Formatting your data


Now that you have an account on Daylight and access to a Workspace, the next step is to upload some text data to analyze. You can refer to the Using different data sources with Daylight page for some pointers on different types of text data to consider. You will also want to include some metadata to provide context for the text data, such as demographic information, dates, scores, etc. Metadata can be used to filter the data to analyze a subset of the data set, and numerical data can be used in Drivers analysis, which you will learn about later in this document.






Data Fields


The following table describes the types of data that can be included in the data to be uploaded. You will need to designate the data type for each column of the uploaded data during the uploading process. There are two ways to do this:







Sometimes, a metadata field can have multiple values within a single document. For example, a survey may ask the respondent “which of these products have you tried?”. In such a case, the respondent may select more than one product. There are two ways that you can format the data in such cases:



Supported languages and multilingual datasets


Daylight is capable of performing analysis natively in 15 languages. For best results with a multilingual dataset, split your data into one language per upload file. Each language will be uploaded and analyzed as its own Project.



Save as a CSV file


Daylight is capable of performing analysis natively in 15 languages. For best results with a multilingual dataset, split your data into one language per upload file. Each language will be uploaded and analyzed as its own Project.

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