JupyterLab Extension for INFACore

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Parse unstructured data

You can transform your input data into a user-defined structured format based on an

intelligent structure model

. You can use the

Parse Unstructured Data

function to analyze data such as log files, XML, or JSON files, Word tables, and other unstructured or semi-structured formats.

To parse unstructured data, use the

Parse Unstructured Data

function. The function uses

Intelligent Structure Discovery

to determine the underlying structure of the sample data file and creates a model of the structure.

Intelligent Structure Discovery

creates the

intelligent structure model

based on a sample of your input data.

You can create models from the following input types:

Text files, including delimited files such as CSV files and complex files that contain textual hierarchies

Machine generated files such as weblogs and clickstreams

JSON files

XML files

ORC files

Avro files

Parquet files

Microsoft Excel files

Data within PDF form fields

Data within Microsoft Word tables

XSD files

You can refine the

intelligent structure model

and customize the structure of the output data. You can edit the nodes in the model to combine, exclude, flatten, or collapse them.

You can process input from the source efficiently and seamlessly based on the

intelligent structure model

that you select. When you select the function, you associate it with the

intelligent structure model

. Select a data source based on a flat file to process local input files.

Explore the data

Configure the structure parser function

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JupyterLab Extension for INFACore

JupyterLab Extension for INFACore

Parse unstructured data

Parse unstructured data