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Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-create-data-assets.md
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When you create a data asset in Azure Machine Learning, you'll need to specify a `path` parameter that points to its location. Below is a table that shows the different data locations supported in Azure Machine Learning and examples for the `path` parameter:
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|Location | Examples |
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|---------|---------|
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|A path on your local computer |`./home/username/data/my_data`|
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|A path on a datastore |`azureml://datastores/<data_store_name>/paths/<path>`|
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|A path on a public http(s) server |`https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv`|
|A path on your local computer |`./home/username/data/my_data`||
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|A path on a datastore |`azureml://datastores/<data_store_name>/paths/<path>`||
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|A path on a public http(s) server |`https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv`| https path pointing to a folder is not supported since https is not a filesystem. Please use other formats(wasbs/abfss/adl) instead for folder type of data.|
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|A path on Azure Storage |`wasbs://<containername>@<accountname>.blob.core.windows.net/<path_to_data>/` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<path>` <br> `adl://<accountname>.azuredatalakestore.net/<path_to_data>/`||
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> [!NOTE]
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> [!IMPORTANT]
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> The studio only supports browsing of credential-less ADLS Gen 2 datastores.
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> [!IMPORTANT]
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> Authentication to access data will use user's identity or compute MSI by default.
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## Data asset types
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-[**URIs**](#Create a `uri_folder` data asset) - A **U**niform **R**esource **I**dentifier that is a reference to a storage location on your local computer or in the cloud that makes it easy to access data in your jobs. Azure Machine Learning distinguishes two types of URIs:`uri_file` and `uri_folder`.
Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-read-write-data-v2.md
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When you provide a data input/output to a Job, you'll need to specify a `path` parameter that points to the data location. Below is a table that shows the different data locations supported in Azure Machine Learning and examples for the `path` parameter:
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|Location | Examples |
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|---------|---------|
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|A path on your local computer |`./home/username/data/my_data`|
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|A path on a public http(s) server |`https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv`|
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|A path on Azure Storage |`https://<account_name>.blob.core.windows.net/<container_name>/<path>` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<path>`|
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|A path on a Datastore |`azureml://datastores/<data_store_name>/paths/<path>`|
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|A path to a Data Asset |`azureml:<my_data>:<version>`|
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|Location | Examples | Notes|
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|---------|---------|---------|
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|A path on your local computer |`./home/username/data/my_data`||
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|A path on a public http(s) server |`https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv`| https path pointing to a folder is not supported since https is not a filesystem. Please use other formats(wasbs/abfss/adl) instead for folder type of data.|
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|A path on Azure Storage |`wasbs://<containername>@<accountname>.blob.core.windows.net/<path_to_data>/` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<path>`<br> `adl://<accountname>.azuredatalakestore.net/<path_to_data>/`||
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|A path on a Datastore |`azureml://datastores/<data_store_name>/paths/<path>`||
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|A path to a Data Asset |`azureml:<my_data>:<version>`||
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## Supported modes
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