The hottest Analytics Substack posts right now

And their main takeaways
Category
Top Technology Topics

Simulate Your Next Marathon Race Pace

The Healthtech Initiative • 2 implied HN points • 20 Feb 26
🎾 Sports Analytics
  1. A predictive marathon model built from 101 runners explains about 79.3% of the variation in finish times and has an average prediction error of roughly 18.3 minutes.
  2. Running performance is framed as two parts: baseline ability (like genetic or starting pace) and adaptation to training (how much fitness you gain per minute of training).
  3. About 21% of finish-time differences are unexplained — things like weather, illness, sleep, motivation, nutrition, and luck — which shows there are real limits to modeling human performance.

Introducing The Data Score Newsletter

The Data Score • 138 implied HN points • 05 Apr 23
🕹 Technology Analytics
  1. DataChorus LLC focuses on generating actionable insights for professionals and investors through data and technology.
  2. DataChorus aims to align data and technology with decision-making outcomes, explore different datasets and analytic frameworks for critical questions, and discuss scaling data practices and creating impactful data products.
  3. The Data Score Newsletter by Jason DeRise, CFA provides actionable ways to extract insights from data, explores breakthroughs in data and technology, and encourages open conversations to maximize success.

Choosing a Product Analytics Tool

Sarah's Newsletter • 299 implied HN points • 27 Sep 22
🕹 Technology Analytics
  1. Product analytics is crucial to understand how users engage with your product through front-end tracking data like what pages they view and buttons they click.
  2. Event tracking data helps in analyzing funnels, identifying drop-offs, and creating customized user experiences, such as re-engagement campaigns.
  3. When choosing a product analytics tool, consider features like tracking implementation, native integrations, analysis capabilities, and pricing based on your team's skillset, budget, and main purpose for utilizing event tracking data.

The Thrill of Deprecating Dashboards

Sarah's Newsletter • 239 implied HN points • 29 Nov 22
🕹 Technology Analytics
  1. Having an excessive number of dashboards can lead to inefficiency and confusion within an organization. It's important to prioritize strategic organization over creating new dashboards indiscriminately.
  2. Developing an automated dashboard deprecation strategy can help save time and maintain a clean BI instance. By automating the process, organizations can efficiently manage and delete unused visuals.
  3. Implementing a proactive maintenance plan, such as using a data catalog or automated tools, can help keep BI instances organized and optimal for data insights. Regular cleaning and organization are key to ensuring the effectiveness of analytics strategies.
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sqlmesh init -t dbt

davidj.substack • 179 implied HN points • 02 Dec 24
🕹 Technology Analytics
  1. SQLMesh recently announced that it is backwards compatible with dbt projects. This means teams can gradually switch to SQLMesh without having to do a big migration all at once.
  2. Using SQLMesh can help improve the clarity of data workflows and avoid broken DAGs during development. It offers features that make managing complex data stacks easier.
  3. Migrating to SQLMesh is possible even for those who aren't very tech-savvy. The process can be simple and done in an afternoon, making it accessible for teams to test and implement.

Card Insights

Pine • 19 implied HN points • 18 Jun 24
🕹 Technology Analytics
  1. Pine now has cool analytics tools to help you understand your data better. You can break down and show your information in different ways.
  2. They've made some neat improvements, like showing summary insights and helping you create better connections between cards. This makes using the app more user-friendly.
  3. You can now open links in new tabs easily and get notifications for actions you take. These small updates improve the overall experience when using the app.

Nearly Headless BI

davidj.substack • 59 implied HN points • 25 Jun 25
🕹 Technology Analytics
  1. Snowflake and Databricks are using a semantic layer, which helps make data easier to understand and access. This is a shift from older methods that relied heavily on text-based commands.
  2. The rise of AI has changed what businesses need from their analytics tools. Now, having a semantic layer is a must for companies that want to stay competitive in agentic analytics.
  3. Headless business intelligence is fading away as companies now blend traditional analytics with smarter, AI-driven tools. This could change how data warehouses and BI tools work together in the future.

