This article walks the reader through how to configure data for ClearQuery success.
Formatting Data for Success – Manual File upload (.csv or JSON)
While uploading data into ClearQuery is simple and intuitive there are a few things to consider which can lead to the greatest analytical experience:
- ALWAYS include Headers in your dataset imports
- For numeric fields which have a value of 0, do not leave the cell blank or fill it with a symbol such as: “-”. Please place a “0” in these cells for the best visual results.
- Valid data import types include: .csv, JSON, Google Sheets, Elastic Indexes, Snowflake, and SQL – other file types & connectors are in the works.
- If work is typically completed within Excel, those files can easily be saved as a .csv file.
- Dates: while there are many ways to format a date field, here are a few examples of date formats that ClearQuery is optimized to handle:
- 1/1/22
- 1-Jan-22
- 1/1/2022
- 01/01/22
- 01-Jan-22
- 2022-01-01
Following manual data import, users can add additional data to those datasets by going to the Dataset Management page, hovering over the "Action" drop down and selecting "Add More Data."
Note:
- The new data needs to be in the same structure as the original imported file
- The original data can be included in the new file; ClearQuery will ignore the original matching records and only import the new rows
- This is not a way to update/edit the existing data, if the original/existing rows have been edited and are no longer identical to when they were originally imported ClearQuery will assume they are new and import them.
If you have additional questions regarding this topic, please reach out to your Account Manager or contact ClearQuery Support (support@clearquery.io).