The hottest Data Trends Substack posts right now

The author analyzed different housing data like Case-Shiller and rent inflation. It's interesting to see how these data points relate to each other.
There are components in the Erdmann Housing Tracker that provide extra insights on the housing market. Comparing these with other measurements helps to understand trends better.
The analysis is not meant for academic purposes, but it's a fun exploration of the data. It shows how digging into numbers can reveal patterns.

YouTube is focusing on subscriptions with over 100 million paying subscribers, positioning itself as a subscription superpower.
Snap's stock slumped after Q4 results, but the company reached 7 million paid subscribers for its product.
Google Maps introduced LLM search, enabling users to search using key phrases for recommendations in the US, with expansion planned.

Jeff Asher created a quiz on crime data and trends with interesting facts and questions.
The quiz covers topics like murder rates, law enforcement reporting systems, and crime definitions.
Readers can test their knowledge and learn new information through the quiz.

The best predictions come from deep analysis of today's data challenges and trends.
Data oracles provide valuable insights for the future by understanding present data trends.
Data writers like Davenport, Moses, Madsen, and Thomas offer grounded observations and advice on data topics.

In 2019, a lot of companies around the world are included in the data analysis, and their classifications are based on geography and industry. This helps in understanding market trends more clearly.
The U.S. firms are still the largest in terms of market value, but the emerging markets have a significant number of companies, highlighting diverse risks and opportunities.
When analyzing financial data, it's important to remember that the numbers can change and may take time to update, so always verify information and be aware of timing issues.

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When evaluating data trends, ignore half and try quick tests for the rest.
Composable CDPs are gaining popularity and have practical value for businesses.
Data product managers should adapt to real-time data, utilize external data sources, and manage all data to avoid being overwhelmed.

Sometimes it's okay to break away from data best practices.
Don't fear AI advancements like Synthesia in videos, embrace them.
Analytics engineering is more about organizational change than specific tools like DBT.