Connect data sources
Connect existing data sources or upload data to the platform
To connect the Spektr platform to your data sources, go to the Connection Hub.
Here you see your existing datasets (if any) and can connect new data sources via API, CRM connection or CSV upload.
In the Service catalog you can see an overview of all the services you can integrate with.
Connect trough API
To connect your own custom data source via API, click on Connect through API.
This will open detailed instructions on how to set-up and connect your API. You can also access the API instructions here
Import Customer Data through API instructions here.
Choose connections
You can also connect your CRM system as a data source.
Currently we support Salesforce, Hubspot, Oracle and Microsoft 365.
Please contact us, if you would like to connect your CRM system.
Upload a CSV file
To import data via CSV file, click on Upload a CSV file.
You can select a file by clicking on Browse or drag and drop a file into the designated area.
Upon uploading, the system validates the file's structure and data consistency.
Once the file is sucessfully uploaded, you find the new dataset under Your datasets.
Here you see the number of fields that were found and the Extract fields button.
To use the data set, click Extract fields.
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Select the variables you want to use by checking/unchecking the variable on the left
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Select the correct data format for each variable from the drop-down menu Data type
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String: text
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Date: date (most common date formats are usable)
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Number: numerical value
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Boolean: 0 or 1
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Country: country code (e.g. GB or GBR, DK or DNK, DE or DEU)
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File: link to the file's location
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Select the identifier that is used to identify duplicates
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Click on Save dataset
Select the variables you want to use by checking/unchecking the variable on the left
Select the correct data format for each variable from the drop-down menu Data type
String: text
String: text
Date: date (most common date formats are usable)
Date: date (most common date formats are usable)
Number: numerical value
Number: numerical value
Boolean: 0 or 1
Boolean: 0 or 1
Country: country code (e.g. GB or GBR, DK or DNK, DE or DEU)
Country: country code (e.g. GB or GBR, DK or DNK, DE or DEU)
File: link to the file's location
File: link to the file's location
Select the identifier that is used to identify duplicates
Click on Save dataset
To make sure the CSV file can be processed, please ensure to use the correct format as described below.
CSV formatting
Character Encoding:
Use UTF-8 as the character encoding.
Header Row:
Include a single header row with clear and descriptive column names.
Date Format:
Use the ISO 8601 standard (e.g., "2023-03-08" for March 8, 2023).
Consistent Data Types:
Ensure each column contains consistent data types (e.g., numeric or text).
Field Names:
Use concise and meaningful names. Avoid spaces or special characters; instead, use underscores (_) or camelCase.
Thousands Separator:
Do not include thousands separators in numeric fields.
Empty Fields:
Non-mandatory fields can be left empty, but their column should still be present in the file.
Example CSV Structure
Headers:
Example Rows:
Common issues
If the upload fails, check if you have
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Missing headers or mismatched field names
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Inconsistent delimiters (e.g. commas instead of semicolons)
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Invalid date formats
Missing headers or mismatched field names
Inconsistent delimiters (e.g. commas instead of semicolons)
Invalid date formats