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high level overview of the different use cases for Predictive Insights, Optimizer and Plan IQ
Is there a slide or resource I can refer to that: describes a high level overview of the different use cases for Predictive Insights, Optimizer and Plan IQ My understnading is : PlanIQ - Uses time based data (historic, related or master) to predict future results Predictive insights - Uses current search trends to evaluate…
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Plan IQ historical data in data collection - should it only contain [target data]?
Hi I'm curious about how to set the data collection - historical data. I want to make a prediction about revenue, and have some historical data. but I also have other historical data, which is revenue and promotion, and those data is related to the revenue data (this is known from other analysis) but I cannot make any…
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PlanIQ clarification - with data collection (historical data and related data)
Hello. I'm new to PlanIQ feature and confused with the error message below- the one says "the related data does not include forward looking information" my understand on historical data is, that I have to ONLY feed the historical data of objective variable (in this case, I tried to make a forecast on revenue in 2019, so I…
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PlanIQ [internal server error] Meaning
Hello while making the data collection for PlanIQ, I faced with "internal server error" and failed data collection. By adjusting the original module (by putting time dimensions for row), the issue is now solved, but I'm now confused about the term "internal server error" since the term seems to be broader than "your module…
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Anaplan’s Intelligence Capabilities Deliver Real-Time Insights
Rapid and unanticipated market changes require business leaders to leverage internal and external data to predict the future, rather than extrapolate from the past, in order to orchestrate the business performance needed for tomorrow. A modern, intuitive, intelligent, and holistic approach to planning that breaks down…
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Start Here - PlanIQ Overview and Resources
Start here: PlanIQ overview and resources Are you are interested in starting time series forecasting with PlanIQ on Anaplan, but you don’t know where to start? You have come to the right place! Here are two resources to get you started: Start your journey with Anaplan PlanIQ! What is PlanIQ, who is it for, use case…
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PlanIQ Best Practices
PlanIQ Best Practices In the articles below, you will find many of PlanIQ's best practices. Learn how to deal with outliers, how to manage NULL values, how to use forecasting quantiles and many more! PlanIQ - Deep dive on the Algorithms under the hood Learn more about Baseline time series algorithms, Flexible local…
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Forecast action in PlanIQ
Hi, I tried implementing the basic setup of PlanIQ with a simple flat list . I have created the historical module using the same flat list with time dimension and created the export action for the same and used it for the data collection. The data collection was successful. Then, I have created the forecast model using the…
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Plan IQ - Taking forecasting to the next level
We launched Plan IQ at our Anaplan Live / Digital CPX with the interest around it being incredible. How does it help customers? The main areas for me; • Provides a business friendly approach to intelligent forecasting insights and recommendations to accelerate decisions • Can leverage internal and external data to…
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PlanIQ
If you were able to join us for CPX then you would have heard the exciting news that PlanIQ is our latest release - putting the power of intelligent forecasting, with an in-built predictive engine, directly into the hands of the users. Amazon Forecast is the first predictive engine to integrate with PlanIQ and the product…
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PlanIQ - Dealing with outliers
Outliers in time series data are values that differ greatly from the rest of the time series. Outliers can be caused by measurement errors, data entry errors, organic real occurrences such as seasonal effects and other reasons. Since outlier values could impact the accuracy of the predictions produced by forecast models…
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PlanIQ - How to manage NULL values?
In real-world forecasting applications, it is common for datasets to contain null values, which represent missing values for specific points in time. There can be multiple reasons for the presence of missing values. For example, a transaction may not have occurred, or a device or service that monitors data may have…
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PlanIQ - Algorithm selection by item: mix and match your forecast
What is algorithm selection by item? Algorithm selection by item is the use of more than one algorithm to produce optimal forecasts across multiple items. Instead of using forecasts generated by a single algorithm for all items in the historical data module, where the algorithm is selected based on best overall performance…
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PlanIQ - New product introduction: all you ever wondered about starting your forecast from scratch
New Product Introduction (NPI) or Cold Start in time series forecasting is a scenario where forecasts should be produced for new items (e.g. new products, new SKUs) for which there is limited historical data, or no historical data at all. Items with no historical data In scenarios where the new items have no historical…
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PlanIQ - How to use item attributes to refine your forecast
Metadata attributes are static, non-time dependent categorical text features that describe the items in the historical time series data. Examples for attributes could be style, category, geographic location, size, item hierarchy level etc. The advanced neural network machine learning algorithms supported by PlanIQ can…
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OEG Best Practice: PlanIQ: Design and build your item list for forecasting
* What is the best practice for concatenation in Anaplan? * Step-by-step overview * Level 1 – code inefficient * Level 2 – code better * Level 3 – Code to use * Level 4 – Optimized code to use * How do we handle items with limited to no history? * Adding “Cold Start” Items Before diving in, if you need to refresh your…
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PlanIQ for Predictive Forecasting and Agile Scenario Planning
Anaplan Extends Intelligence Capabilities with PlanIQ for Predictive Forecasting and Agile Scenario Planning September 15, 2020 New integration with Amazon Forecast arms business users with easy to understand machine learning-driven insights and predictions SAN FRANCISCO, CA, SEPTEMBER 15, 2020 — Anaplan, Inc. (NYSE:…