In-Database Python Analytics for SQL Developers

The goal of this walkthrough is to provide SQL programmers with hands-on experience building a machine learning solution in SQL Server. In this walkthrough, you'll learn how to incorporate Python into an application by adding Python code to stored procedures.

Note

Prefer R? See this tutorial, which provides a similar solution but uses R, and can eb run in either SQL Server 2016 or SQL Server 2017.

Overview

The process of building an end to end solution typically consists of obtaining and cleaning data, data exploration and feature engineering, model training and tuning, and finally deployment of the model in production. Development and testing of the actual code is best performed using a dedicated development environment, such as these Python tools:

After you have created and tested the solution in the IDE, you can deploy the Python code to SQL Server using Transact-SQL stored procedures in the familiar environment of Management Studio.

In this walkthrough, we'll assume that you have been given all the Python code needed for the solution, and you'll focus on building and deploying the solution using SQL Server.

Note

We recommend that you do not use SQL Server Management Studio to write or test Python code. If the code that you embed in a stored procedure has any problems, the information that is returned from the stored procedure is usually inadequate to understand the cause of the error.

Scenario

This walkthrough uses the well-known NYC Taxi data set. To make this walkthrough quick and easy, the data is sampled. Using this data, you'll create a binary classification model that predicts whether a particular trip is likely to get a tip or not, based on columns such as the time of day, distance, and pick-up location.

Requirements

This walkthrough is intended for users who are already familiar with fundamental database operations, such as creating databases and tables, importing data into tables, and creating SQL queries.

All Python code is provided. An experienced SQL programmer should be able to complete this walkthrough by using Transact-SQL in SQL Server Management Studio or by running the provided PowerShell scripts.

Before starting the walkthrough, you must complete these preparations:

  • Install an instance of SQL Server 2017 with Machine Learning Services and Python enabled (requires CTP 2.0 or later).
  • The login that you use for this walkthrough must have permissions to create databases and other objects, to upload data, select data, and run stored procedures.

Next Step

Step 1: Download the Sample Data

See Also

Machine Learning Services with Python