# Lesson 2: Building a Forecasting Scenario (Intermediate Data Mining Tutorial)

Applies To: SQL Server 2016 Preview

As the sales analyst for Adventure Works Cycles, you have been asked to forecast the sales of products for the next year. In particular, you have been asked to compare forecasts for the different regions and product lines. Additionally, you have been asked to determine whether sales of different products vary depending on the time of the year.

To find the requested information, in this lesson you will summarize the company's sales data at the monthly level, and you will also summarize sales figures by three regions: Europe, North America, and the Pacific.

After you complete the tasks in this lesson, you will be able to answer the following questions:

• How do the sales of different bike models change over time?

• Are there differences between the patterns for sales in the three regions?

• Can we forecast sales peaks?

The lesson can be completed in two parts:

• Part One introduces the basics of how to create and use a time series model.

• Part Two walks you through creation of a general time series model, based on all regions. You can use this general model for cross-prediction.

To complete the tasks in this lesson, which are listed below, you will use the AdventureWorksDW2012 data source that you created in Lesson 1: Creating the Intermediate Data Mining Solution (Intermediate Data Mining Tutorial).

Warning

The dates in the Adventure Works Cycles sample database have been updated for this release. If you use an earlier version of Adventure Works Cycles, you can build the model following these steps, but you might see different results.

Creating a Simple Forecasting Model

Creating a General Forecasting Model for Cross-Prediction

Adding a Data Source View for Forecasting (Intermediate Data Mining Tutorial)

Understanding the Requirements for a Time Series Model (Intermediate Data Mining Tutorial)

## All Lessons

Lesson 1: Creating the Intermediate Data Mining Solution (Intermediate Data Mining Tutorial)

Lesson 2: Forecasting Scenario (Intermediate Data Mining Tutorial)

Lesson 3: Building a Market Basket Scenario (Intermediate Data Mining Tutorial)

Lesson 4: Building a Sequence Clustering Scenario (Intermediate Data Mining Tutorial)

Lesson 5: Building Neural Network and Logistic Regression Models (Intermediate Data Mining Tutorial)