What is Data Ingest?
Data Ingest is a feature in SysTrack that allows cloud customers to import external user or device data into SysTrack from CSV files and make it available through report views in dashboards, groups, and queries. Users may also refer to this process as data ingestion or data ingress. A typical use case is enriching SysTrack data with business-owned attributes such as department, asset tag, purchase date, employee ID, or other fields that are maintained outside SysTrack.
IMPORTANT: Currently, the Data Ingest feature is API-only. All operations run through REST endpoints, and no dedicated UI is available. This guide describes the recommended workflow, from schema design through audit review.
How Ingest Works
The Ingest API uses a staged process to provide validation and feedback that helps prevent failed or incorrect imports:
You define the target schema for users or devices and send it to SysTrack.
You send a CSV file to SysTrack that matches the defined schema.
SysTrack analyzes the uploaded file and reports any differences between the CSV and the current schema.
You review the differences and decide how to proceed. This step ensures that you validate schema changes and data updates before ingestion.
You explicitly call the process endpoint to start ingestion.
SysTrack ingests the data. After the first successful ingest run, the data is available through the
RPT_EnrichedDevicesandRPT_EnrichedUsersreport views.SysTrack associates each ingested device with its WGUID, optimized to run during off-hours to minimize impact.
Ingested users do not need to be associated with SysTrack data. Use email as a unique identifier to map user data.
You can use the Ingest API to update your imported data as often as needed.
Data Ingest Limitations
Only CSV files are supported.
You can upload up to 2,000 bytes of metadata per row in a CSV file.
A CSV file can contain rows for up to 125% of your current device or user count.
The schema must be in the JSON format.
Prerequisites
Before you start, ensure you have:
A valid Ingest API key for authentication. See Manage API Keys.
A CSV file with data you are importing: users or devices.
For devices, a key column type defined for mapping:
Use
SystemNamewhen device rows should be matched by system name.Use
Serialwhen device rows should be matched by serial number.
A validated column design:
Column names contain only letters, digits, and underscores.
Supported data types are
int,double,datetime,guid,boolean, andstring.String columns have a
lengthvalue greater than 0.
Step 1: Build the Schema
If you do not have a saved schema, create one from your CSV file during the following steps or use the provided examples.
Start From the Matching Template
If importing devices, start from
IngestAPI_Devices_Template.csv.If importing users, start from
IngestAPI_Users_Template.csv.
Example device schema mapping for IngestAPI_Devices_Template.csv
IngestAPI_Devices_Template.csvIngestAPI_Devices_Template.csv headers:
SystemName- the key columnAssetTagDepartmentGuidSupportTierPurchasePricePurchaseDateIsLoaner
Example device schema:
{
"keyColumn": {
"name": "SystemName",
"keyType": "SystemName"
},
"columns": [
{
"name": "SystemName",
"type": "string",
"length": 100
},
{
"name": "AssetTag",
"type": "string",
"length": 50
},
{
"name": "DepartmentGuid",
"type": "guid"
},
{
"name": "SupportTier",
"type": "int"
},
{
"name": "PurchasePrice",
"type": "double"
},
{
"name": "PurchaseDate",
"type": "datetime"
},
{
"name": "IsLoaner",
"type": "boolean"
}
]
}
Example user schema mapping for IngestAPI_Users_Template.csv
IngestAPI_Users_Template.csvIngestAPI_Users_Template.csv headers:
UsernameEmployeeIdDepartmentHireDateIsManager
Example user schema:
{
"columns": [
{
"name": "Username",
"type": "string",
"length": 100
},
{
"name": "EmployeeId",
"type": "int"
},
{
"name": "Department",
"type": "string",
"length": 50
},
{
"name": "HireDate",
"type": "datetime"
},
{
"name": "IsManager",
"type": "boolean"
}
]
}Draft the Schema from Your CSV Headers
Create a JSON file for your schema in a text editor.
Add one schema column entry for each CSV header.
Infer type per column using real sample values:
boolean: values liketrueorfalse.int: whole numbers only.double: decimal numbers.datetime: ISO-like timestamps such as2025-01-15T00:00:00Z.guid: GUID format values.string: anything else.
For each
stringcolumn, setlengthto a safe maximum expected value.
Add Device Key Mapping Explicitly (Devices Only)
Choose the matching strategy:
SystemNameif your CSV has stable system name values.Serialif your CSV has stable serial values.
Set
keyColumn.nameto that exact CSV header.Make sure that same column is also present in
columnswith the required type.
To get valid device key values, use the RPT_System_Config report view:
For
SystemName, use theSystemIdcolumn.For
Serial, use theSerialNumbercolumn.
Copy the values exactly as SysTrack stores them. In some environments, SystemId contains a fully qualified name. Do not shorten it. Devices without configuration inventory do not appear in RPT_System_Config.
Match the User Identifier Format (Users Only)
For user imports, SysTrack does not validate or change the user identifier value. You can ingest any format, for example email, UPN, or DOMAIN\user. To match ingested user data with SysTrack data in dashboards, groups, and queries, use the same format as the SysTrack column that you match it with.
