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Day: January 6, 2025

Transposing Data Frames in R

Published 2025-01-06 by Kevin Feasel

Steven Sanderson does a switcharoo:

Data manipulation is a crucial skill in R programming, and one common operation is transposing data frames – converting rows to columns and vice versa. Whether you’re cleaning data for analysis, preparing datasets for visualization, or restructuring information for machine learning models, understanding how to transpose data frames efficiently is essential. This comprehensive guide will walk you through various methods to transpose data frames in R, complete with practical examples and best practices.

Read on for a few approaches to the problem.

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Generating an Example of SQL Injection

Published 2025-01-06 by Kevin Feasel

Vlad Drumea points out that SQL injection is still a thing:

SQL injection, also refereed to as SQLi, is a security vulnerability that allows attackers to modify the queries that an application makes to its underlying database.
This type of vulnerability can allow attackers to interact with data that they are not normally able to access, including data belonging to other application users.

For at least a decade, injection attacks were either number one or number two on OWASP’s top 10 list. It dropped all the way to number 3 in 2021. We’ll see how it looks with the 2025 OWASP top 10 application security vulnerabilities list, but in the meantime, check out Vlad’s post.

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Finding Capacity-Level Fabric Settings with Semantic Link Labs

Published 2025-01-06 by Kevin Feasel

Sandeep Pawar lists some Microsoft Fabric properties:

Just before the holidays last year Michael Kovalsky released version 0.8.10 of Semantic Links Labs with a bunch of new helpful functions, among them list_server_properties() lists properties of an Analysis Services instance. As you know, in Fabric, the workspace acts as a server which is tied to a capacity. You define these server properties in the Capacity Settings. As far as I am aware, there wasn’t an API to get these capacity settings for audit/monitoring/debugging. With this new function, you can programmatically get the Semantic Model (i.e. Power BI workload) settings.

Click through for an example.

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Data Lakes, Warehouses, and Lakehouses

Published 2025-01-06 by Kevin Feasel

Noa Shavit disambiguates three terms:

A data warehouse is a repository and platform for storing, querying, and manipulating data. Warehouses are particularly suited for structured data used for decision support and business intelligence. Modern data warehouses have become more efficient, flexible, and scalable (particularly in the context of massively parallel processing and distributed computation), but they still bear the mark of their early development in the previous century.

The data warehouse concept dates back to data marts in the 1970s. After a long incubation period, the idea began to bear fruit commercially at IBM in the late 1980s and early 1990s. Data warehousing improved on the inefficiency of data marts, siloed data stores maintained by individual departments. 

Click through to learn more about each of the three concepts and how they relate.

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