The hottest Analytics Substack posts right now

And their main takeaways
Category
Top Technology Topics

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.

Issue #4 - The Five Minute History of Data

The Data Ecosystem • 59 implied HN points • 05 May 24
🕹 Technology Data science AI Analytics Data processing Cloud Computing
  1. Data is generated and used everywhere now, thanks to smart devices and cheaper storage. This means businesses can use data for many purposes, but not all those uses are helpful.
  2. Processing data has become much easier over the years. Small companies can now use tools to analyze data without needing a team of experts, although some guidance is still necessary.
  3. Analytics has shifted from just looking at past data to predicting future trends. This helps companies make better decisions, and AI is starting to take over some of these tasks.

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.
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Ronin is LIVE on Dune!

Ronin’s Newsletter • 24 implied HN points • 11 Nov 24
🔮 Crypto Blockchain Analytics Data Gaming Community
  1. Ronin is now accessible on Dune Analytics, allowing users to analyze on-chain transactions and build dashboards for various data insights.
  2. Creating dashboards on Dune is easy; just sign up, choose Ronin, and start building your queries to visualize data.
  3. The Dune API lets users get real-time data updates and notifications, making it simpler for developers and analysts to track important metrics.

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.

BigQuery processing engine: Shuffle

VuTrinh. • 119 implied HN points • 06 Jan 24
🕹 Technology Data Engineering Big Data Cloud Computing Data processing Analytics
  1. BigQuery uses a processing engine called Dremel, which takes inspiration from how MapReduce handles data. It improves how data is shuffled between workers for faster processing.
  2. Traditional approaches have issues like resource fragmentation and unpredictable scaling when dealing with huge data. Dremel solves this by managing shuffle storage separately from the worker, which helps in scaling and resource management.
  3. By separating the shuffle layer, Dremel reduces latency, improves fault tolerance, and allows for more flexible worker allocation during execution. This makes it easier to handle larger data sets efficiently.

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.

Five Effective Marketing Strategies for Small Businesses on a Budget

The Small Business Corner • 39 implied HN points • 06 May 24
💼 Business Marketing Small businesses Social media Email Marketing Analytics
  1. Craft a targeted marketing plan to save time and effort by focusing on potential customers with a detailed strategy that aligns with your business goals.
  2. Create engaging content that resonates with your audience, providing value and building trust over time to attract and convert followers into customers.
  3. Utilize social media platforms to connect with your target audience cost-effectively, engaging with users, choosing the right platforms, and leveraging analytics for success.

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

Data Science Weekly - Issue 486

Data Science Weekly Newsletter • 359 implied HN points • 17 Mar 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Engineering Analytics
  1. AI and data science are evolving rapidly, making it challenging for many to keep up. It's common for professionals to feel overwhelmed as they try to understand new advancements.
  2. There's a growing discussion about whether we should slow down AI development. Some people believe we need to pause and figure out the implications of current technologies before moving forward.
  3. Many professionals are exploring career shifts between data science and data engineering. It's important to consider personal interests and skills when deciding which path to take.

Predict a Mockingbird: November Week-2

The Parlour • 17 implied HN points • 11 Nov 24
💰 Finance Investment Analytics Market Trends Economic Indicators
  1. Companies can show strong or weak financial health based on key metrics like cash flow and profitability. This helps investors decide where to put their money.
  2. Insider trading activities can hint at stock movements. If insiders are buying, it might be a good sign, but heavy selling could be a warning.
  3. Using tools like search interest and news sentiment helps track how a company is viewed in the market. Positive buzz can mean good things for stock performance.

Introducing The Data Score Newsletter

The Data Score • 138 implied HN points • 05 Apr 23
🕹 Technology Data Technology Business Analytics Insights
  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 Vendors Tools
  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 Automation Data Management BI Tools Data Visualization
  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.

Card Insights

Pine • 19 implied HN points • 18 Jun 24
🕹 Technology Software Data Analytics User Experience Improvements
  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.

Dashing Data Viz - Issue 232

Dashing Data Viz • 98 implied HN points • 04 Apr 23
🕹 Technology Data Visualization 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 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.

Update now: Stop Running Playbooks Directly from Analytics Rules

Rod’s Blog • 79 implied HN points • 08 Jun 23
🕹 Technology Software Automation Analytics Security
  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.

Tracking/Measurement/Collection/Creation - what was the question again?

timo's substack • 78 implied HN points • 26 Mar 23
🕹 Technology Data Engineering Analytics Data Privacy Data Collection
  1. Finding a niche involves identifying what you enjoy and what is consistently needed in your projects.
  2. Tracking data is easily understood, but may have a negative reputation due to its association with web tracking practices.
  3. Measurement is a broader term than tracking, and data collection is often overlooked in the data engineering process.

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 AI Analytics Deep Learning Machine Learning Algorithms
  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.

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.

dbt Labs acquires Transform - who's next?

Data Thoughts • 119 implied HN points • 19 Feb 23
💼 Business Data science Analytics Acquisitions Market Trends Technology
  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 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.

Streaming in real life

davidj.substack • 47 implied HN points • 23 Feb 24
🕹 Technology Analytics Data Warehousing ETL 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.

Python Powers Excel

Sector 6 | The Newsletter of AIM • 39 implied HN points • 24 Aug 23
🕹 Technology Software Data science Analytics Machine Learning Programming
  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 Emerging Tech Marketing Analytics Tech Trends
  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.

I made 1+1=0 in DuckDB

VuTrinh. • 19 implied HN points • 03 Feb 24
🕹 Technology Data Engineering Databases Analytics Software Development Programming
  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 AI Analytics Partnerships Startups Acquisitions
  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.