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Day: October 18, 2024

Looping through Column Names in R

Steven Sanderson builds a loop:

Looping through column names in R is a crucial technique for data manipulation, especially for beginners. This article will guide you through various methods to loop through column names in R, providing practical examples and insights to enhance your data analysis skills.

Read on for examples with for loops, the dynamic duo of lapply() and sapply(), and the map() function in the purrr library.

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Building an Impact Analysis Process

Marc Lelijveld needs more than the minimum impact analysis:

Imagine you have a semantic model in the Power BI Service (or Fabric if you will), and you’re about to make a breaking change to this semantic model. How do you inform your end users? How do you tell them about this change? In this blog I will zoom in to options you have in the interface that will help you to reach out to your users, looking at different aspects from other reports in Power BI, but also more complex the users that connect via Analyze in Excel.

Click through for the use case, why the built-in impact analysis option for Power BI isn’t sufficient, and what you can do to flesh it out.

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Tips for Adopting Microsoft Fabric

Paul Turley shares some thoughts:

Hello, friends. I’ve spent the past few months working with several new Fabric customers who were seeking guidance and recommendations for Fabric architecture decisions. What have we learned about using Fabric in enterprise data settings in the past 11 months? This post covers some of the important decisions points and Fabric solution design patterns.

Much of the industry’s experience with Microsoft Fabric over the past several months has been at a high-level as organizations were dipping their toe in the pool to test the water. So far, our Data & AI team have assisted around 50 clients with Fabric projects of various sizes. We have also implemented a handful of production scale projects with enterprise workloads, comparing notes with community leaders and the product teams who develop the product. What lessons have we learned?

Click through for several bits of high-level architectural guidance intended to make that adoption easier.

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Working with Parquet Files in Postgres

Craig Kerstiens announces an extension:

Today, we’re excited to release pg_parquet – an open source Postgres extension for working with Parquet files. The extension reads and writes parquet files to local disk or to S3 natively from Postgres. With pg_parquet you’re able to:

  • Export tables or queries from Postgres to Parquet files
  • Ingest data from Parquet files to Postgres
  • Inspect the schema and metadata of existing Parquet files

Code is available at: https://github.com/CrunchyData/pg_parquet/.

Read on for more background on why we built pg_parquet or jump below to get a walkthrough of working with it.

Hey, that’s my job to tell people to read on to learn more!

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Avoid Storing Files in Databases

Joey D’Antoni explains why you almost never want to use FILESTREAM:

Yesterday, I accidentally walked into a discussion on LinkedIn about the merits of Filestream in SQL Server. If you aren’t familar with Filestream, consider yourself lucky, it was a feature that was added to SQL Server in the short timeframe that people thought it was a good idea to use databases for file storage, and before the enlightened times when object storage became a thing. I first remember blobs being a thing in Oracle 8i, where at least you had the ability to store them in a tablespace with a larger block size than 8k, and had a dedicated area of the buffer pool with that larger block size that you could dedicate to that blob tablespace.

Joey has the right of things. There are rare exceptions where it could make sense to store files in databases. My best example involves storing ML models that we use in SQL Server ML Services, simply because of how difficult it is to read anything off of disk via ML Services. But that’s a real edge case.

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Migrating to Azure PostgreSQL Flexible Server from Single Server

Josephine Bush performs a migration:

Why Migrate to Flexible Server?

  • High availability and disaster recovery: Flexible Server provides higher availability with zone-redundant architecture.
  • Customizable maintenance windows: More control over when updates and maintenance tasks occur.
  • Performance improvements: Fine-tuned scaling and performance adjustments without downtime.
  • Enhanced security: With VNet integration and more advanced networking options.

Read on to learn more about by when you have to migrate and how you can perform the migration.

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