CSV is the only file type that can be uploaded to the Keatext text analytics platform.
Your first step to importing data begins with a well-configured CSV file. To learn more about CSV files and preparing your data for upload, click here.
All of your uploaded data sources are accessible on the Sources page of the platform.
Adding a CSV file to your sources
Once your CSV file is properly prepared, you're ready to upload it for analysis. On the Sources page, add your new source from the files stored on your computer.
Configuring your data fields
Once your CSV file is uploaded, configure the data fields so Keatext can interpret and analyze the data correctly.
You have the option of giving your dataset a source name. By default the original CSV file name automatically appears in this field, but can be changed for clarity.
For future reference, you can add a brief description of your source. This can be a useful piece of information when working with multiple people in the same account.
If applicable to your dataset, choose a date field (we say "primary date" as you may have more than one - choose the one of most importance). This is how the Keatext system detects temporal trends.
You also have the option of choosing a commenter ID field (a unique customer/employee identifier such as an email or internal customer/employee ID linking an individual across channels).
These settings cannot be modified once your source has been uploaded.
Now it's time to select the fields you would like to add.
Click the "select fields" button to choose the columns from your CSV that you would like to add. You do not have to add all of the columns if some are irrelevant to the analysis.
You'll see the Date and Customer ID columns are automatically selected if you chose those options previously.
Don't forget to add relevant metadata. At Keatext we love metadata! It can be used for segmenting and creating data correlations, and makes for really interesting charts on the dashboard.
Selecting fields for analysis
Each field will automatically be named in correlation with the original CSV's field name (headers).
Next to each field name, identify that field's data type (as in the original CSV) via a pull-down menu. The app automatically detects the data types used. While typically accurate, it’s a good idea to double-check the data types when configuring the data fields. The options are: text (string of characters, such as drop down options or long form textual responses), number (a price or any other numeric value) and date (click here for all supported date formats).
Perhaps the most important aspect of uploading data for text mining is identifying long form textual comment or feedback fields and check-marking them. In your original dataset, you can see which fields contain comment data that came directly from the respondent - check those fields, and only those fields!
Fields that do not include long form textual comment data or other direct feedback should not be check-marked. Those fields will be used as metadata filters.
Keep in mind that you need to select at least one text field to be analyzed.
Starting the analysis
Once you've selected the fields to include in the analysis, click the “Import CSV” at the bottom of the page and sit back and relax while the Keatext system gets to work!
If you encounter any problems in the upload process, check that: