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allowNestedData, dataHandler, No-Code Data Pipeline Release

The moment has arrived to reveal what our engineering team has been occupied with during the previous months. Let's delve into the March Product Updates!

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We are excited to announce the latest updates and features. In this blog, we will cover our top five feature highlights of March:

  • Our data importer can now process nested JSON files
  • Our dataHandler feature brings a lot of new possibilities and allows you to handle even more complex data transformation scenarios than before
  • We reduced the loading time for option and column mapping by up to 90%
  • We extended the i18nOverrides functionality for boolean drop-downs and introduced new pre-written translations
  • And the big news: We released a new product, our automated no-code Data Pipelines

Let’s dive in!

Parsing nested JSON files (allowNestedData)

Multi-dimensional/grouped data also called nested data is something a lot of companies struggle with when importing and reformatting customer data. Breaking up these dimensions into a two-dimensional structure that can be displayed as a table takes up significant time and effort for engineering teams and is a key challenge brought to us by our clients.

Our new feature allowNestedData finally solves this issue by allowing to de-nest .json files based on a pre-defined set of rules. The de-nesting process involves replacing arrays with underscores "_" and objects with periods "." to facilitate the display of data in a 2D table.

Check out our documentation for more information.

Parsing nested JSON files (allowNestedData)
Parsing nested JSON files (allowNestedData)

dataHandler for complex data transformation scenarios

Our new dataHandler feature allows to solve complex data manipulation scenarios, such as transposing data, merging and splitting columns, joining sheets, de-nesting data, and more. Unlike our other Cleaning Functions, that either iterate through every entry or are applied on only one column, the dataHandler function works on the entire data at once.

The function contains two parts: The headerStep (runs before the “Header Selection” step) and the reviewStep (runs before the “Review Entries” step) providing access to the original data and its metadata as well as enabling you to add/remove columns and rows. The dataHandler can be configured to run based on the your needs.

More details on this powerful tool as well as Code Sandboxes to test sample use cases can be found in our documentation.

dataHandler function overview
dataHandler function overview

Up to 90% loading time reduction for Columns and Category Matching

To improve our user experience during the “Match Columns” step, especially with target data models including category columns with a large amount of dropdown options, we updated our matching module and were able to reduce the matching time up to 90%.

Install the latest version and try it out with your own sample file, we'd love to hear your feedback!

Multi-selection of dropdown options
Column Matching time reduction

Improvement of i18n functionality

For enabling you to use custom UI texts or support multiple languages, we provide you with an i18nOverrides option in the SettingsAPI. We now also added the i18n support for the “Yes” and “No” labels of the boolean dropdown fields via the keys “txt_boolean_yes” and "txt_boolean_no". In addition, we extended our list of pre-written translations to reduce your time and efforts for implementing our importer even more!

Find more information about this feature in our documentation.

Do you want to implement our data importer in a language that is not on the list yet? Feel free to reach out to us and we are happy to add it!

i18n translation functionality improvement
i18n translation functionality improvement

New Release – nuvo's no-code Data Pipelines

(drum roll, please) We are excited to announce the official release of our new no-Code Data Pipelines solution!

Automating the mapping, transformation and importing of customer and supplier data based on a pre-defined schedule or event was a huge pain point that a lot of our users told us about.

Providing a secure and scalable solution for this that enables anyone in the organization to setup data pipelines, manage, observe and fix them accordingly was something we wanted to solve for all our users.

After long months of development, we are happy to release our No-Code Data Pipeline Solution and are very proud to also be ranked as Top 3 Product of the Day on Product Hunt!

Our Data Pipeline Product allows to:

  • Connect to a dedicated input source and output source to define where the data should come from and be sent to
  • Build powerful data transformations using Excel-like formulas or JavaScript Code injection
  • Run, observe and fix your data pipelines using our simple and intuitive dashboard

Intrigued to learn more? Check out our Start Guide or get in touch with us for a short demo and test access!

data transformation step
Data Transformation Step

If you want more details about any of the new features, don't hesitate to book a call with our team.

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