Document Version: 1.0

  1. General Description

    Sympathy for Data is a software platform for data processing, data analytics and data science applications. Offering numerous building blocks for operating on data and the flexibility to build your own. These are combined into workflows to solve larger tasks.

    Supported formats include CSV, Excel, and SQL for tabular data and JSON, XML and MongoDB for unstructured data. Additionally, there is support for working with images, machine learning models, text, plots, HTML and PowerBI datasets via HTTP.

    The graphical user interface gives an overview of the workflows while allowing the data to be explored, down to the building blocks, at every step of the way. Intuitively providing the insight and feedback needed at different stages, from data exploration and prototyping to testing and maintenance of production applications. Alternatively, the batch interface can be used for automation of existing workflows.

    Aimed to be extensible and flexible, new building blocks can be built from workflows. Support for new kinds of data and processing can be added with Python code, leveraging the vast Python ecosystem.

  2. Sympathy for Data

    Sympathy for Data has the following components as listed below:

    • Graphical user interface. For development and interactive use, this includes building workflows, executing them, producing data, reports and getting help to build new nodes, etc. through wizard helpers.

    • Batch interface. For automation/deployment of workflows already built.

    • Data viewer which can visualize Sympathy for Data’s own data format.

    • Standard library. Includes nodes for data processing, input/output, image processing, machine learning, visualization and more.

    • Batteries included python environment for data analysis.

    • Stand-alone documentation (usable offline).

    • Advanced machine learning toolkit: Extended machine learning with many new nodes and concepts for working with larger amounts of data, compared with the standard library.

    • Advanced databases toolkit: Includes support for MongoDB.

    • Azure toolkit: Includes support for SharePoint and PowerBI datasets.

    • Image analysis toolkit: Extends image processing with many new nodes for processing images, compared with the standard library.

    • Time Series toolkit: Includes nodes for time series analysis.

  3. Purpose of Sympathy For Data

    • Build workflows from nodes, connections, and text boxes. Customize texts and labels.

    • Create new custom libraries (owned by the Licensee).

    • Create new nodes, subflows and plugins to custom libraries.

    • Generate documentation for custom libraries.

    • Execute nodes and workflows, executing nodes process input data and produce output data.

    • Explore the input and output data from nodes and workflows.

    • Configure nodes via the graphical user interface or the configuration port to customize their behavior/function

    • Add python packages to the installation without overriding the existing environment as specified in the Software Requirement Specifications. For example, adding a new python module/package to use for a new kind of analysis in a custom node or a python scripting node.

    • See the documentation for more details about what you can do.

  4. Limitations

    1. Parallel running instances

      Maximum 4 concurrent instances are allowed to run on the same device with the same activation unless otherwise agreed on in the quote, purchase order confirmation or another addon agreement.

  5. Third Party Software

    Sympathy for Data makes use of third party software, as set out in the Third Party Software. The installer version is packaged with the Third Party Software.