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Author: Kevin Feasel

Linked Servers into Azure

Andy Brownsword goes old-school:

Connecting different versions of SQL Server can allow us to combine or transfer data between environments. This can become a challenge when the versions are really different.

Have you tried to connect SQL Server 2008 to a SQL database in Azure? – it can throw up a few curve balls.

In this post we’ll look at how to solve 3 of the issues you might come up against.

When reading the title, my first response was, “But why not use PolyBase?” Then Andy threw the SQL Server 2008 bit at me, and then my response was, “But why not use a product that isn’t nearly old enough to vote?”

Nonetheless, Andy does a great job of demonstrating how this would work, and it can work for later versions of SQL Server as well.

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Using Perspectives in Power BI

Koen Verbeeck turns his head just slightly:

Since the days of Analysis Services Multidimensional, we could create perspectives on our cubes. A perspective provides the opportunity to show only a selection of items (facts, dimensions, or measures) to a user. In Analysis Services Tabular, the same functionality is also available, and it helps to make complex models more digestible for end users. Right now, we have a big model in Power BI that covers different domains of our organization. We would like to create perspectives too, but is this even possible in Power BI?

Click through for the answer, as well as an important note that perspectives are for usability, not security.

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Azure AI and Content Safety

Tomaz Kastrun continues a series on Azure AI, this time focusing on content safety functionality. First up is an overview of the product:

Content safety Azure AI service detects harmful user-generated and AI-generated content in applications and services. It includes text and image APIs that allow you to detect harmful or inappropriate material. This service is , as all other services, easy to integrate to your app.

After that is how to access items via the SDK:

The Python SDK contains several functions to analyze text, images, and manage blocklists in text moderation. With the SDK you can cover the following scenarios:

  • Text moderation: Detect hate speech, sexual, selfharm, violence content in text.
  • Image moderation: Detect hate speech, sexual, selfharm, violence content in images.

Coming back to example we covered yesterday – moderating the text content – we can alternate the filtering to suit your needs. 

Click through to see how it works.

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Building and Deploying a Streamlit Data App

Ivan Palomares Carrascosa deploys an app:

This article will navigate you through the deployment of a simple machine learning (ML) for regression using Streamlit. This novel platform streamlines and simplifies deploying artifacts like ML systems as Web services.

I’ll leave aside my aside that linear regression isn’t machine learning. Click through to see how you can build a simple application in approximately 60 lines of code. This example shows off some of the simplicity in Streamlit’s design.

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The Posit Package Manager and diffify

Colin Gillespie and Myles Mitchell share some updates:

The latest release of Posit Package Manager introduces several enhancements, including:

  • Python Git Builders: Build Python packages (wheels) directly from Git.
  • Blocklists: Easily block specific packages or versions.
  • Improved Documentation: Clearer and more accessible information.

Read on for one more big change to Posit Package Manager, as well as how diffify fits into the mix.

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Re-Using Visual Formatting between Power BI Reports

Kurt Buhler does a bit of recycling:

If you build Power BI reports, then you know how much time it costs to format visuals so that they work and look the way that you want them to. This applies not only when you make new reports, but also when you need to maintain or make changes to existing ones. When a report gets fancy in its design (sometimes unnecessarily so, if we are frank), then, often, this is accompanied by a need for many formatting tweaks and changes. Inevitably, this formatting becomes time consuming (and sometimes frustrating) to deal with when there is a problem to fix or a modification to make. How can we make formatting and maintaining Power BI reports both more convenient and more efficient?

Read on for the answer.

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Recovering SQL Server Data via FlashArray Snapshot

Andy Yun does a bit of data recovery:

Almost all of us have experienced a time when someone incorrectly modifies or deletes a subset of data in a database. And usually the only recourse is to run a database restore to get the data that we need back.

But… what if we cannot simply run a RESTORE operation over the entire database. Maybe the accident occurred a few hours prior and you cannot roll everything back. You need to do a side-by-side RESTORE.

But… what if the database in question is absolutely massive and will take hours to restore? And what if your server doesn’t have enough available storage to fit a second copy of that database at all?

Andy has answers to these questions. Granted, they require some expensive (and very good) hardware and a proper configuration of said hardware, but it does work beautifully.

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Fabric Benchmarking: Moving CSV Files

Eugene Meidinger breaks out the abacus:

First, a disclaimer: I am not a data engineer, and I have never worked with Fabric in a professional capacity. With the announcement of Fabric SQL DBs, there’s been some discussion on whether they are better for Power BI import than Lakehouses. I was hoping to do some tests, but along the way I ended up on an extensive Yak Shaving expedition.

I have likely done some of these tests inefficiently. I have posted as much detail and source code as I can and if there is a better way for any of these, I’m happy to redo the tests and update the results.

Part one focuses on loading CSV files to the files portion of a lakehouse. Future benchmarks look at CSV to delta and PBI imports.

I think Eugene did a fine job documenting everything in the process, and it was interesting to see relative price differences between different techniques for uploading a very large CSV file.

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Power BI: Microsoft Store or Direct Download?

Soheil Bakhshi shares some advice:

Within the regular Power BI Desktop, there are also two flavours:

  1. Power BI Desktop (Store Version)
  2. Power BI Desktop (Download Version)

These flavours, though similar in functionality, offer different features and experiences. In this blog, we’ll examine why these two versions exist, how they differ, and which version might suit your needs and why you might want both.

Read on to learn about the differences between the two and when you might prefer one to the other.

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Working with the Azure AI Document Service

Tomaz Kastrun continues a series on Azure AI. First up is a visual review of the Azure AI Document service:

Vision and Document services gives your apps the ability to analyze images, process documents and use technologies for optical character recognition (OCR) with combinations to machine learning.

That product has gone through a few name iterations, including Document Recognizer. But wait, there’s more!

Tomaz also takes a look at the Python SDK:

Vision and Document SDK for Python gives you extra extensibility of the services to add it to your apps.

Using Vision and Document SDK with Python, you will need to have the resource up and running (for the starters go with free pricing tier (F0)) and get the Document intelligence API Key and Endpoint address.

Click through for an example of how that works.

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