The hottest Data Analytics Substack posts right now

And their main takeaways
Category
Top Business Topics

The evolution of user onboarding at Databox

Kyle Poyar’s Growth Unhinged • 339 implied HN points • 28 Feb 24
💼 Business Data Analytics
  1. Databox focused on improving activation, which led to a 10% increase from 30% to over 40%.
  2. Experimenting with the onboarding process, like allowing users to explore the product before connecting data, can significantly impact user engagement and activation rates.
  3. Implementing strategies like a reverse trial and a guided onboarding process can help not only improve activation rates but also showcase more value to users upfront.

Personalized Pricing: History, Economics, and Impact of AI-Driven Price Discrimination

Gad’s Newsletter • 41 implied HN points • 28 Jul 25
💼 Business Data Analytics
  1. Personalized pricing means companies set different prices for different people, which can increase their profits but might not always be fair. This trend is growing, especially with airlines using AI to set prices based on individual customer data.
  2. While personalized pricing can help some customers get better deals, it can also lead to others paying more. This can create feelings of unfairness and make customers lose trust in companies.
  3. As personalized pricing becomes more common, companies may need to be more transparent about how prices are set. This could help balance profit motives with consumer trust and fairness.

Modernity != Value

Sarah's Newsletter • 299 implied HN points • 19 Apr 22
🕹 Technology Data Analytics
  1. Having modern tools doesn't guarantee providing value - it's more about how analytics teams use the tools to drive organizational change.
  2. The focus should be on delivering value to the organization rather than just building data platforms or using the most modern tools.
  3. Start simple with the minimum viable data stack and only add complexity when necessary - focus on solving real problems and evaluating tools based on problem-solving, maintenance, and scalability.

Data at Depth 12: Surging Substack, Creative Reflections, Streamlit GIS Tutorial

Data at Depth • 19 implied HN points • 02 May 24
🕹 Technology Data Analytics
  1. Documenting analytics platform performance can reveal growth trends and areas needing more attention, like focusing on Substack engagement.
  2. Balancing intrinsic and extrinsic motivation in creativity can impact the quality and longevity of content creation, pushing creators towards enduring satisfaction.
  3. Utilizing AI like GPT-4 for filtering and mapping GIS data in Python with tools like Streamlit can streamline complex data visualization tasks, enhancing efficiency and interactivity.
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Issue #114

Infra Weekly Newsletter • 4 implied HN points • 15 Jan 26
🕹 Technology Data Analytics
  1. GCP favors consistency and global networking primitives and is stronger in data, analytics, and ML. It uses a project-based organization that makes builds faster but more opinionated than AWS.
  2. Platform teams now sit between security, compliance, finance, and application groups and need clearer ownership and decision authority to avoid an accountability gap.
  3. A sophisticated, modular Linux malware framework is targeting cloud servers and containers for credential theft and stealthy persistence, so organisations should assume such threats are coming and tighten access controls, monitoring, patching, and Linux/cloud EDR.

Correlating AWS S3 Breaches

Detection at Scale • 19 implied HN points • 29 Apr 24
🕹 Technology Data Analytics
  1. AWS S3 buckets are a common target for attackers due to misconfigurations and high-value data. Security teams should focus on monitoring S3 activity to ensure authorized access and detect breaches early.
  2. S3 serves as a major storage solution for various data types in the cloud. Its widespread use makes it a prime target for attackers seeking to compromise sensitive information.
  3. Monitoring S3 bucket activity is crucial for detecting suspicious behavior that could signal a breach. Using tools like CloudTrail, GuardDuty, and CloudWatch can provide valuable insights and enhance security measures.

About Data User Experience

timo's substack • 78 implied HN points • 28 Sep 23
🕹 Technology Data Analytics
  1. Agile approach works for quick insights but can fail for user experience
  2. Data user experience includes utility, usability, findability, credibility, desirability, and accessibility
  3. Improving data user experience involves naming conventions, SQL style guides, ownership clarity, metadata, architecture, data consistency, and regular user feedback

Microsoft Sentinel SOC 101: How to Detect and Mitigate Advanced Persistent Threats (APTs) with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 12 Oct 23
🕹 Technology Data Analytics
  1. Advanced Persistent Threats (APTs) are stealthy and sophisticated cyberattacks that aim to gain unauthorized access and remain undetected for prolonged periods, typically orchestrated by skilled threat actors like nation-state groups or cybercrime syndicates.
  2. Microsoft Sentinel provides a cloud-native Security Information and Event Management (SIEM) solution that offers intelligent security analytics, threat intelligence, and the ability to collect and analyze data at scale.
  3. To combat APTs effectively, organizations can utilize Microsoft Sentinel to connect data sources, use workbooks for monitoring, analytics rules for correlating alerts into incidents, playbooks for automating common tasks, and hunting queries for proactively searching for threats.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Session Token Stealing Attacks with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 06 Oct 23
🕹 Technology Data Analytics
  1. Session token stealing attacks can lead to unauthorized access, data theft, account takeover, and other malicious activities.
  2. To detect session token stealing attacks, Microsoft Sentinel offers a comprehensive solution using advanced analytics, threat intelligence, and automation.
  3. Mitigate session token stealing by using HTTPS encryption, secure cookies, short-lived session tokens, strong passwords, multifactor authentication, and other security measures.

