Notion

The Notion Data Connector enables seamless integration and synchronization of data from your Notion account into Mantium. Notion is a versatile workspace tool that combines notes, databases, wikis, and project management features into a single platform. With this data connector, you can access, analyze, and manipulate your Notion data, including pages, databases, and blocks, using Mantium's powerful suite of data transformations.

Features

Feature	Supported	Notes
Re-Syncing	Yes	1 Hour 12 Hour 24 Hour Weekly Monthly
History	Yes	Entire History
Fields	Yes	`notion_type` `created_by` `edited_by` `title` `content` `source_url`
API Configurable	Yes	Contact Us

Setup instructions:

To set up the Notion Data Connector with Mantium, follow these steps:

Log in to your Mantium account.
Click on "Connectors" on the left-side navigation bar.
At the top right corner, click on Add Connector and then select Notion.
You will be redirected to an Notion OAuth page where you will grant Mantium access to your Slack workspace.
Once the authorization is successful, you will be redirected back to Mantium, and the Notion Data Connector will be added to your list of connected data sources.

Recommended transformations:

Based on the data headers provided, here are some recommended transformations that can be performed using Mantium:

Token Count: Analyze the frequency of words in the title, content, and source_url columns.
Generate Text: Create a human-readable summary of each row using the title, content, and source_url columns.
Summarization: Summarize long text fields in the content column.
Create Column: Create new columns based on existing data, such as extracting keywords or mentions from the content column.
Rename Column: Rename columns for easier understanding or to comply with specific naming conventions.
Split Text: Split the source_url column into separate domain and path columns.
PDF to Text: If the content column contains PDF files, extract the text from these files.
Combine rows: Merge rows with related data or concatenate text from multiple rows into a single row.
Generate Embeddings: Create embeddings for text fields like title and content to use for machine learning or clustering purposes.
Delete Columns: Remove unnecessary columns that are not needed for analysis.
Reformat CSV: Adjust the CSV format as required, including delimiters and encoding.
Columnize CSV: Convert a single column of CSV data into multiple columns for easier analysis.
Transcribe Audio: If the content column contains audio files, transcribe the audio into text.
Clean Text: Remove unwanted characters or formatting from the title, content, and source_url columns.