<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data on David Bartolomei-Guzmán</title><link>https://www.davidbartolomei.com/categories/data/</link><description>Recent content in Data on David Bartolomei-Guzmán</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 01 Oct 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://www.davidbartolomei.com/categories/data/feed.xml" rel="self" type="application/rss+xml"/><item><title>Case Study: Leveraging Machine Learning for Spoken Media Analysis – Share of Voice of Puerto Rico’s Political Figures in 2024</title><link>https://www.davidbartolomei.com/case-study-leveraging-machine-learning-for-spoken-media-analysis-share-of-voice-of-puerto-ricos-political-figures-in-2024/</link><pubDate>Tue, 01 Oct 2024 00:00:00 +0000</pubDate><guid>https://www.davidbartolomei.com/case-study-leveraging-machine-learning-for-spoken-media-analysis-share-of-voice-of-puerto-ricos-political-figures-in-2024/</guid><description>&lt;p&gt;This is the first in a series of articles where I share my findings exploring Speech-to-Text (STT) ML models to transcribe and analyze spoken content in news media. In this article, I discuss how STT output can be used for automatic mention detection and tracking metrics such as Share of Voice of political figures in Puerto Rico during the 2024 election season.&lt;/p&gt;
&lt;h2 id="the-back-story"&gt;The Back Story&lt;/h2&gt;
&lt;p&gt;Before diving into the details, here’s a brief back story on what sparked my interest in this topic. You can skip directly to the results by scrolling down.&lt;/p&gt;</description></item><item><title>Challenges and Benefits of the Analytics Engineer Role</title><link>https://www.davidbartolomei.com/challenges-and-benefits-of-the-analytics-engineer-role/</link><pubDate>Mon, 22 Apr 2024 00:00:00 +0000</pubDate><guid>https://www.davidbartolomei.com/challenges-and-benefits-of-the-analytics-engineer-role/</guid><description>&lt;p&gt;The Analytics Engineer is a relatively new role that emerged during the “Modern Data Stack” trend of the last 5-10 years and was &lt;a href="https://www.getdbt.com/what-is-analytics-engineering"&gt;”formalized”&lt;/a&gt; by dbt Labs. In this article, I discuss some of the learnings, challenges, and benefits that I have experienced while adopting this role in my team.&lt;/p&gt;
&lt;p&gt;TLDR: Analytics Engineers merge the analytical skills of a data analyst with the engineering mindset and practices of a software engineer, creating a hybrid profile. This can be very effective in keeping a data team agile, providing insights, and aiding in the decision-making process more effectively than traditional data analysts.&lt;/p&gt;</description></item></channel></rss>