Strategy One

Time Series Forecasting Troubleshooting

The limitations addressed below are associated with the MicroStrategy ONE Update 11 release. Strategy is actively working on enhancing this feature, and some of these limitations may be addressed in upcoming versions. For the latest information and updates, we encourage you to visit this page periodically. By understanding and considering these limitations, you can make the most of the forecasting feature and achieve meaningful insights.

  • Attribute and Metric Requirements For accurate predictions, make sure to use exactly one attribute and one metric in your questions to be placed in the X and Y axes, respectively. Queries not meeting this requirement may not yield optimal forecasts.

  • Break By Attributes: When you include a break by attribute to represent forecasts for multiple elements such as when you forecast sales revenue for the next 12 months for each employee, ensure the number of elements (employees in this case) in the attribute are limited to enhance readability of the analysis results.

  • Consider Attribute Forms The attribute used for forecasting should have at least one form with a type of date, datetime, or integer. Timestamp data is not supported.

  • Timezone-based Attributes Forecasting with timezone-based smart attributes is not currently supported.

  • Consolidation and Grouping Forecasting against consolidated or grouped attribute elements is not possible at this time.

  • Granularity Level Forecasts are not available for less than daily level data (such as hourly, minute, or second intervals).

  • Integer-based Forecasting Be cautious when using integer-based time representations in your queries (such as 202101 for January 2021). Strategy does not automatically convert these time representations to date/time format, leading to unexpected results such as 202113 or 202114.

  • Maximum Forecasting Points You can forecast up to 100 future data points. This limit helps ensure efficiency and accurate predictions.

  • Hindcasting and Tuning Currently, hindcasting against existing data is not supported. Additionally, adjusting algorithm hyper-parameters can only be done via Auto in the current release. For example, you can tune the confidence interval by asking Auto to forecast with a specific confidence level, but this is not available in the dashboard authoring interface yet.