TensorFlow I/O's BigQuery Reader allows you to directly read data from BigQuery tables into your TensorFlow model without the need to export the data to a separate file format. This can minimize any bottlenecks during the data ingestion stage and also it can increase the scalability. By using BigQuery Reader, you can easily read large amounts of data from BigQuery and use it to train your model without having to worry about the performance impact of reading from a dataframe or CSV file.
You can use the tfio.BigQueryRecordDataset which will return a dataset of dictionaries, and where each key corresponds to a table column and each value corresponds to the value in that column.