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Day: November 2, 2023

Building a Multinomial Distribution in R

Steven Sanderson isn’t satisfied with the binomial:

The multinomial distribution is a probability distribution that describes the probability of obtaining a specific number of counts for k different outcomes, when each outcome has a fixed probability of occurring.

In R, we can use the rmultinom() function to simulate random samples from a multinomial distribution, and the dmultinom() function to calculate the probability of a specific outcome.

Click through to see how you can build a multinomial distribution and what the difference is between rmultinom() and dmultinom().

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An Overview of Data Lake Operations with Apache NiFi

Lav Kumar gives us a 10,000 foot view:

In the world of data-driven decision-making, ETL (Extract, Transform, Load) processes play a pivotal role. The effective management and transformation of data are essential to ensure that businesses can make informed choices based on accurate and relevant information. Data lakes have emerged as a powerful way to store and analyze massive amounts of data, and Apache NiFi is a robust tool for streamlining ETL processes in a data lake environment.

Read on for a brief primer on NiFi and how some of its capabilities can assist in ETL and ELT processing.

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Using SQL Doc to Find Object Dependencies

Steve Jones looks for links:

In the SQL Doc application, you can dive down into the various objects in your database. As I’ve shown below, I navigated on the left side down to a specific object.

This gives me the basics of this object, but I can scroll down and see more. The lower part below the script shows what this object depends on (Uses) and what other objects depend this one (Used By). In this case, this object depends on dbo.ErrorLog and dbo.uspPrintError.

Read on to learn more about how it works and some tips from Steve.

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The Benefits of Checklists

Aaron Bertrand checks a box:

If there has been one constant throughout my career, it’s change. As applications become more complex and we continue improving reliability, there will always be the next patch, upgrade, new replica, new cluster, and even new cloud region – or moving to the cloud in general. For complex architectures, multiple teams are often actively involved, and even more who want to be “in the know” during any changes.

We use tickets (JIRA) to track and document the work, and incidents (FireHydrant) to expose the status to internal and external customers. But these are complex systems to keep current in real-time. And while nearly everything we do is scripted, broad audiences can’t consume code – even when saturated with comments. Since multiple teams are involved, the code is scattered across disparate things like runbooks, which are not easy or desirable to combine. How can a wide range of people stay coordinated during a major change?

For more complicated tasks, I’m all-in on creating either checklists or dedicated runbooks. I have a client that uses merge replication, and every once in a while, we need to rebuild replication. In that case, we have a more detailed runbook with step-by-step instructions, but this is great for keeping track of complex processes, whether or not they go cross-team.

Also, callout to the greatest Site Reliability Engineer ever to play the game, Mario Lemieux.

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Moving VMs and Disks between Azure Tenants

Dennes Torres makes a move:

Move objects on Azure is not simple. Move between Tenants is extremely difficult or not possible. I faced the challenge to move a virtual machine and disks between tenants recently and found the solution.

Some Years ago, I wrote an article about the Azure Resource Mover when it was still being created. Today the resource mover is integrated with the entire azure portal, although there are already many limitations in relation to moving resources. Anyway, this will not affect us on this blog post.

Click through for the step-by-step, as well as a few gotchas you might run into along the way.

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