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Use the [`from_sql_query()`](https://docs.microsoft.com/python/api/azureml-core/azureml.data.dataset_factory.tabulardatasetfactory?view=azure-ml-py#from-sql-query-query--validate-true--set-column-types-none-) method on `TabularDatasetFactory` class to read from Azure SQL Database.
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```Python
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from azureml.core import Dataset, Datastore
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# create tabular dataset from a SQL database in datastore
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sql_datastore = Datastore.get(workspace, 'mssql')
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tabular = Dataset.Tabular.from_sql_query((sql_datastore, 'SELECT * FROM my_table'))
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```
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Use the [`with_timestamp_columns()`](https://docs.microsoft.com/python/api/azureml-core/azureml.data.tabulardataset?view=azure-ml-py#with-timestamp-columns-fine-grain-timestamp--coarse-grain-timestamp-none--validate-false-) method on `TabularDataset` class to enable easy and efficient filtering by time. More examples and details can be found [here](http://aka.ms/azureml-tsd-notebook).
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