GroupBy #12: AWS re:Invent 2023, Druid and ClickHouse at Lyft, Apache Hudi History

VuTrinh. • 39 implied HN points • 05 Dec 23
🕹 Technology Data Analytics
  1. AWS re:Invent 2023 announced new features focused on improving data storage and processing. This includes faster storage options and AI capabilities for better data insights.
  2. Lyft switched from using Druid to ClickHouse for their analytics needs. This change was driven by a need for faster data query responses.
  3. Apache Hudi was created to help manage data in a more efficient way. It enables incremental data processing, making it easier to work with large amounts of information.

Using AI to build a robust testing framework

Inside Data by Mikkel Dengsøe • 24 implied HN points • 11 Jul 25
🕹 Technology Data Analytics
  1. It's important to establish a solid testing strategy for data models. Focus on verifying what can be objectively checked, keeping tests clear and manageable.
  2. Testing should prioritize sources and the transformations that impact data the most. Don't repeat tests for unchanged fields; it's better to test only what really matters.
  3. For final metrics, shift the focus from basic checks to business-specific assumptions. Use adaptive monitors for outliers instead of hard-coded limits to ensure flexibility.

Analytics Engineering (NOT DBT!) 101

Three Data Point Thursday • 39 implied HN points • 14 Sep 23
🕹 Technology Data Analytics
  1. Cyber security is evolving due to personalized threats; data-driven security is critical.
  2. Synthetic video presenters are emerging as a trend with growth potential in various sectors.
  3. Analytics engineering involves bridging the gap between data analytics and engineering through organizational change.
  4. Companies need to consider upskilling analysts or hiring analytics engineers to streamline data flow.

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

Rod’s Blog • 39 implied HN points • 03 Oct 23
🕹 Technology Data Analytics
  1. Cryptojacking involves using cloud resources to mine cryptocurrencies, leading to increased costs and performance issues for affected cloud customers.
  2. Common indicators of cryptojacking include high CPU/memory usage by unknown processes, unusual network traffic patterns, changes in cloud resource usage, and presence of malicious mining code.
  3. Microsoft Sentinel can help detect and respond to cryptojacking by analyzing data from various sources, applying advanced analytics, providing visualization dashboards, and enabling fast investigation and response using built-in playbooks.

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

Rod’s Blog • 39 implied HN points • 26 Sep 23
🕹 Technology Data Analytics
  1. Increase the cost of compromising an identity by banning common passwords, enforcing multi-factor authentication, and blocking legacy authentication.
  2. Detect threats through user behavior anomalies by ensuring event logging and data retention and by leveraging User and Entity Behavioral Analytics.
  3. Assess identity risk by conducting penetration tests, password spray tests, and simulated phishing campaigns to strengthen security controls.

Reinventing the Wheel of Data Activation

Sarah's Newsletter • 99 implied HN points • 26 Jul 22
🕹 Technology Data Analytics
  1. Data activation is not just a concern for the data team; it affects the entire data ecosystem and requires consideration of how data moves from one destination to another.
  2. Tools like Zapier and Make are essential for activating data, even bypassing warehouses, though maintaining software engineering principles like testing and version control is crucial for data teams.
  3. Integration bridges will always be necessary to connect applications that aren't warehouse-native, highlighting the importance of scalable systems and minimizing potential points of failure in data movement.

Shift-Left Analytics

SUP! Hubert’s Substack • 50 implied HN points • 22 Nov 24
🕹 Technology Data Analytics
  1. Shift-left analytics means doing analysis early in the data process. This helps in getting insights faster and making quick decisions.
  2. It focuses on checking data quality right away, so only reliable data is used. This leads to more accurate insights and avoids problems caused by bad data.
  3. Collaboration between teams is encouraged in this approach. By working together from the start, everyone can ensure their analyses are useful and aligned with business goals.

GroupBy #16: Uber's Anomaly Detection & Alerting System, many layers of data lineage

VuTrinh. • 19 implied HN points • 02 Jan 24
🕹 Technology Data Analytics
  1. Uber has developed an anomaly detection system called uVitals, which helps identify issues before they become major problems. It analyzes data patterns to catch anomalies early.
  2. Data modeling is essential for creating structured databases that allow for better analysis and comparisons. It's important for data projects to have clear designs.
  3. As the field of data engineering evolves, new roadmaps and resources are emerging to guide professionals in developing necessary skills. Staying updated can help engineers advance their careers.

The humanoid space is going crAIzy!

Robots & Startups • 39 implied HN points • 25 Mar 23
🕹 Technology Data Analytics
  1. Big-data analytics firm Databricks has open-sourced a new AI model that rivals ChatGPT with impressive speed and efficiency.
  2. The AI model was trained in less than three hours on a single machine, requiring far less data compared to other models.
  3. The field of generative artificial intelligence is continuously evolving with advancements like these, showcasing the rapid progress in AI technology.

