The hottest Analytics Substack posts right now

And their main takeaways
Category
Top Technology Topics

It's time to build

benn.substack • 1271 implied HN points • 19 Jan 24
🕹 Technology Data AI Software Startups Analytics
  1. The modern data stack ecosystem is shifting as interest in generative AI takes over.
  2. The hype surrounding data tools can lead to rapid product development but also instability and distraction.
  3. Startups can find success by focusing on rebuilding existing ideas in a more deliberate and stable manner.

Championship Sunday was a strange watch for Vikings fans

Purple Insider • 294 implied HN points • 29 Jan 24
🎾 Sports Football Draft Analytics Quarterbacks Strategy
  1. Sunday's games were strange for Vikings fans to watch from a unique perspective.
  2. Building a championship team can involve having an all-time great quarterback, hitting on many draft picks, or building a strong supporting cast around an affordable quarterback.
  3. Success in the NFL requires making bold decisions and it's challenging to win even with a great team.
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Why Today Is The Perfect Time to Learn Data | Seattle Data Guy

Data Analysis Journal • 373 implied HN points • 25 Oct 23
🕹 Technology Data science Analytics Data Engineering Learning Resources Career Advice
  1. Learning data is more accessible and better now than in the past years.
  2. For transitioning into data engineering, focus on SQL, programming, data warehouse, and data pipelines.
  3. Analysts should focus on understanding the business problem, building maintainable systems, and following a data analytics process.

Revenge of the Nerds

The Better Letter • 196 implied HN points • 08 Dec 23
🎾 Sports Analytics Baseball Innovation Management Statistics
  1. Baseball's analytics revolution owes its existence to a smart security guard creating statistical analysis accessible and interesting.
  2. The success of 'Moneyball' accelerated the statistical disruption in baseball and led to the widespread use of advanced statistical measures in MLB.
  3. The Bill James approach transformed baseball analysis to be more objective, relevant, and useful, impacting team strategies and decision-making.

Streaming in real life

davidj.substack • 47 implied HN points • 23 Feb 24
🕹 Technology Analytics Data Warehousing Real-Time Data
  1. Real-time data streaming from databases like MySQL to data warehouses such as Snowflake can significantly reduce analytics latency, making data processing faster and more efficient.
  2. Streamkap offers a cost-effective solution for streaming ETL, promising to be both faster and more affordable than traditional methods like Fivetran, providing a valuable option for data professionals.
  3. Implementing Streamkap in data architectures can lead to substantial improvements, such as reducing data update lag to under 5 minutes and delivering real-time analytics value for customers, showcasing the impact of cutting-edge data technology.

The NFL Is Working On Technology To Eliminate The Chain Gang

Huddle Up • 22 implied HN points • 08 Mar 24
🎾 Sports Technology NFL Analytics Business Entertainment
  1. The NFL is developing optical tracking technology to replace the traditional 'chain gang' for measuring first-down yardage.
  2. The NFL has been using RFID chips in footballs and players' gear for tracking player movements and collecting Next Gen stats.
  3. Introducing additional video review technology in the NFL could complicate the game over time and may not necessarily be a positive change.

Everyone is a CDP now

timo's substack • 157 implied HN points • 27 Nov 23
🕹 Technology Data Platforms Analytics Activation Integration
  1. The concept of a Customer Data Platform (CDP) is evolving with a focus on defining its functionality more clearly.
  2. There is a trend towards composable CDP solutions, allowing for flexibility but also potential complexity.
  3. The key value of a CDP lies in activation - using customer data to create targeted audiences for more efficient marketing strategies.

Celebrating An Anniversary: Three Years of Writing About Analytics - Issue 154

Data Analysis Journal • 452 implied HN points • 26 Jul 23
🕹 Technology Analytics Data science Newsletter Writing Career development
  1. The author reflects on three years of writing a newsletter about analytics, thanking supporters and subscribers.
  2. The author's newsletter aims to document their journey, bridge the gap between academics and industry, and encourage classic data analysis.
  3. The author shares insights on their writing strategy, the power of being small and independent, and future plans for the newsletter.

