JSON extraction made simple
Problem — JSON handling can get complex for developers. It’s inaccessible for non-developers.
Solution — Auto key-value detection, quick transformation into rows and columns, powerful automation, zero coding
While JSON seems to have taken over the world, there are glaring problems for both developers and non-techies alike — attempting to parse and manage the data.
For developers, it may be a simple scripting exercise at first, but if you throw in multiple sources or deeply nested values, the pains can increase exponentially. For the non-tech folks, it’s just not accessible.
At Mammoth Analytics, we’ve made some massive strides to reinvent that process. Our solution is game-changing and for anyone who needs to manage JSON data, and we think you’re going to love it.
Here’s a quick animation. There’s a bit more explanation further down.
What you see in the above video is an example of a JSON structure being transformed into rows and columns and placed in a data pipeline. This is all done in under a minute, without writing any code. Some features worth mentioning:
Auto key-value detection
The Mammoth platform automatically detects the JSON schema and presents a point and click solution to flatten out the data.
Easy handling of nested values
If your first level of extraction results in a column with another JSON structure, we can keep applying the “Extract JSON” function. These tasks get added to the pipeline.
Mammoth provides automation by default. All your incoming JSON data automatically goes through the extraction pipeline. Extract your JSON data, perform various transformations to it and then send the prepared data out to your data warehouse.
Instant discovery and exploration
In the above video, you’ll notice we’re exploring and drilling down on the data we’ve extracted. This allows us to get an overview of the data and perform sanity checks. In the case of anomalies, we can take immediate action, as described below.
Additional transformational capabilities
There’s a good chance the extracted values aren’t in the perfect shape. Whether it is miscategorized or uncategorized data, spelling mistakes, or just simple filtering of rows, you can make the changes and add them to the data pipeline.
After shaping the data to your liking, send it out to a data warehouse using Mammoth’s various exporting capabilities. This export task gets added to the end of the data pipeline, so all your steps are completely automated.
The Mammoth Platform
We’re assuming JSON extraction is a small part in your data project. Mammoth provides all the tools you need for the rest of your journey, including data ingestion, warehousing, transformation and discovery. Check out all the features here.
For those who don’t know about Mammoth Analytics, it is a code-free data management platform. It provides powerful tools for the entire data journey, including data retrieval, consolidation, storage, cleanup, reshaping, analysis, insights, alerts and more. You can check it out at www.mammoth.io
We’ll be posting similar articles regularly. If you have additional questions, feel free to leave a comment here or reach out to us at hello @ mammoth.io