As the importance of data-driven decisions increases, the tools we use to gather, process, and visualize this data become equally critical. Two tools that have significantly impacted the data analytics landscape are KNIME and Tableau.Â
KNIME Analytics Platform is an open-source data analytics tool that enables users to manage, process, and analyze data through a visual, user-friendly interface. Tableau, owned by Salesforce, is a leading tool for data visualization, allowing users to create interactive dashboards and reports for better data understanding and decision-making.
While both these tools are powerful on their own, their combined strength offers a comprehensive solution for data analytics.Â
In this blog post, we will show you how to leverage KNIME’s Tableau Integration Extension and discuss the benefits of using KNIME for data preparation before visualization in Tableau.
KNIME Tableau Integration Extension
The KNIME Tableau Integration Extension allows for seamless connectivity between KNIME and Tableau, enhancing the capabilities of both tools. This extension enables users to send data directly from KNIME workflows to Tableau Server, bypassing the need for intermediate file exports. Additionally, users can save the output of their workflows as Hyper extract files locally. As a result, users can streamline their data analytics process, moving from data processing in KNIME to visualization in Tableau with just a few clicks.
The extension includes dedicated nodes for writing data to Tableau hyper files and publishing them to Tableau Server or Tableau Online. It ensures that data processed and analyzed in KNIME can be conveniently visualized in Tableau, fostering a smooth transition and saving significant time and effort. You can read more about the KNIME Tableau Integration here.
How to Install the KNIME Tableau Integration Extension
KNIME Analytics Platform allows users to install hundreds of useful extensions, including the KNIME Tableau Integration Extension. Installing extensions is straightforward and can be done directly from within the KNIME Analytics Platform. This extension is not included in the standard KNIME installation, so it needs to be added manually. Here’s how to do it:
With the KNIME Analytics Platform open, navigate to File → Install KNIME Extensions…
In the menu that appears, either use the search bar to type in a keyword or scroll through the list of folders. The Tableau extension is in the KNIME & Extensions folder.
Once you have found the extensions you wish to install, press Next through a few menus and accept the license agreement.Â
Press Finish and allow KNIME to install the selected extensions. Once the installation is complete, restart KNIME. You will see your new extensions in the Node Repository when it reopens.
Once installed, you can find the dedicated Tableau nodes in the node repository in the Tableau folder under the Tools & Services section. These nodes can then be dragged and dropped into your workflow, just like any other KNIME node.
Installing the KNIME Tableau Integration Extension will unlock the potential of a more streamlined, efficient data analytics pipeline, where data manipulation in KNIME and visualization in Tableau can occur almost simultaneously. This not only saves you time but also ensures that your visualizations in Tableau are powered by accurately processed and analyzed data.
Why Use KNIME for Data Prep for Tableau?
Data preparation is a critical phase in any data analytics process. While many tools are available, KNIME stands out for its robust capabilities and superior features, especially compared to traditional tools like Microsoft Excel.
Handling Large Datasets
One of the primary advantages of using KNIME is its ability to handle large datasets. Some tools, like Microsoft Excel, have row limits, which are about a million rows as of the latest versions. However, real-world data, especially in the context of big data, can often be well into the hundreds of millions or billions of records. KNIME, on the other hand, is designed to work with big data technologies and can handle much larger volumes of data without compromising performance.
Automation and Reproducibility
KNIME allows users to create automated workflows for data preparation. These workflows can be saved, shared, and reused, ensuring consistency and reproducibility in your data prep processes. This is particularly useful when you’re dealing with regular data updates or need to perform the same data prep steps on different datasets.Â
KNIME Business Hub (which replaced KNIME Server earlier this year) elevates the automation capabilities of KNIME, facilitating better collaboration and operational efficiency. It provides a platform for users to share and reuse data science projects, fostering a collaborative environment.
One key feature of KNIME Business Hub is its advanced scheduling capabilities. You can automate KNIME workflows to run at specific times or intervals, a boon for regular data prep tasks or updates. This ensures that your Tableau dashboards are consistently updated with the latest data.
Moreover, with the support for REST APIs, your KNIME workflows can integrate with other applications or services, enabling even greater automation. Thus, the KNIME Analytics Platform and Business Hub saves time and ensures that your data prep for Tableau is robust, efficient, and scalable.
Advanced Data Processing Capabilities
KNIME provides a wide range of nodes for data extraction, transformation, and loading (ETL), but it also offers advanced data manipulation and processing capabilities. This includes machine learning, statistical modeling, and text mining, among others. These advanced capabilities can significantly enhance your data preparation, allowing you to uncover deeper insights and create more meaningful visualizations in Tableau.
KNIME’s capabilities are significantly expanded with a host of extensions that provide advanced data processing and analytics functions. Here are a few noteworthy extensions:
KNIME Text Processing Extension: This extension provides a set of nodes for text data processing, including reading and writing documents, text cleaning, term extraction, and text classification. It’s a valuable tool for natural language processing tasks and sentiment analysis.
KNIME Machine Learning Extensions: KNIME offers various extensions for machine learning, such as the KNIME Deep Learning – Keras Integration, KNIME H2O Machine Learning Integration, and KNIME Python Integration. These extensions provide nodes for implementing a wide range of machine learning models, from regression and classification to deep learning.
- KNIME Time Series Nodes Extension: This extension provides nodes for the analysis of time series data, including time series filtering, decomposition, and forecasting. It’s a valuable tool for financial data analysis, sales forecasting, and other temporal data tasks.
Conclusion
The combination of KNIME for data preparation and Tableau for data visualization offers a powerful, streamlined solution for data analytics. Whether you’re cleaning and transforming raw data or creating interactive, dynamic dashboards, these tools can make your data work for you.
If you’re ready to take your data analytics process to the next level, don’t hesitate to contact us. Our team of experts can help you leverage the power of KNIME and Tableau, guiding you through the process of data preparation and visualization. Start your data journey today and transform the way you make decisions with KNIME and Tableau.
Are you ready to unlock the full potential of your data analytics process? Harness the power of KNIME and Tableau to make better-informed decisions.
