KNIME for Microsoft Excel Users

Learn how KNIME switches between the classic interface and the new modern interface in version five, so you can use either view and build workflows with confidence.

Learn to read all sheets from multiple Excel workbooks in Knime using a list files and folders node, read Excel sheet names, and nested loops that iterate files and sheets.

Learn to update specific cells in an Excel file with Knime using the Excel cell updater and table creator. Specify cell addresses like a6 or c6 and data types.

Learn how to perform vlookup or index match in knime using value lookup or joiner, including mapping region abbreviations to full names via a region dictionary.

Explore knime's joiner to perform vlookup with multiple criteria, mapping sales managers by sales area and product name, and drop duplicates with the duplicate row filter.

Explore nominal value row filter and table indexer with index query in KNIME, learn extension installation, and apply multi-country filtering (Germany, Italy, Netherlands) efficiently.

Learn how to pivot and unpivot data in KNIME by using the pivot and unpivot nodes, reshaping tables with grouping, pivots, and aggregations like sum and mean.

Master sorting columns and rows in KNIME, rename columns, and perform multiple transformations in one table manipulator node, with tips on missing values and column order for Excel outputs.

Learn to use KNIME's math formula node to perform numerical operations, create a sales column by multiplying quantity and price paid, and compute totals and percentages.

Learn to read data from multiple Excel sheets with different structures in KNIME, using sheet names, loops, and the column merger to merge columns into one table.

Explore KNIME visualization options, including built-in view nodes and extensions for Power BI and Tableau, and publish datasets to Power BI service or Tableau server.

Learn to read data from Excel into KNIME using an Excel reader, configure sheet selection by name or index, and preview headers and types.

Learn how to read all sheets from an Excel workbook into KNIME by looping through sheet names, configuring the Excel reader with file path and sheet variable, and appending results.

Learn to read multiple excel files from a folder in knime using the excel reader in folder mode, with file filters and first-sheet selection.

Learn to read multiple Excel workbooks with multiple sheets in KNIME by listing folder files, looping over files and sheets, and combining all data into one table.

Learn how KNIME connects to online sources like SharePoint and S3 and authenticates to read data. Read Excel files from SharePoint Online and S3 using the appropriate connectors.

Update specific excel cells with KNIME using the excel cell updater, by building an update table with address, string and integer fields, then save as a new file or overwrite.

Master vlookup and index match in KNIME with two methods: cell replacer and join, using a region dictionary to align abbreviations with full region names.

Learn to filter rows in KNIME using row filter, regular expression, and rule-based filters. Leverage country and product criteria to select Germany, Netherlands, Italy, and Red Bull.

Learn to convert data types in KNIME by configuring type per column and using string to date time notes to enable date transformations, such as for the order date.

Explore sorting and renaming columns in KNIME with column result, column rename, and the table manipulator. Learn to sort rows, handle missing values, and export to Excel or Tableau.

KNIME for Microsoft Excel users teaches building math formulas to compute revenue after numeric conversion by multiplying quantity and price, then aggregating by product and calculating percentage of total sales.

Learn to read multiple Excel sheets in KNIME and combine tables with different structures using the Excel reader, loop over sheets, and align columns with a column merger.

Apply Excel formatting in KNIME by installing the Excel notes extension, mapping cell ranges, and applying font and background color to headers and data, then export to Excel.

KNIME offers various charts including bar charts, box plots, heatmaps, histograms, and pie and donut charts, and shows how to configure them with aggregation, sorting, and data shaping.

Use Knime to visualize geographic data by coloring by metro code with the color manager and plotting latitude and longitude on a map, filtered to California.

Learn to create and apply an Excel template, set header colors and formats (bold, date, italic, underline), and write data back into the template via the right to Excel template.

In KNIME for Excel users, derive a month-column table from date ranges by looping over rows, extracting months, and pivoting to headers, marking present months with 1s.

Apply a customer-challenge workflow in Knime using an Excel Reader to unpivot date columns. Use lag comparisons and a Rule Engine to detect gains and losses, then pivot results.

Explore KNIME's lookup and comparison challenge by joining two Excel sheets with a left outer join, using group loop and lag variables to align values, and rename columns with regex.

Build a Knime workflow to create monthly validation periods from start and end dates, using date time range, extract date fields, pivot, and column append to show monthly validity.

Leverage KNIME's filtering techniques to match descriptions against wildcard criteria using dot star patterns. Use a pre-built component to quickly filter items like papaya or wood.

Use KNIME to filter suppliers by requiring all boolean columns in time, budget, and positive experience to be true, then join results to identify the best supplier.

Learn to solve the what is missing challenge in KNIME by using column aggregator, cross join, and ungroup to identify missing fruits and map them back to input rows.

Learn how to restart a counter for each group in KNIME when names repeat, using row ID based identifiers, the rule engine, and a group loop with counter generation.

Learn to clean misspelled names with KNIME by applying fuzzy matching using similarity search with Levenshtein distance, and a helper counter to map to correct retailer names.

Explore approximate grouping in KNIME by using string distances and a levenstein distance measure, build a distance matrix, apply hierarchical clustering, and assign clusters with a distance threshold.