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KNIME: End to end data science for better decision making

Open source and free to use software to create and productionize data science using one easy and intuitive environment, enabling every stakeholder in the data science process to focus on what they do best.


KNIME’s visual programming environment makes data analytics accessible to people who don’t have coding or scripting backgrounds. In a data-driven culture, this is essential because non-experts can independently use the available data, enhance control procedures, and turn insights into business value.


It does take time to learn KNIME and basic data analysis skills are required to build workflows. It takes approximately 10 hours to get familiar with the workbench and 100-200 hours to become confident in building workflows. However, the time investment has significant rewards and is worth it. Using KNIME saves time.

Workflows are reusable and shareable, which reduces the need to recreate them from scratch for every single project. Repeated steps such as mundane pre-processing tasks can be captured as a component and used in other workflows or by other colleagues. Configuration changes can also be programmed to update across all components if needed – guaranteeing consistency in business processes. All KNIME workflows are self-documenting, meaning knowledge is stored in the workflow itself and not in the mind of an employee. Not everyone has to become a KNIME specialist, but with basic knowledge, even non-technical employees can contribute meaningfully to data analytics.

Efficiency gains by automating Top 10 sales reports with KNIME

KNIME as a free no-code/low-code platform offers many possibilities, but a simple use case for more efficiency is the automation of Top 10 reports, which are otherwise often still made manually on a daily, weekly or monthly basis, for example with Excel.

In this example, both the Category Manager and Country Manager automatically receive a personalized email with a Top 10 products per product category or country after a run of 30 seconds. They don't have to download or look up anything themselves, but receive it immediately in their inbox.

KNIME can directly access various on-premise and cloud databases, such as SQL Server, Amazon or Snowflake, but in this example sales figures are read from Excel. Then the desired period and required columns are selected:

  • sales date for monthly, weekly or daily reports

  • article number and article name

  • product category

  • country or sales region

  • turnover, margin or profit

Workflows in KNIME are easy to interpret and well documented, making adjustments easy to make. This makes it easy to expand this workflow with, for example, the most important customers per country or the best performing employees per branch. The challenge is therefore more to unlock the right data sources than to report on the data. Further optimizations with inserted charts, attached PDF or Excel files or references to real-time dashboards (in Tableau) are of course also possible.


See accompanying post on LinkedIn:

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