Dashing Data Viz - Issue 232

Dashing Data Viz • 98 implied HN points • 04 Apr 23
🕹 Technology Analytics
  1. The newsletter shares curated news, articles, and jobs related to Data Visualization.
  2. There are interesting links shared, such as Twitter threads, articles on data visualization tools, and event announcements.
  3. Readers can engage by clicking on the links provided and subscribing to receive future newsletters.

How to be Notified When Microsoft Sentinel Data Stops Populating

Rod’s Blog • 79 implied HN points • 02 Oct 23
🕹 Technology Analytics
  1. Being notified when data ingestion stops is crucial for security analysts to maintain the integrity of security tools.
  2. A KQL query can be set up as an Analytics Rule to alert if a specific table has not received new data within a set timeframe, allowing for timely action.
  3. Email alerts can be configured instead of generating unnecessary security incidents, ensuring the operations team can address potential issues efficiently.

Update now: Stop Running Playbooks Directly from Analytics Rules

Rod’s Blog • 79 implied HN points • 08 Jun 23
🕹 Technology Analytics
  1. Microsoft Sentinel is deprecating the capability to assign Playbooks directly to Analytics Rules, encouraging the use of Automation Rules for better efficiency and management.
  2. With Automation Rules, you can manage all your automations from one place, trigger playbooks for multiple analytics rules with a single rule, define playbook execution order, and set expiration dates for playbook runs.
  3. Consider migrating existing Analytics Rules with directly assigned Playbooks to the new Automation Rules method to enhance effectiveness.

What CEOs, leaders, and investors need to know about the different meanings of AI

Mike Talks AI • 78 implied HN points • 27 Jul 23
🕹 Technology Analytics
  1. The term AI can mean different things and understanding those meanings is crucial for clear communication, better decisions, and addressing concerns.
  2. Different definitions of AI include AGI or artificial general intelligence, deep learning for solving complex problems, and tools like ChatGPT for tasks like writing and summarizing.
  3. CEOs, leaders, and investors should explore opportunities in AGI, deep learning, ChatGPT, and practical AI to stay relevant and make informed decisions.

📽 Webinar: How Convirza Scaled SLMs for Real-Time Call Analytics – Without Breaking the Bank

TheSequence • 126 implied HN points • 15 Nov 24
🕹 Technology Analytics
  1. Convirza found a way to analyze call data quickly and affordably. They combined many tools into one setup, making everything run smoother.
  2. Their response time for customers is now under two seconds, even when many people are using the service. This helps workers get the info they need fast.
  3. By switching to a new system, they reduced costs a lot. They no longer need expensive machines for each task, which keeps their expenses low while still providing accurate results.

MLS Finally Released Viewership Data...But It Raises More Questions Than It Answers

Huddle Up • 29 implied HN points • 28 Jul 25
🎾 Sports Analytics
  1. MLS has reported that it averages 120,000 viewers per game this season, which is a 50% increase from last year. This increase is partly due to new deals that make games more accessible.
  2. The viewership numbers have mostly been kept secret until now, which makes this disclosure significant. It raises questions about how Apple and MLS calculated these figures.
  3. While the growth sounds impressive, it can also be misleading and confusing. More information is needed to fully understand what this means for the league's future.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Botnet Attacks with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 16 Oct 23
🕹 Technology Analytics
  1. Botnet attacks can be detrimental to network security by causing massive disruptions through DDoS attacks, data theft, and malware distribution.
  2. Microsoft Sentinel provides advanced AI and machine learning capabilities to detect and mitigate botnet attacks effectively, offering features like threat intelligence integration and automated incident response.
  3. Organizations can enhance botnet detection with Microsoft Sentinel by setting up custom alerts, regularly updating systems, implementing strong access controls, and collaborating with security teams for threat intelligence sharing.

dbt Labs acquires Transform - who's next?

Data Thoughts • 119 implied HN points • 19 Feb 23
💼 Business Analytics
  1. dbt Labs has bought Transform, and more companies in the data field might be sold or closed soon. This could lead to big changes in the industry.
  2. Data teams are seen as a 2nd order need for businesses, meaning they aren't absolutely necessary. Companies may cut these teams first when they need to save money.
  3. To get the best value from tools, data practitioners should focus on essential needs rather than extra features. This means keeping an eye on what really matters in the data ecosystem.

