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Day: May 18, 2022

Protecting ML Models and IP

Pete Warden has some advice:

Over the last decade I’ve helped hundreds of product teams ship ML-based products, inside and outside of Google, and one of the most frequent questions I got was “How do I protect my models?”. This usually came from executives, and digging deeper it became clear they were most worried about competitors gaining an advantage from what we released. This worry is completely understandable, because modern machine learning has become essential for many applications so quickly that best practices haven’t had time to settle and spread. The answers are complex and depend to some extent on your exact threat models, but if you want a summary of the advice I usually give it boils down to:

– Treat your training data like you do your traditional source code.

-Treat your model files like compiled executables.

Read on to see why Pete came to this as the appropriate answer, as well as what I have to consider a sly mention of duck boat tours.

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Low-Code Churn Prediction with Synapse Analytics

Gavita Regunath shows off a capability in Azure Synapse Analytics:

We will build a machine learning solution to predict churn using Azure Synapse Analytics and Azure Machine Learning.

Azure Synapse Analytics is Microsoft’s limitless analytics platform that combines enterprise data warehousing and big data analytics. In simple terms, it is a one-stop-shop that allows you to ingest, prepare, and manage data that can then be used for machine learning and business intelligence, all from a single place. It provides a unified platform and encourages collaboration between data and machine learning professionals.

This article will show you how to build an end-to-end solution to train a machine learning model from Azure Synapse analytics using AutoML functionality within Azure Machine Learning. Using the T-SQL Predict statement, we can then use the trained machine model to make predictions against the churn dataset stored in the SQL Pool table. One of the key benefits of working from within Azure Synapse is that all the necessary steps required to train and make predictions with the trained model can be done from a single platform, Azure Synapse.

Click through for the three-step process and a demonstration.

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Adding Dynamic Hierarchies in Power BI

Kristyna Hughes makes use of the Tabular Object Model:

Power BI hierarchies are a powerful and easy way to enable end users to dig deeper into their visuals and data. While hierarchies can be a useful resource for self-serve analytics, maintaining hierarchies can be a pain as new levels get added or removed. Thankfully, if you have Power BI premium you can use the XMLA endpoint to add code into existing .NET applications to dynamically add or remove levels from hierarchies as they are created/removed in your application.

Unfortunately, while we can manipulate, add, and delete hierarchies and their levels, visuals already containing the hierarchy will not be automatically adjusted with any new levels/ordinals.

In spite of that limitation, click through to check out what you can do.

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Managing Power BI Tenant Settings

Melissa Coates takes us through tenant settings management in the Power BI Service:

The tenant settings in the admin portal of the Power BI Service are incredibly important. The tenant settings include a wide-ranging number of things that significantly affect the user experience. It’s really important to manage the tenant settings effectively.In this post I’m going to talk about the process you should go through for reviewing and specifying your tenant settings.

The following is a high-level overview of what’s involved:

Read on for a helpful image as well as a flow of what to think about before you act.

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Returning an Empty Table in Power Query

Imke Feldmann doesn’t want you to leave empty-handed:

When your query returns an error, sometimes it could make sense to return an empty table instead of a simple error message. And ideally, this table has the same columns and types than the table that would have been returned without the error. Check out Chris Webbs article about it here: Chris Webb’s BI Blog: Handling Data Source Errors In Power Query Chris Webb’s BI Blog (

Read on for a function which generates an empty replica table based on some other table.

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Installing mssql-cli on Ubuntu 22.04

Andrew Pruski runs into a problem:

I really like the mssql-cli tool. I use it pretty much everyday however it seems like it’s not being maintained anymore and as such, there are issues when trying to install it on Ubuntu 22.04.

The issue with Ubuntu 22.04 is that it has python 3.10 installed by default which the current mssql-cli is not compatible with. I did try installing previous versions of python (3.8 and 3.9) but had no luck so kept the default version.

Click through to see what Andrew did to resolve the problem. It looks like there’s already a GitHub issue for this that was opened back in October.

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