After uploading your dataset to the Relevance AI's platform, you can check your data, data statistics and configure some settings.
In this page, we will explain the Setting dataset feature. The setting page allows you to configure field types, aliases, and more technical settings. To start click on your desired dataset under your account

Select an existing dataset under your account.Select an existing dataset under your account.

Select an existing dataset under your account.

From the menu on the left-hand side, click on "Settings" under Datasets and you will see a page similar to the following image.

Relevance AI - Dataset setting pageRelevance AI - Dataset setting page

Relevance AI - Dataset setting page

There are 5 main sections to this page:

Dataset fields

In this section, you can 1) assign an alias to a field, 2) change the data type if necessary.

Relevance AI - Dataset settings, fieldsRelevance AI - Dataset settings, fields

Relevance AI - Dataset settings, fields

Aliases can be used to refer to fields with another name. This feature is very useful in situations like when existing names are too long, not descriptive enough or a simple change of format as shown in the image (i.e. full_name -> Full Name).
Data types are detected automatically in our platform and it is best not to change them. However, in the very rare case of wrong type detection, use the marked down-arrow and select the correct data type from the list.

Name of entities in the dataset

The use of the right words makes the insight and the final presentation more tangible and meaningful. If your dataset is on customer reviews, comments, data descriptions or project learnings, you can simply use the right referral to the entities here, (e.i. Reviews, Comments, Descriptions and Learnings respectively). Using the plural word form is recommended.

Relevance AI - Dataset settings, entitiesRelevance AI - Dataset settings, entities

Relevance AI - Dataset settings, entities

Main date field

You are provided with date filtering and time series for insight analysis and presentation. Every data entry automatically receives an insert_date_ field, the date the entity has been uploaded to Relevance AI's platform. In case, you wish to analyse with another date field in your dataset, select it from the drop-down menu as shown below.
Note: Keep in mind that date entries must follow dash-separated year, month and day format in 4, 2, and 2 digits (e.g. yyyy-mm-dd). Therefore, in case your dataset contains a date field with values not in the standard format, you need to standardize the date values before uploading your dataset to the platform. For instance,
May 29, 20 --> 2020-05-29
2017-08-21 15:56:48 ---> 2017-08-21

Relevance AI - Dataset settings, date fieldRelevance AI - Dataset settings, date field

Relevance AI - Dataset settings, date field

Text highlighting rules

A very useful tool when dealing with text data is a highlighter. Relevance AI's highlighting tool receives a "Text field to highlight" and a "Substring" field where the substring is a subset of the main text and the text subset is highlighted when presenting/visualizing the parent field. This is very helpful when analysing subsets of the original text to achieve more fine-grained results.
Text field to highlight and the substring field are selected via the marked drop-down menus in the picture below. Leave the weight as none or use the numeric values in your dataset as a weighing parameter if applicable (e.g. when analysing negativity or positivity of comments and darker highlights identify stronger views).

Relevance AI - Dataset settings, date fieldRelevance AI - Dataset settings, date field

Relevance AI - Dataset settings, date field


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