The Ways Microsoft Security Copilot Can Enhance Security Operations with Microsoft Sentinel

Rod’s Blog • 39 implied HN points • 06 Dec 23
🕹 Technology Analytics
  1. Security teams face challenges such as complexity in handling large volumes of security data from various sources like logs and alerts, making analysis overwhelming, especially during cyberattacks.
  2. There is a skills gap in the market for skilled security professionals, leading to a lack of resources and expertise within security teams to manage all security tasks effectively.
  3. To address challenges, security teams need solutions that simplify security data and tasks, empower them with AI and machine learning capabilities, and protect the organization from cyberthreats by leveraging the latest threat intelligence.

SDF

davidj.substack • 59 implied HN points • 12 Feb 25
🕹 Technology Analytics
  1. SDF and SQLMesh are alternatives to dbt for data transformation. They are both built with modern tech and aim to provide better ease of use and performance.
  2. SDF has a built-in local database, allowing developers to test queries without costs from a cloud data warehouse. This can speed up development and reduce costs.
  3. Both tools offer column-level lineage to track changes, but SQLMesh provides a better workflow for managing breaking changes. SQLMesh also has unique features like Virtual Data Environments that enhance developer experience.

90th minute and the home team is 1-0 up…

Klement on Investing • 2 implied HN points • 16 Jan 26
🎾 Sports Analytics
  1. Crowd noise and spectator pressure shape referees' decisions, creating a home-field advantage; referees add more stoppage time in close matches and the bias grows with bigger crowds.
  2. Female referees are more likely than male referees to be swayed by audience pressure, often awarding less stoppage time when the home team leads by one goal, which benefits the home side.
  3. Among female referees, younger and less experienced officials are especially prone to yielding to social pressure, while older referees are less affected.

sqlmesh init duckdb

davidj.substack • 71 implied HN points • 03 Dec 24
🕹 Technology Analytics
  1. There's a new public repository called bluesky-data where people can collaborate and follow along with its development. It's easy to get started by setting it up on your local machine.
  2. Using sqlmesh with the Bluesky data can provide real-time data availability, while also allowing for a more complete view of the data in a batch processing style. This means you can get both immediate updates and historical data.
  3. It's better to start with dlt and then initialize sqlmesh within that project. This way, you can efficiently manage large datasets without needing to compute everything each time.

You can take your gold and shove it...

davidj.substack • 59 implied HN points • 13 Jan 25
🕹 Technology Analytics
  1. The gold layer in data architecture has drawbacks, including the loss of information and inflexibility for users. This means important data could be missing, and making changes is hard.
  2. Universal semantic layers offer a better solution by allowing users to request data in plain language without complicated queries. This makes data use easier and more accessible for everyone.
  3. Switching from a gold layer to a semantic layer can improve efficiency and user experience, as it avoids the rigid structure of the gold layer and adapts to user needs more effectively.

The Freedom of Freelancing

kleandata • 39 implied HN points • 29 Sep 23
💼 Business Analytics
  1. Freelancing offers flexibility in work hours and location.
  2. Analytics engineering work is well-suited for freelance contracts.
  3. Freelancing can lead to higher earning potential through diverse projects and multiple clients.

Python Powers Excel

Sector 6 | The Newsletter of AIM • 39 implied HN points • 24 Aug 23
🕹 Technology Analytics
  1. Python is now integrated into Excel, making it easier for users to blend Excel's tools with Python's capabilities.
  2. This allows users to perform advanced tasks like data visualization and machine learning directly in Excel.
  3. The integration works well with existing Excel features, so users can still use familiar functions like formulas and charts.

What A Waste of Time!

Sector 6 | The Newsletter of AIM • 39 implied HN points • 05 Sep 23
🕹 Technology Analytics
  1. The Gartner Hype Cycle is often seen as unhelpful. Many believe it doesn't accurately show how technologies are adopted.
  2. Experts feel that the report is getting less relevant over time, showing a decline in new ideas.
  3. It might be time to rethink how we assess and talk about emerging technologies. There's a need for clearer and more effective ways to measure innovation.