Data: the new oil or a new byproduct?

Topsoil • 511 implied HN points • 30 Jun 23
🕹 Technology Data Agriculture Framework Digitization Analytics
  1. Data in agriculture is essential for advancements like Generative AI, automation, and precision agriculture.
  2. Challenges in farm digitization include issues like connectivity, interoperability, data quality, trust, and incentives.
  3. Farmers derive value from data through decision-making, enabling technologies, sharing with advisors, compliance, and future income opportunities.

A/B Testing Paradox: UX Maturity Reduces Your Gains

Jakob Nielsen on UX • 15 implied HN points • 13 Mar 24
🕹 Technology UX Design Analytics ROI Experimentation
  1. In A/B testing, the average uplift from design changes is small, about 0.15%, with 54% of cases showing improvements of 0.5%.
  2. Only 19% of experiments result in statistically significant gains, with an average lift of 1.0% across those cases.
  3. As companies mature in UX, gains from design experimentation may decrease over time due to the nature of tested designs and the diminishing low-hanging fruit.

Spotify, Revolut and the rise of the Super Sub

Department of Product • 393 implied HN points • 22 Jun 23
💼 Business Tech Subscription Analytics Product Launch Market Trends
  1. Some tech companies are experimenting with higher-priced subscription tiers to offer new features to exclusive users.
  2. Revenue generation is a key focus for many product teams, leading to new pricing strategies.
  3. Pricing experiments like launching super premium subscriptions are worth monitoring for trends in the industry.

Leaving product analytics

timo's substack • 314 implied HN points • 05 Jun 23
🕹 Technology Analytics Product Data Warehousing
  1. Product analytics tools like Amplitude, Mixpanel, and Heap are evolving to offer new features like marketing attribution and user experience analytics.
  2. New players in the market like Kubit are focusing on providing product analytics directly on cloud data warehouses.
  3. The future of analytics is moving towards event analytics, opening up new possibilities and challenges for businesses.

Embracing the New Era of Accelerated Testing - Issue 150

Data Analysis Journal • 235 implied HN points • 28 Jun 23
🕹 Technology Data science Analytics A/B Testing Experimentation Tooling
  1. Embracing accelerated testing in the modern data analysis landscape is essential for success.
  2. The current traditional academic workflow for A/B testing may not be suitable for the evolving landscape of experimentation.
  3. To thrive in the era of rapid feature flagging and A/B testing, teams need to adapt by automating statistical checks, simplifying documentation, and eliminating bias.

How to be Notified When Microsoft Sentinel Data Stops Populating

Rod’s Blog • 79 implied HN points • 02 Oct 23
🕹 Technology Data Management Security Monitoring 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.

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

Rod’s Blog • 39 implied HN points • 06 Dec 23
🕹 Technology Security AI Cloud Analytics Automation
  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.

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 Cybersecurity Analytics Threat intelligence Automation Collaboration
  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.

The Analytics Requirements Document

Sarah's Newsletter • 359 implied HN points • 27 Oct 22
💼 Business Analytics Product Launch Contracts Data Management Team Collaboration
  1. Analytics should be a first-class citizen in crafting product launches to avoid wasted time and ensure measurable success.
  2. Utilize detailed agreements like Product Requirements Documents (PRD) and Analytics Requirements Documents (ARD) to align teams, outline goals, data criteria, assumptions, and finalize expectations.
  3. Involving analytics early in the product evolution lifecycle is crucial for gathering and analyzing data effectively, helping in decision-making, and ensuring alignment across technical and business teams.

Retention Analytics - the definitive guide

timo's substack • 176 implied HN points • 12 Mar 23
🕹 Technology Analytics Retention Data Analysis
  1. Focus on retention rate, especially first-week retention for free users, as a key metric for product analytics
  2. Retention analytics require solid user identification to track if users are returning and engaging with your product
  3. Measure retention with cohorts to understand performance over time, highlighting improvements or decreases in user retention