Report View | Column | Format |
|---|---|---|
|
| |
| Email. Available only for users with Active Directory inventory. | |
| UPN. Available only for users with Active Directory inventory. |
Prepare the CSV File
Prepare the CSV file for the Ingest API so that its headers match the schema and its values match the column types. A file that does not meet these requirements can fail processing.
CSV File Format
Save the CSV file with UTF-8 encoding and use a comma as the delimiter. Excel in regions that use a decimal comma saves CSV files with semicolons as delimiters. The Ingest API reads such a file as one column.
CSV Header Names
CSV header names must match the column names in the schema. Matching ignores letter case. The Ingest API does not remove spaces from header names. A header with a space before or after the name, for example ' PurchasePrice ', does not match the schema column. In this case, the upload response lists the name with spaces under added and the schema column under deleted, and processing fails.
A common cause is a space after each comma in a header line that you typed, or spaces in Excel header cells.
CSV Values
The Ingest API keeps spaces in values. In string columns, spaces count toward the column length. In the device key column, remove spaces before and after the values, or the device rows do not match.
Every cell in an int, double, datetime, guid, or boolean column must have a value. An empty cell in these columns fails processing, even if the upload response does not show a problem. Cells in string columns can be empty.
Values in number, date, and boolean columns must use these formats:
Data Type | Accepted Values | Values That Fail |
|---|---|---|
| Whole numbers without separators, for example | Numbers with separators, for example |
| Numbers with a dot as the decimal separator and with the decimal part, for example |
|
| ISO 8601 dates, for example | Dates in day-first order, for example |
|
|
|
IMPORTANT: In a
doublecolumn, the Ingest API can accept the value1,345as 1.345 without an error. In adatetimecolumn, dates are read in US order, so03/04/2022is read as March 4.
Save the CSV File from Excel
Excel saves each cell in a CSV file as it is shown on the screen. Before you save the file from Excel, format the columns:
Format number columns as Number with the required decimal places, and clear Use 1000 Separator (,).
Do not use the Comma Style, Accounting, or Currency formats. These formats add thousands separators and padding spaces.
Format date columns with a custom format, for example
yyyy-mm-dd.Before you paste the device key values, format the device key column (
SystemNameorSerial) as Text. Otherwise, Excel removes leading zeros and changes long numbers to scientific notation.Save the file as CSV UTF-8 (Comma delimited).
Step 2: Submit the Schema
Call the schema endpoint in two situations: before your first upload for a given table type, and any time you need to change the schema (adding, removing, or modifying columns).
Use one of these endpoints (see Update an ingest schema):
PUT /ingestapi/tableType/devices/schemaPUT /ingestapi/tableType/users/schema
Paste your schema JSON as the request body.
Expected result:
SysTrack accepts the schema update.
Old ingested records remain (if any).
Step 3: Upload the CSV File
Upload the CSV file as raw text/csv content.
Use one of these endpoints (see Upload a CSV file):
POST /ingestapi/tabletype/devices/csvPOST /ingestapi/tabletype/users/csv
What to do:
Send the CSV body with the
text/csvcontent type.Review the response sections:
addeddeletedexistingwithisChanged: falseandisChanged: true
Expected result:
The upload succeeds.
The response shows a schema-difference analysis that indicates whether you can continue.
Upload does not automatically start processing.
If you upload a second CSV before processing the first, it replaces the first file.
Step 4: Decide Whether to Adjust the Schema
If the upload response shows unexpected added, deleted, or changed columns, stop and correct the schema or the CSV before processing.
Accepted for processing:
Header order does not have to match the schema order.
String values may be shorter than the schema length. In this case, the column still appears under
existingwithisChanged: true.
Not accepted for processing:
addedcolumns.deletedcolumns.Values that do not match the type in the saved schema.
String values longer than schema length.
The type in the upload response is a guess from the values in the CSV file. Processing checks each value against the type in the saved schema. A string column in the schema accepts any value up to its length. A type shown for a string column, for example int for numeric asset tags, does not stop processing. For other types, a value that does not match the schema type stops processing.
What to do:
If the upload response shows no added or deleted columns and all
isChangedvalues arefalse, proceed to the next step.If the only change is shorter string values within the schema limit, proceed to the next step.
If the CSV is incorrect, fix the file and upload it again.
If the schema is outdated, update it and upload the CSV again.
Expected result:
The upload response reflects the expected structure.
Step 5: Start Processing
Once the uploaded CSV looks correct, start the ingest run.
Use one of these endpoints (see Process a CSV file):
POST /ingestapi/tabletype/devices/processPOST /ingestapi/tabletype/users/process
What to do:
Send the process request.
Save the returned
ingestId. It is required to track the run result.
Expected result:
The response returns a new
ingestId.If processing cannot start, the response explains whether a run is already in progress, no schema exists yet, or the uploaded CSV file is missing.
If the endpoint reports that the file is already being processed, do not start another run. Use the ingestion ID from the error message to monitor the existing run.
Step 6: Monitor the Run Status
Use the ingestId to check the run state.
Use:
GET /ingestapi/status/{ingestId}(see Get ingest status)
What to do:
Poll the endpoint until the status reaches a final state.
