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Datasets

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Written by Omnisient Product
Updated today

The Datasets section is where you view and manage all datasets available to your organization. This includes datasets youโ€™ve uploaded and registered, datasets shared with you by connection partners, and tools that allow you to prepare, transform, and generate derived datasets for use in projects.

My Datasets

The My Datasets tab displays all datasets uploaded by your organization. Datasets are grouped based on their current processing, registration, and sharing status.

This table acts as the dataset lobby. Newly uploaded datasets appear here while they are being processed. You can review potential issues, such as high error rates or possible PII leaks, to ensure the dataset is in optimal condition before registration.

At this stage, datasets can also be mapped. Mapping is a crucial step to ensure the dataset is fit for its intended purpose. The mapping process confirms that all required columns and information are available for use in future projects.

These datasets have completed processing and registration and are ready to be used in projects. Available datasets can also be shared with connection partners. Deleting a dataset will trigger a confirmation modal if it is currently shared. This helps prevent accidentally removing a source dataset that one or more connection partners may be using.

These datasets can also be mapped. Mapping is a crucial step to ensure the dataset is fit for its intended purpose. It confirms that all required columns and information are available for use when the dataset is included in a project.

Dataset Share

This table lists registered datasets that have been shared with connection partners. You can manage or revoke partner access to a dataset at any time from here.

Dataset Types

Dataset types help categorize datasets based on their purpose and the kind of data they contain. These types are used throughout the platform to guide processing and downstream usage.

Dataset Type

Description

Mapping Supported
โ€‹
๐Ÿ“š How to map a dataset

Custom / Derived

A dataset created on the platform using tools such as SQLPad, then registered for use in the platform.

Customer

A dataset containing customer information, including PII that must be anonymized.

Customer (Activation)

Contains single hash values intended for upload to activation channels such as Meta and TikTok.

Dimension

Descriptive dataset information that does not contain PII and does not require anonymization.

Transactional data where each row represents an individual transaction at a point in time. Does not contain PII and does not require anonymization.

โœ…

Other

A dataset containing mixed information that may include PII and may require anonymization.

Partner Datasets

This tab shows datasets that have been shared with your organization by connection partners. From here, you can review incoming dataset shares and decide whether to accept or decline access.

Partner Datasets Statuses

Status

Description

New

Requires action from you. You can either Accept or Decline the dataset share.

Accepted

You have accepted the dataset share. The dataset can now be used when creating a new project and will surface in the partner referencing dropdown.

Declined

You declined the dataset share. The dataset will not be available for use in projects.

Locked

The dataset share has expired. Any projects using this dataset will also become locked.

Own Data Preparation

This tab provides tools to explore, transform, and prepare your datasets for use in projects. You can also create and save new datasets, which will appear as Custom / Derived datasets under My Datasets.

Supported Tools

The following tools are available:

Tool

Description

SQLPad

Use SQLPad to write and run SQL queries to explore and prepare your data for projects. In supported projects, SQLPad can also be used to generate exports, allowing you to extract query results for external use through the platformโ€™s export approval process.
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๐Ÿ‘‰ How to Create a SQLPad Export
๐Ÿ‘‰ Approving SQLPad Exports Created On Your Data
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๐Ÿ‘‰ How to Assess SQLPad Exports with Confidence

Jupyter Notebook

Create code and data visualizations and effortlessly enhance your data preparation.

Prepare your dataset by mapping its columns to the required fields.

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