Data Import
Why Use Direct Import? When starting a new project on Dots, importing a pre-prepared Excel sheet lets you populate your database fast, enabling you to import hundreds and thousands of rows in one go and start analysis in no time.
Start Importing Data - Steps to Follow In the Datasets tab, click on the 'Import New Dataset' button and upload CSV sheet from your device.
Verify the Data Mapping After uploading data, the system will automatically map it to the relevant fields. You’ll then be able to preview how the data will appear once published, and you can change the field type as needed.
Different field types
To guide you, the table below shows how to structure your data for each field type. You can also refer to the sample sheet over here to test with sample data.
Document Title
Use this field type to uniquely identify each document in your dataset.
Date
Use this field to add date values. Dates can be analyzed over time and used in time-series visualizations.
Text
Use this field type for short pieces of text, such as titles, labels, or brief notes. Best suited for concise content of around 10 to 20 words which does not require highlighting.
Rich Text Field
Use this field type for longer qualitative content like transcripts, summaries, or long responses. Rich Text supports highlighting and is ideal for deeper analysis.
Numbers
Use this field type for numeric values. Numbers are analyzed within relevant ranges for calculations and comparisons.
URL
Use this field type to store external or reference links related to your data.
Single Select
Use this field type when one option applies for each entry.
Multiple Select
Use this field when more than one option applies for each entry using a chosen separator.
Single Tag
Use this field type to assign one tag to each entry. Tags help organize, filter, and connect data across datasets and form the basis of data connectors. This field type requires data connection to be set up with an existing tag category, if present.
Multiple Tag
Use this field type to assign multiple tags to each entry using a chosen separator. Tags help organize, filter, and connect data across datasets and form the basis of data connectors. This field type requires data connection to be set up with an existing category, if present.
How to set up Data Connectors with Single / Multi Tag field types
The Data Connectors feature enables users to connect different datasets using consistent tags. Allowing cross-dataset analysis and filter data from multiple datasets simultaneously to ease your search.
Step 1: Upload Dataset 1
Upload your first dataset to the platform.
For any column you plan to use for connections, set its field type to Single Tag or Multi Tag.
Import the data. This creates a tag-category based on the values in that column.
Step 2: Upload Dataset 2
Upload your second dataset.
For the header/column you want to link to the first dataset, again set its field type to Single Tag or Multi Tag.
In the "Connect with Existing Tag Category" dropdown, choose the entire dataset if you want all fields or select an individual field for a specific filter.
Import the data.
Once complete, the values in that column from both datasets will be unified under a common tag category, enabling cross-dataset filtering and analysis.
Using Separators for Multi-Tag / Multi-Select Field
A separator between tags or options helps you separate two or more options added in a single cell. Using any special character, you can split the two-option added in one cell and register on the platform as two data points.
Example: Let's say you have a dataset with a column named Safe Sanitation Awareness Campaigns. In that column, you may want to indicate more than one campaign name. Using a special separator (e.g. $) allows the system to record multiple values from a single cell.
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Behavior Change Communication (BCC) via Mass, Mobile & Community Media
Upload data on the platform
Once you've reviewed the data you click on 'Confirm Import' to have your data on the platform.
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