Planiq

这篇文章是为了provide guidance that helps PlanIQ practitioners understand how the data in the "data collection" in PlanIQ is used in the training and running of a forecast model. This article also explains how PlanIQ users can change the data source for existing forecast models. What is the "data collection"? Data collection is exactly what the name implies - a collection of data. Today, data collections reference data that is hosted in Anaplan and pulled into PlanIQ via their associated export actions. When data collections are created, PlanIQ exports the relevant data sets from Anaplan and analyzes them. This analysis allows PlanIQ to make sure that the data is properly formatted, to look for any possible issues or errors in the data, and to identify which algorithms and horizons can be supported for the given data. This process eliminates a significant chunk of manual data prep time that is required for more technical intelligent forecasting tools. This checkpoint allows PlanIQ users to make sure everything is in order before running a forecast. If the process finds any issues, the user can always update the data in Anaplan and re-run data assembly of the data collection to resolve the problems. What happens with the data when the "forecast model" is being created? When forecast models are created, PlanIQ is training the algorithms based on the historical data. During this process, PlanIQ pulls the latest data from the data collection. This means that even if the data collection was created some time ago, PlanIQ will always train its models on the most up to date actuals. A tip for building PlanIQ into your planning process: If you want to perform a series of rolling forecasts, it's better to train all the models from the same "point in time" of the rolling forecast. What happens with the data when the forecast action is run? When forecast actions are run, PlanIQ pulls the latest data from the data collection. So, as new actuals are added to the source model in Anaplan, the forecast will be generated using that data. As part of the forecast action execution, PlanIQ compares its previous forecasts with new actuals to make sure that model accuracy stays consistent. You will receive a warning message when you run the forecast action if PlanIQ sees a degradation in the PlanIQ model quality metric (see Anapedia article on PlanIQ metrics). What if I want to train a new forecast model? There might be several reasons to train a new forecast model, including: A long time has passed since the previous model has been used and you want to retrain the model with the latest data. The engine noticed changes in forecast quality and you want to re-train the model to review and update the quality metrics. You want to use a new data collection for forecast and therefore need to retrain the model with the new data. To retrain the model, you must create a new version of the model. This can easily be done by duplicating the forecast model in the PlanIQ interface. PlanIQ will pre-populate all the configuration options so you only need to provide a new name for the model. If you'd like to change the data source for the model, you can point it to a different data collection. Once your new model has been trained, if your forecast action is already operationalized and/or scheduled, you can edit it and point it to the new forecast model. Voila! ... 查看更多

我想分享一些有关如何可视化预测的想法。我鼓励每个人都不要在任何分析中折扣可视化的价值。我们如何呈现数据以及如何允许用户与该数据进行交互对于推动更好的决策至关重要。以下是我将Planiq可视化构建到Anaplan应用程序中的几种方法，以帮助用户更好地了解数据告诉我们的内容。希望这能激发您同样的事情！ ... 查看更多

我希望能够在Anaplan模块中进行预测模型评估。是否可以访问预测模型进行回测窗口结果？ ... 查看更多

虽然最初打算在纽约市举行，但围绕Covid的全球条件已将M5预测会议转移到虚拟活动。尽管情况是不幸的，但玻璃杯的一半是，会议现在向更大的听众开放。上次M会议于2018年举行，我发现这一经历非常有价值（我在这里写了这一点）。如果您下周有空闲时间，我强烈建议您参加一些会议。这是向预测社区中的领导者学习的绝佳机会。注册会议议程是什么M5会议？M5会议议程包括主要软件/技术公司（Google，Kaggle，Walmart，Microsoft，Amazon，Facebook，SAS和Target）的杰出演讲者，以及顶级大学的领先学者。它以开发人员本身对M5竞争的三种最准确方法的介绍，他们还将讨论他人如何实施他们的方法。他们的代码将在GitHub上免费提供。会议涵盖了预测的所有关键方面，包括结合方法和判断调整，特别强调机器学习和统计预测方法的比较以及对不确定性的评估。 Who should attend? Professionals working in companies or non-profit organizations in jobs that involve preparing forecasts and estimating uncertainty Financial managers who prepare budgets and the financial requirements for their firms Government officials requiring to predict receipts and expenses Hedge fund and other related managers who need to predict stock and other market variables Production managers requiring forecasts for their production planning activities Inventory managers who must predict the demand for a large number of items to figure out optimal inventory levels and reordering points Logistics and transportation managers whose scheduling tasks need forecasts Academics teaching forecasting and related courses Students interested in forecasting for their courses or for their research I hope to see you there! ... 查看更多

Predictive forecasting tools like PlanIQ can create incredible opportunities for businesses. If we want the outputs of a forecast model to create value, it's critical that we evaluate the model and present information about its performance in an elegant way that is easy for planners to understand. I spent some time putting together a simple dashboard that is both information-rich and easy to consume. I've attached a video walkthrough along with some thoughts. Let me know what you think! ... 查看更多