If the run fails, start it again.
Expected result:
You know whether the run completed successfully or failed.
NOTE: The
RPT_EnrichedDevicesandRPT_EnrichedUsersreport views are available only after the first ingest run for that table type completes successfully. Until then, dashboards, groups, and queries that use these views can show errors. Before you use the views, make sure that the run status shows a successful run.
Step 7: Remove Uploaded or Current Ingest Data When Needed
If you need to reset the staged file or clear current ingested data, use the delete endpoint for the relevant table type.
Use one of these endpoints (see Delete ingest data):
DELETE /ingestapi/tabletype/devicesDELETE /ingestapi/tabletype/users
Use this endpoint carefully. It removes the current uploaded file and ingested data for that table type.
Expected result:
The current ingest data for the selected table type is removed.
Step 8: Review Ingest History
Use the history endpoint to confirm completed work and review prior runs.
Use:
GET /ingestapi/history(see Get ingest history)
Recommended uses:
Review recent runs.
Filter by
categoryto focus onusersordevices.Filter by
startTimeandendTimewhen investigating a specific time range.
Expected result:
You can confirm start time and end time of each run.
Step 9: Review Audit Records
Use the Audit API to verify who performed ingest actions.
Use:
GET /auditapi/ingest/actions(see Get ingest action audit records)GET /auditapi/ingest/actions/{actionType}(see Get ingest action audit records by type)
Recommended uses:
Review all ingest-related actions in a time range.
Filter by
runByfor operator-specific auditing.Filter by
actionType.
Expected result:
You can see who ran ingest actions, from which IP address, and when.
Ingest API Troubleshooting
Schema Errors
Error Message | Reason | How to Fix |
|---|---|---|
KeyColumn is required for tableType 'devices'. | A device schema was submitted without a device key column. | Add |
Length is required for string column '{columnName}'. | A string column was defined without a length. | Add a positive |
The key column was defined with name '{name}' and KeyType '{keyType}'. No column was found with the name '{name}' and type '{requiredType}'. | The declared device key column does not match a valid column definition in the schema. | Make sure the key column also appears in |
Upload Errors
Error Message | Reason | How to Fix |
|---|---|---|
The column name 'WGUID' is reserved and cannot be used. | The CSV header included | Remove the For device imports, use the configured key column such as |
The number of the header columns does not match with the row '{rowNum}'. | At least one data row has a different number of values than the header. |
|
No error message. The upload response lists the same column name under both | The CSV header has spaces before or after the column name. | Remove the spaces from the header name in the CSV file and upload the file again. See Prepare the CSV File. |
Process Errors
Error Message | Reason | How to Fix |
|---|---|---|
The uploaded file could not be found. Please upload the file before processing. | Processing was started before a CSV was uploaded, or the staged upload is no longer present. |
Or
|
There is currently no schema defined, please call the schema generation endpoint. | The process endpoint was called before a schema was created for the selected table type. |
|
The file is already being processed. Please wait for it to return. The current ingestion id is '{ingestId}'. | A process run for the same table type is already starting or running. |
|
The column '{column}' in csv was not found in the table definition. | The uploaded CSV contains a column that is not defined in the saved ingest schema. |
|
The number of columns in the CSV do not match a number of columns that previously were defined. Line: '{currentLineNumber}' | A data row does not match the number of columns expected from the saved schema. |
|
The data '{value}' of the column '{columnName}' cannot be parsed to '{dataType}' data type. Line: '{currentLineNumber}' | A value does not match the type defined in the saved schema. |
Common causes:
See Prepare the CSV File. |
FAQ
What is Data Ingest used for?
Data Ingest is used to supplement SysTrack data with customer-provided user and device metadata, within tenant sizing and CSV import limits.
Is Data Ingest available at no additional cost?
Yes. Data Ingest is available at no additional cost if you have the required API access.
Do you need special permissions to use Data Ingest?
A valid API key is required to access and use Data Ingest. Once configured, imports and updates can be performed through the supported APIs.
Which file formats are supported?
Only CSV files are supported.
What limitations apply to Data Ingest?
Only CSV files are supported.
Up to 2,000 bytes of metadata per row can be uploaded.
A CSV file can contain records for up to 125% of the current user or device count within the tenant.
User and device imports are managed as separate CSV files and stored in separate report views.
Can imported data be updated after upload?
Yes. Imported data can be updated through the API as often as needed.
What happens when a new CSV file is uploaded?
Uploading a new CSV file allows you to update the existing imported data. The ingestion process converts the uploaded CSV file into a corresponding report view.
If you upload a new CSV file before processing the previous staged file, the new upload replaces the earlier staged file.
After data has been ingested, you can delete previously imported data or upload a new CSV file to replace or update the existing imported dataset.
Does a new CSV file replace previously imported data?
The imported dataset can be refreshed by uploading a new CSV file. The newly uploaded file becomes the source for the corresponding imported report view.
How is imported data stored?
User imports are stored in a dedicated report view.
Device imports are stored in a separate report view.
Each import is maintained independently and can be managed separately.