Data Basics: Overview

This article is intended as a foundation for understanding how data connects to and works with Stratifyd. The is provided as a general background on data management in Stratifyd, while other articles contain detailed step-by-step guides for connecting and analyzing your data. 

Stratifyd Data Types 

Stratifyd data terminology is broken into 3 groups: 

• Data Source – the repository that holds the universe of data available 
• Data Connector – the method to extract a subset of the data source 
• Data Stream – the Stratifyd object that contains a subset of a data source. A data stream is what is used to build workspaces, visualizations, run AI models, etc. 

Data Source 

Stratifyd is a data agnostic platform that is flexible in handling both structured (numbers, classifiers, location, etc) and unstructured (long text fields, reviews, transscripts) data. You can leverage Stratifyd to analyze any of these data sources. However, there must be a data connection in order for Stratifyd to get access to the sources you care about. 

Data Connector  

Data connectors allow you to get access to the data you care about. Connectors can be found in the data management tab of the platform (see image below). Each connector has a workflow that prompts you to input basic information so the connector can access the right subset of data.  

Custom data “connectors” can be built in order to protect first party data and maintain privacy, but will require scoping and development. For information on custom connectors please review this article and contact your Stratifyd representative.  

Data Streams  

Data streams are the final output of the data connector. Each stream will be considered unique in the Stratifyd platform in order to facilitate necessary functions. Admins and Power Users can share streams with one another to create workspaces, leverage out of the box AI models, and create new models (taxonomy, autolearn, etc).  

Stratifyd Tip💡: Because Stratifyd allows for  custom analytics practices on each stream, the content of the stream is considered unique. If you create two streams with identical raw data of 100 records the total record count is considered 200.  

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