Time Series in Microsoft SQL Server

In a previous blog post, it was said that new research was initiated in order to design and develop a framework for time series using agent technology. 

In order to proceed with the research, it was decided to perform of feature analysis in various tools such as Microsoft SQL Server, Weka, Orange, Azure Machine Learning and Rapid Data Miner. Please comment if you have better tools. 

The following figure shows the components for Microsoft SQL Server 

Microsoft SQL Server supports three types of algorithms such as ARIMA, ARTxp and Mixed. ARTxP and Mixed are supported for the cross prediction. Further, ARTxP works well for short term predictions while the ARIMA will work for long term predictions.

Fast Fourier Series is used to detect the seasonality in SQL Server. Missing values will be identified only when there are multiple time series are presented. Mean, Constant, Previous and Same curvature are the techniques used to replace the missing values. 

Further, Microsoft SQL Server has the capability of using the predicted values for further predictions.  

References

https://www.sqlshack.com/microsoft-time-series-in-sql-server/

https://docs.microsoft.com/en-us/analysis-services/data-mining/microsoft-time-series-algorithm

https://docs.microsoft.com/en-us/analysis-services/data-mining/time-series-model-query-examples

https://docs.microsoft.com/en-us/analysis-services/data-mining/microsoft-time-series-algorithm-technical-reference

https://docs.microsoft.com/en-us/analysis-services/data-mining/mining-model-content-for-time-series-models-analysis-services-data-mining

https://docs.microsoft.com/en-us/analysis-services/data-mining/browse-a-model-using-the-microsoft-time-series-viewer

https://docs.microsoft.com/en-us/sql/dmx/data-mining-extensions-dmx-function-reference

Further, every month Cheatsheet for the Time Series will be released. Please let me know your thoughts.