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Author: Kevin Feasel

Visualizing when Lower is Better

Published 2023-08-30 by Kevin Feasel

Alex Velez inverts a common experience:

When quickly scanning, I wonder why the direct and indirect sales teams underperformed in 2022. Mostly, they fell below the goal of 90 days, exceeding their target only three times. 

Now, pausing to think more critically about the context of this scenario, I realize I’ve misread the graph—specifically the goal line. Targets and goals are often seen as minimum thresholds, not maximum limits. But in the sales industry, the goal is to close a deal as quickly as possible. In this visual, below the goal line is actually a good thing!

This graph challenges my standard construct of targets and goals, which could lead to confusion or, worse, the wrong conclusions if I’m not careful. 

Read on for five alternative ways to display this graph and (hopefully) reduce confusion.

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Setting Table and Matrix Column Widths in Power BI

Published 2023-08-30 by Kevin Feasel

Kurt Buhler controls the horizontal, Kurt Buhler controls the vertical:

One challenge of the table and matrix visuals in Power BI is that it’s difficult to precisely and consistently set column widths. Unlike in Excel, where you can set the row and column widths in a spreadsheet, you have no option in the visual interface to control the column width property. However, it’s still possible to control it in the report metadata, which is exposed in the officially supported Power BI Projects format (.pbip) which is in preview. Notably, however, opening and modifying report metadata from this format isn’t yet supported. Despite that fact, it still works reliably, so I thought I’d demonstrate how to do this.

There are a fair number of steps involved but it all makes sense in the end.

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Data Type Conversions and Snowflake Performance

Published 2023-08-30 by Kevin Feasel

Kevin Wilkie is implicit in this whole thing:

One of the ways we can get better at speed is to attempt several slightly different ways that can get you (hopefully) the same data. Some tables work better with one query while some work better with another query.

Let’s work through a scenario in Snowflake and we’ll see which one is faster under “normal” conditions.

Click through for a few query examples and how they end up performing.

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Comparing the Microsoft Fabric Data Wrangler and Power Query Editor

Published 2023-08-30 by Kevin Feasel

Reza Rad performs a comparison:

Power Query Editor and Data Wrangler are data transformation and preparation tools in Microsoft Fabric. There are similarities between these two tools. However, there are differences, too. It is essential to know the capabilities of each tool to understand which one should be used for what purpose and scenario. In this article, this is our quest.

Reza includes a video and an article. Reza also has a summary chart at the bottom.

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Returning Matrix Elements in Spiral Order in R

Published 2023-08-29 by Kevin Feasel

Tomaz Kastrun forgot to remove The Club from his REPL:

Another one from the Leetcode challenge. This time, get the elements (single values) from the matrix in a spiral order with a starting position of [1,1].

So, the basic idea is to retrieve a vector of elements from a matrix in the following order:

Probably not something you’d use with any frequency, but it’s a fun way to learn how to operate within matrices.

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Versioned State Store in Kafka Streams

Published 2023-08-29 by Kevin Feasel

Victoria Xia announces new functionality in Apache Kafka 3.5:

Since the introduction of stream processing, there have been three certainties in life: death, taxes, and out-of-order data. As a stream processing library built for Apache Kafka, Kafka Streams processes data in offset order. When out-of-order data is present, offset order differs from timestamp order and care must be taken to ensure that processing results respect timestamp order where appropriate. The introduction of versioned state stores to Kafka Streams in the Apache Kafka 3.5 release is a huge milestone in this direction.

In this blog post, I’ll address the what, why, and how of versioned stores in Kafka Streams, including what they are, why you might like to use them, how to get started, and a couple of things to watch out for when upgrading.

Read on to see what this entails and how you can try it out yourself.

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The Medallion Architecture in Data Modeling

Published 2023-08-29 by Kevin Feasel

Nikola Ilic gets the gold:

The most common pattern for modeling the data in the lakehouse is called a medallion. I love this name – it’s really easy to remember. But, why medallion? Tag along and you’ll soon find out why.

The same as for the lakehouse concept, credits for being pioneers in the medallion approach goes to Databricks.

What I’ve found interesting is the number of people who have taken to disliking the medallion architecture terms because Databricks pushed it so hard that their clients automatically assumed “medallion = using Databricks.”

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Built-In R Datasets

Published 2023-08-29 by Kevin Feasel

Adrian Tam continues a series on getting started in R:

The ecosystem in R contains not only the function libraries to help you perform statistical analysis but also the data library that gives you some famous datasets to test out your program. There are a lot of built-in datasets in R. In this post, you will:

  • Learn some of the built-in datasets
  • Know how to use these datasets

Let’s get started.

Most of these built-in sets are fairly small and able to help you illustrate a specific point.

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Group Replication in MySQL

Published 2023-08-29 by Kevin Feasel

Aisha Bukar continues a series on replication in MySQL:

MySQL Group replication is a remarkable feature introduced in MySQL 5.7 as a plugin. This technology allows you to create a reliable group of database servers. One of the most important features of MySQL’s group replication is that it allows these servers to store redundant data. This allows the database state to be replicated across multiple servers making it efficient in the situation where there is a server breakdown, the other servers in the cluster can agree to work together.

This technology is built on top of the MySQL InnoDB storage engine and employs a multi-source replication approach which we discussed in part 3 of the replication series. In this article, we’d be looking at an overview of the group replication technique, configuring and managing group replication, and also best practices for group replication. So, let’s get started!

Read on to see how it works and some recommendations around using it.

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