11/18/2023 0 Comments Tableau public server![]() Using parameters in MODEL_EXTENSION functions is a powerful way to analyze complex scenarios in real-time, evaluate the impact of different variables on outcomes, and enable more informed and effective decisions. When parameters are changed, the extension server is triggered to dynamically compute predictions for the new record, and the updated values are seamlessly updated in Tableau. For example, weather and economic patterns don’t make for good parameters since they’re outside of your control, whereas pricing, promotion, and marketing campaigns can be influenced and make sense as parameters. When doing this, make sure to only parameterize the fields you have influence over. This time with expressions replaced by their parameter counterparts. To enable users to test out different scenarios, we can create another calculated field. Then in the function, we define the deployed model we’re invoking, the model’s inputs, and the values passed from Tableau to the model which can be either aggregated or disaggregated.Īs for the output, we’ll receive a single column with the same number of rows as the amount we passed to the server (e.g., if we send 18 rows of data, we receive 18 rows back). Since this model returns a real number–the probability a customer will churn–the MODEL_EXTENSION_REAL function is used. In the example below, a likelihood to churn model was deployed. ![]() To decide which function to use, simply select the one matching the type of value the model returns. ![]() There are four variations of the model: MODEL_EXTENSION_BOOL, MODEL_EXTENSION_INT, MODEL_EXTENSION_REAL, and MODEL_EXTENSION_STR. Similar to creating a calculated field in Tableau, you call a MODEL_EXTENSION function with the parameters of the model name, the arguments, and the expression in the order expected by the model. Table calculations trigger upon interaction and allow for dynamic what-if analysis. Use Analytics Extensions in Table Calculations This data can then be scored, transformed, or augmented to facilitate dynamic exploration. At the root, an Analytics Extension is a server that you stand up to receive data from Tableau in real-time. Analytics Extensions do just that!Īnalytics Extensions provide the flexibility you need, letting you choose the programming languages and platform of your choice to build and fine-tune models that can be used for dynamic interaction and report building purposes. However, true return on investment is realized only when these models are used to leverage insights and make informed decisions that drive tangible value for the organization. Data scientists have a wide range of options to choose from when it comes to programming languages and platforms to build their predictive models. The typical analytical ecosystem has two silos: business intelligence and data science. Reference Materials Toggle sub-navigation.Teams and Organizations Toggle sub-navigation.Plans and Pricing Toggle sub-navigation.
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