, and save the cleaned data and transactions to disk.

Extract currency information from the ECB web feed, convert the XML to JSON, and pull the currency symbol and exchange rate using jsonpath, then save to an Excel file.

Explore cleaning in Knime by handling missing values with the missing value node, choosing string and number strategies, and filling the country column to produce a clean product info dataset.

Combine cleaned transactions with sales representative data using the joiner node, mapping region and product name to assign sales managers, and resolve numeric formats with string to number conversions.

Learn how to combine data in Knime using joined nodes to map country and product name, add list price and production cost, and export the result to a CSV.

Learn data transformation and cleaning with KNIME, removing duplicates and invalid quantities, calculating revenue, and joining USD exchange rates to prepare a final dataset for Power BI or Tableau.

Learn data cleaning and transformation in Knime, calculate profit, join exchange rates, convert to euro, and export a csv for bi visualization.

Learn how KNIME exports data to Tableau and Power BI by installing Tableau and Power BI extensions, using writer and server nodes, and publishing data sources to servers.

Explore visualizing cleaned Knime data in Power BI desktop, addressing decimal and currency formats with the local option, creating maps, bar and donut charts, and enabling interactive filtering.

Learn how to visualize data directly in KNIME with bar charts, configuring categories, sums, and profits, and explore interactivity, axes settings, and image export.

Learn to build a no-code machine learning workflow in KNIME to predict customer churn using training and validation data, a random forest model, and confusion matrix based evaluation.

Explore generative AI in Knime with built-in chi assistant after free signup. Learn to retrieve web data via the webpage retriever and XPath nodes, then filter columns and rows.

Learn how to switch between the classic user interface and the modern UI in KNIME version 5, and how to work in either interface as needed.

Start KNIME analytics platform version five by creating a workflow in your local space, using the node repository, and configuring and running nodes to build and monitor data.

Prepare the 2022 energy drink transaction data from CSV files, cover product details, regions, sales reps, and pricing, and learn data cleaning and region lookup before the case study.

Knime crash course for beginners teaches importing case study data into Knime using Excel reader and CSV reader, consolidating twelve monthly transactions with product info and managers, and data cleaning.

Discover KNIME loops for reading multiple data sources with list files and folders, table row to variable loop, and CSV reader, using a path flow variable.

Knime teaches cleaning the sales area and sales rep data by replacing abbreviations with region names via a region dictionary and value lookup, then saving via csv and excel writers.

Enrich data in Knime by fetching exchange rates with a get request, converting XML to JSON, extracting USD rate via JSON path, and exporting results to Excel.

Learn to join transaction data with cleaned sales reps in KNIME using the joiner, matching on sales area and product name to map sales managers.

Combine transactions with product information in KNIME using a join node and missing value handling. Enrich with sales manager and pricing details, then export to csv.

Learn how to join currency exchange data in knime, convert us dollar revenue to euros using the exchange rate, and save the results for visualization with a csv writer.

Learn how KNIME writes data to Tableau hyper format or to Tableau Server, and how to install and use Power BI and Tableau extensions.

Visualize cleaned KNIME data in Power BI by importing a CSV, using the Power Query editor, and creating bar charts and country maps of revenue by product.

Learn how to install the latest Table to PDF node in KNIME, resolve deprecation issues, and use KNIME hub or node pit to update and restart for the next video.

Learn to use the timer info in KNIME to measure execution times for nodes and the workflow, helping you identify bottlenecks and optimize performance.

Explore KNIME's breakpoint node and how it terminates a looped workflow when a file is empty, using list files and folders, variable loops, and transfer files to copy data.

Master KNIME's case switch start and end nodes, configure ports and flow variables, and build pivoted and calculated sales workflows using math formulas, single selection configuration, and grouping by product.

Explore how KNIME's empty table switch handles no data by routing flows to appropriate outputs, enabling conditional transfers only when the table contains data, and preventing partial workflow execution.

Learn to handle errors in KNIME with try catch nodes to continue workflows, using breakpoints to detect empty data and catch error ports for alternatives.

Explore the KNIME Java if table node, configuring data inputs and integer settings to switch between zero and one ports using equals and return logic.

Explore error handling in KNIME with try catch for API requests, using get requests to json placeholder and alternate results for failed URLs.

Learn to call another KNIME workflow inline using a table-based approach, supply a sample data table, and return transformed results to the original workflow.

Learn how to connect Knime to databases, using a SQLite example or generic DB connectors, select tables, and read data with DB Reader or DB Query Reader, enabling SQL queries.

Learn how to create and populate a SQLite database in KNIME using DB writer node, fetch latest tables, and read results with the DB table selector and DB reader.

Explore KNIME DB nodes to perform operations inside the database, compare DB group by with the normal group by node, and leverage the order node for efficient sorting.

Learn KNIME database operations using the db row filter, table selector, and db join nodes, with SQLite, conditions, like and wildcards, and data reading via db reader.