Everyone Should Care About Data Storage

Sarah's Newsletter • 159 implied HN points • 01 Feb 22
🕹 Technology Analytics
  1. Data storage impacts an organization's ability to make informed and timely decisions.
  2. Data-driven decision making relies on access to clean and relevant information.
  3. Different types of data storage, like data puddles, warehouses, and lakes, serve unique purposes and must align with the organization's needs.

sqlmesh plan

davidj.substack • 59 implied HN points • 10 Dec 24
🕹 Technology Analytics
  1. Virtual data environments in SQLMesh let you test changes without affecting the main data. This means you can quickly see how something would work before actually doing it.
  2. Using snapshots, you can create different versions of data models easily. Each version is linked to a unique fingerprint, so they don't mess with each other.
  3. Creating and managing development environments is much easier now. With just a command, you can set up a new environment that looks just like production, making development smoother.

I made 1+1=0 in DuckDB

VuTrinh. • 19 implied HN points • 03 Feb 24
🕹 Technology Analytics
  1. DuckDB is easy to use because it works like SQLite, running directly inside applications without needing a separate server. This makes it simpler to manage.
  2. It processes data in batches through vectorization, which means it can handle multiple records at once, making operations faster than traditional row-by-row processing.
  3. DuckDB supports ACID transactions, ensuring that data remains safe and reliable, which is important in data analytics and shared environments.

A Groundbreaking Week of AI Collaboration

Sector 6 | The Newsletter of AIM • 39 implied HN points • 02 Jul 23
🕹 Technology Analytics
  1. Many big companies are teaming up or buying each other to improve their AI skills. These moves help them stay strong in the AI market.
  2. NVIDIA recently bought a startup called OmniML that focuses on making smaller and quicker AI models. This could lead to new AI technology for cars and robots.
  3. The AI industry is rapidly changing with new partnerships and innovations. Companies are working hard to create better AI tools and applications.

2025 - Year in Review

trydeepwork • 2 implied HN points • 01 Jan 26
🕹 Technology Analytics
  1. The tool is widely used — about 29,420 hours logged (~14 full-time years) — and user habits shifted, with peak focus moving from 2 pm to 10 am and many sessions happening late at night.
  2. Auto-abandoning tasks proved hugely valuable. About 23% of tasks are abandoned and 98% of those are automatic, which cuts clutter and decision fatigue.
  3. Small UX and workflow tweaks changed behavior: Time Dots, step breakdowns, microWork sessions, and improved scheduling made progress more visible and lowered friction to start work.

sqlmesh migrate

davidj.substack • 47 implied HN points • 20 Dec 24
🕹 Technology Analytics
  1. If you're using dbt to run analytics, switching to sqlmesh is a good idea. It offers more features and is easy to learn while still being compatible with dbt.
  2. sqlmesh helps manage data environments and is more comprehensive in handling analytics tasks compared to dbt. It's simpler to transition from dbt to sqlmesh than from older methods like stored procedures.
  3. When using sqlmesh, think about where to run it and how to store its state. You have choices like using a different database or a cloud service, which can save you money and hassle.

The NFL has been testing optical tracking technology for first downs (but is that a good thing?)

Huddle Up • 40 implied HN points • 29 Jan 25
🎾 Sports Analytics
  1. The NFL is exploring new tracking technology to improve accuracy in measuring first downs during games. This could make it easier to determine if a play is successful or not.
  2. Fans are frustrated because they feel the NFL is slow to adopt advancements that other sports have already embraced. For example, technologies like Hawk-Eye in tennis are much faster.
  3. Some people are questioning whether this new technology is actually needed or if it complicates the game more than it helps. There are mixed feelings about its impact on the sport.

Breaking and Non-Breaking Changes

davidj.substack • 47 implied HN points • 11 Dec 24
🕹 Technology Analytics
  1. When making changes to data models, it's important to identify if they are breaking or non-breaking changes. Breaking changes affect downstream models, while non-breaking changes do not.
  2. SQLMesh automatically analyzes changes to understand their impact on other models. This helps developers avoid manual tracking and reduces the chances of errors.
  3. New features in SQLMesh will allow for more precise tracking of changes at the column level. This means less unnecessary work when something minor is modified.