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1
Intro
2
Presenter Introduction
3
Session Outline
4
The History of Forecasting
5
Describing the Data Mining Process
6
SQL Server 2014 Analysis Services
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Microsoft Time Series Algorithm ARIMA Algorithm
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Time Series Model Definition
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Time Series Data
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Characteristics of Time Series Models
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Time Series Model Querying
12
Determining Prediction Accuracy (Continued)
13
Algorithm Parameters
14
Business Scenarios
15
Summary
Description:
Explore time series forecasting techniques in this comprehensive conference talk from PASS Data Community Summit. Learn how to leverage SQL Server Analysis Services' Microsoft Time Series algorithm for accurate predictions based on historical data. Discover the process of preparing data, creating and querying time series data mining models, and interpreting results. Gain insights into various demonstration models using Visual Studio and Excel data mining add-ins for self-service scenarios. Delve into topics such as the history of forecasting, data mining processes, ARIMA algorithm, model definition, data characteristics, querying techniques, prediction accuracy, algorithm parameters, and real-world business applications. Equip yourself with valuable skills to predict future trends and make data-driven decisions in various fields, including stock market analysis.

Introduction to Time Series Forecasting

PASS Data Community Summit
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