As we continue working with Azure Synapse Analytics on Peruvian voting data, as I have posted before, we are extending to creating an external table from the ground up, that points to existing data in the Data Lake Store.

This post will show how to create an external table that will point to a folder hierarchy that contains data in plain text (CSV format). All files inside the folder will be considered for this example.

This is an extension of a prior post that shows how to create an external table in CSV format with Azure Synapse Analytics. Most of the steps equivalent, with the exception of the file format.

This post will show how to create an external table in Parquet format using Azure Synapse Analytics. The creation of an external table will place data inside a folder in the Data Lake Store, that has to be specified. The format can be plain text or parquet. Additional information can be found in the Microsoft documentation link.

This is a continuation from a prior post that allows users leverage Peruvian voting data with Azure Synapse Serverless.

This post will show how to create an external table using Azure Synapse Analytics. The creation of an external table will place data inside a folder in the Data Lake Store, that has to be specified. The format can be plain text or parquet. Additional information can be found in the Microsoft documentation link.

Last week I published a post that allows users use Peruvian voting data to Azure Synapse Serverless.

This post will allow us take assumptions to visualize votes on the 1st round that aligned to either left or right, and compare them to the 2nd round, where Pedro Castillo (Perú Libre) represents the left, and Keiko Fujimori (Fuerza Popular) represents the right.