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Curated SQL Posts

Extracting Refresh Metrics for a Power BI Workspace

Marc Lelijveld wants to pull some metrics:

In the Power BI service, you can easily look at refresh times for an individual dataset or dataflow. There are many different reasons why these metrics are important to you as a dataset or dataflow owner. For example, you may bump into refresh time-outs or unfortunate errors. There are many good reasons to think about why you want to have more insights in your refresh metrics.

Having that said, it can be a pain to look at these metrics every day. Power BI already offers a way to send automatic notification in case of a refresh failure. Though, I would personally prefer to have more insights in all my refresh metrics, whether they are failing or succeeding.

In this blog I want to share a way how you can export all refresh metrics for your datasets and dataflows using a PowerShell script.

Click through to see how and to get a copy of the script.

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Running an mlflow Server on Azure

Paul Hernandez configures mlflow on Azure using platform-as-a-service offerings:

It is indisputable true that mlflow came to make life a lot easier not only for data scientists but also for data engineers, architects among others. There is a very helpful list of tutorials and example in the official mlflow docs. You can just download it, open a console and start using it locally on your computer. This is the fastest way to getting started. However, as soon as you progress and introduce mlflow in your team, or you want to use it extensively for yourself, some components should be deployed outside your laptop.

To exercise a deployment setup and since I own azure experience, I decided to provision a couple of resources in the cloud to deploy the model registry and store the data produced by the tracking server.

I concur on the power of mlflow.

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String Modification in T-SQL

Steve Jones answers a question:

Recently I ran across a question posted by a beginner on the Internet and thought this would be a good, basic topic to cover. The question was: how can I replace a value in a comma separated string in a table?

This post covers the basics of this task.

Incidentally, this is where I say hey, that sounds like a failure in normalization. If you need to care about individual values in a collection, your value is not atomic. But that’s a bit of a tangent.

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Transforming Arrays in Azure Data Factory

Mark Kromer shows off a few functions in Azure Data Factory to modify data in arrays:

The first transformation function is map() and allows you to apply data flow scalar functions as the 2nd parameter to the map() function. In my case, I use upper() to uppercase every element in my string array: map(columnNames(),upper(#item))

Read on for more iteration and aggregation functions akin to map, reduce, and filter.

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When to Use Event Sourcing

Vikas Hazrati takes us through the pros and cons of using event sourcing for a project:

You would always get a ton of literature on Event Sourcing and CQRS. The key question is WHEN do you use it? Under what circumstances? Is your problem really in need of ES?

I would not go into the details of what Event Sourcing and CQRS is. The industry stalwarts have covered that in adequate detail. This post delves into battle-tested scenarios on where we should have used and otherwise ignored ES.

Click through for an analysis of pros and cons, as well as some advice on what it all means.

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Configuring a Linked Server to Oracle

Emanuele Meazzo needs to pull data from Oracle into SQL Server:

The most atrocious part of my search for glory was without doubt navigating all the packages to download and install for each component, between broken links and differences between the instructions and the actual content, it’s a mess.

It took a while, based on Emanuele’s tone. With SQL Server 2019, you can avoid some of this pain by using PolyBase. But for prior versions of SQL Server, your options are more limited.

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Top N with Others in Power BI

Marco Russo and Alberto Ferrari cover a pain point in Power BI:

The VisibleProducts variable contains a list of products for the selection currently displayed in the visual. In the example, we have the top 3 products for each Product Category included in our report. The ranking that is returned is only up to the value selected in the TopN parameter – for this reason, we can use the result of Ranking by Sales to filter the visual, including only the products ranked in the 1-to-TopN Value range. We use a filter in the Power BI filter pane to accomplish this task.

This is a common enough pattern that I do wish Power BI made it easy.

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