Mock Data Generators for Tabular Data

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Developing a JavaScript-based web front-end, e.g. with frameworks such as Angular, at some point – especially during the prototype phase – often requires working with data supplied by a back-end data source.

Tools such as JSON Server enable you to spin up such a data source as a REST API server in no time with zero coding involved.

However, running a back-end server is only part of the equation that is testing a front-end against actual data. Another vital ingredient is the data itself. Barring a copy of production data (which comes with its own caveats and necessary precautions such as the need for anonymising customer and transaction data) manually entering test data often seems like the only straightforward option.

This, of course, is a tedious, error-prone process that’s likely to produce less-than-stellar data (apart from more often than not consuming otherwise valuable developer time).

Mockaroo is a simple online tool that tries to alleviate this problem by providing a generator for mock data. It allows you to generate tabular test datasets with attributes of a plethora of different data types from fake names to geographic coordinates, or even ICD-10 codes.

The generated dataset can be downloaded in a variety of formats such as CSV, JSON, SQL statements, XML, or as an Excel spreadsheet.

Up to a 1,000 rows of generated data per download Mockaroo is free of charge. If you need larger datasets subscription plans start at $50 / year.

Another useful tool in this category is the – quite bluntly named – It generates arbitrary data from plenty of data types as well, albeit not quite as many and not quite as sophisticated ones as those you get with Mockaroo. A nice feature that came in particularly handy for me lately though was the option to export data in not just the common data exchange formats such as CSV, JSON, SQL, or XML but as an HTML table, too.

This allowed me to immediately use the generated mock data in a static HTML example I had whipped up for a CSS workshop dealing with the challenges that come with styling large data tables in web applications.

About the author: Bjoern
Independent IT consultant, entrepreneur

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