---
title: "OneLake"
slug: "onelake"
description: "Export data from any source to OneLake as CSV, JSON, JSONL, or Parquet files with Dataddo. No coding required."
updated: 2026-07-26T12:58:21Z
published: 2026-07-26T12:58:21Z
canonical: "docs.dataddo.com/onelake"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt
> Use this file to discover all available pages before exploring further.

# OneLake

OneLake is Microsoft's unified data lake for the Microsoft Fabric platform, designed to store all organizational data in a single, secure, and accessible location. It enables data sharing and collaboration across teams and tools by standardizing storage on the Delta Parquet format and integrating natively with Fabric services.

## Authorize Connection to OneLake

Authorize the connection so Dataddo can write files to OneLake:

| Field | Description |
| --- | --- |
| A name for this authorizer in Dataddo | A label so you can recognize the connection later. |
| Workspace GUID | Workspace GUID |
| Lakehouse GUID | Lakehouse GUID |
| Tenant ID | Tenant ID |
| Client ID | Client ID |
| Client Secret | Client Secret |

Dataddo validates the connection when you save it.

## Create an OneLake Destination

Go to Destinations, click Create Destination, and select OneLake. Give the destination a name, choose the authorizer, then set:

| Field | Description |
| --- | --- |
| Path | Path |

Click Save.

## Supported File Formats

Each flow run writes the data as a file in the format you pick.

| Format | Description |
| --- | --- |
| `csv` | OneLake writes the data as CSV files. |
| `json` | OneLake writes the data as JSON files. |
| `jsonl` | OneLake writes the data as JSONL files. |
| `parquet` | OneLake writes the data as PARQUET files. |

For CSV you can set the delimiter, header row, and date formatting. For Parquet, JSON, and JSONL you can set the timestamp unit.

## File Naming

You can also build a custom filename with these placeholders (see [Dynamic File Naming Patterns](/docs/dynamic-file-naming-patterns) for the full list):

- `{{objectLabel}}` and `{{objectId}}`: the flow name and id.
- `{{today}}` and `{{yesterday}}`: the run date.
- `{{dateRangeStart}}` and `{{dateRangeEnd}}`: the bounds of the flow's date range.
- Date-range expressions such as `{{1d1}}` (yesterday) or `{{90d1}}` (the last 90 days through yesterday).
- Add a date format after a `|`, for example `{{today|Ymd}}` gives `20201231` and `{{1d1|Y-m-d}}` gives `2020-12-31`.

## File Partitioning

File partitioning splits a large dataset into smaller files based on a criterion such as date, which improves how a data lake organizes and queries the data (see [Data Lake Ingestion](/docs/data-lake-ingestion)). In Dataddo you partition by putting date variables from File Naming into the file name, so each flow run writes its own dated file.

For example, `events_{{1d1|Y-m-d}}.parquet` writes one Parquet file per day, so a lake engine such as OneLake can read the set of files as a date-partitioned dataset. Pick a file format like Parquet or CSV that your lake reads, and schedule the flow to match the partition period (for example daily for a daily date token).

## Write Modes

Each flow run writes a file at the resolved name. The default is `truncate_insert`: `insert` keeps writing new files, and `truncate_insert` replaces the file at the same name.

## How Data Is Delivered

Every run produces one file at the resolved name. A date-stamped name accumulates a new snapshot file per run, which is the pattern described in [Data Lake Ingestion](/docs/data-lake-ingestion).

## How to Create a Flow to OneLake

1. Go to Flows and click Create Flow.
2. Add one or more sources.
3. Add OneLake as the destination and pick the authorizer.
4. Choose the file format and the file name.
5. Set the schedule and click Save.

## Troubleshooting

### Cannot connect to OneLake

Dataddo cannot reach OneLake. Check the credentials, path, and permissions in the authorizer and destination, and make sure OneLake is reachable by Dataddo.

### File is not created

The account used by Dataddo lacks write permission on the target path. Grant write access to the folder or bucket and restart the flow.

## Related Articles

- [Data Backfilling to Storages](https://docs.dataddo.com/docs/data-backfilling-to-storages)
- [Write Modes](https://docs.dataddo.com/docs/data-storages#write-modes)
- [Implementation of Batch Ingestion to Data Warehouses](https://docs.dataddo.com/docs/ingestion-to-data-warehouses)
- [Network Access Control List (ACL) Configuration](https://docs.dataddo.com/docs/network-acl)
- [SSH Tunnelling](https://docs.dataddo.com/docs/ssh-tunnelling)
- [Data Transformations](https://docs.dataddo.com/docs/data-transformations)
- [Data Quality Firewall](https://docs.dataddo.com/docs/data-quality-firewall)