The Tech Buffet #15: Build and Evaluate LLM Applications with TruLens

The Tech Buffet • 19 implied HN points • 03 Dec 23
🕹 Technology Data Analytics
  1. TruLens is a helpful open-source tool for evaluating and monitoring applications that use Large Language Models (LLMs). It tracks performance and helps you find the best settings for your models.
  2. The tool allows you to create feedback functions that measure how well the model's answers relate to the questions asked. This helps ensure the answers are relevant and grounded in the provided context.
  3. You can visualize the results and metrics in a dashboard, making it easy to understand how your model is performing and where improvements may be needed.

✅ African public relations agency recognised by The Financial Times

Wadds Inc. newsletter • 39 implied HN points • 04 May 23
💼 Business Data Analytics
  1. BHM, an African public relations agency, was named one of Africa's Top 100 fastest-growing companies by The Financial Times. This is a big deal for a privately owned firm.
  2. The agency focuses on helping African businesses reach international markets and helping foreign companies understand Africa. This is important as businesses look for new opportunities.
  3. BHM values hard work and community involvement, with a strong team made up of people who have grown within the company. They even created World PR Day to highlight the importance of public relations.

A Song of Junk and Value

davidj.substack • 95 implied HN points • 03 Jan 24
🕹 Technology Data Analytics
  1. Data dashboards can become like old, unused bookmarks, cluttering up space.
  2. Having standard data models and a semantic layer could lead to a more efficient data analysis experience.
  3. It's important to focus on creating value in data analysis by asking complex questions and optimizing processes.

Unprecedented Boom in Data Analytics & AI M&A

Sector 6 | The Newsletter of AIM • 19 implied HN points • 05 Nov 23
💼 Business Data Analytics
  1. There has been a big increase in companies buying up data analytics and AI businesses recently. Over 25 acquisitions happened this year, which is a lot more than the 15 last year.
  2. Major companies like Accenture, IBM, and Snowflake are very active in this space. Accenture alone spent about $2.5 billion on 25 acquisitions to boost its AI and analytics services.
  3. These acquisitions help companies improve their tech capabilities, like inventory management and engineering, making them more efficient and innovative.

On building data-driven VC in Emerging Market firsthand

nonamevc • 8 implied HN points • 13 Aug 25
💼 Business Data Analytics
  1. Data tools are essential for managing investments in multiple frontier markets. Without them, investors risk falling behind the competition.
  2. It's important to build a strong database that reflects local conditions since emerging markets don't follow the same growth patterns as startups in places like Silicon Valley.
  3. Combining different data signals provides better insights. Just looking at one metric isn't enough; you need to see the bigger picture to make smart investment decisions.

Benchmark Your Data Team

Inside Data by Mikkel Dengsøe • 24 implied HN points • 13 Feb 25
💼 Business Data Analytics
  1. Your data team size should be about 1-5% of your total company staff. Fintech companies usually have a higher percentage of data roles.
  2. The mix of different data roles is important. Having too many analysts can slow things down, while too many engineers might not deliver useful insights.
  3. Data salaries in Europe vary by experience. For example, a junior data role typically pays about $70k, while senior roles can reach $110k or more.

Big Tech Platforms’ Entry into Healthcare and Education

Platform Papers • 59 implied HN points • 13 Jul 22
🕹 Technology Data Analytics
  1. Big Tech platforms like Google and Apple enter regulated industries like healthcare and education by capturing sensitive data, leading to concerns about privacy and competition.
  2. In highly regulated industries, Big Tech firms focus on data capture and analysis, offering insights that can significantly impact incumbent service providers and drive innovation.
  3. For platform strategy, success in regulated industries hinges on superior data analytics capabilities, strategies to access and use sensitive data, and balancing stakeholder interests like privacy and security.

Why You’re Missing The Point Of Analytics

Three Data Point Thursday • 19 implied HN points • 05 Oct 23
🕹 Technology Data Analytics
  1. Analytics and Business Intelligence are about turning data into actionable insights, not just analyzing historical data.
  2. Separating data into 'hot' and 'cold' categories can lead to cost savings and less complexity in data management.
  3. Be cautious of the term 'data product' as it can have different meanings to different people, and ensure clarity in hiring, marketing, and tool usage.

OpenAI in Crisis

Sector 6 | The Newsletter of AIM • 19 implied HN points • 10 Aug 23
🕹 Technology Data Analytics
  1. OpenAI is facing serious challenges, including high losses, dropping user numbers, and increasing legal issues. This creates uncertainty about the company’s future.
  2. In July, the number of users on ChatGPT decreased by 12%, dropping from 1.7 billion to 1.5 billion. This decline raises concerns about the platform's popularity.
  3. If these problems continue, there's a chance that OpenAI might go bankrupt. The situation looks tough for the company right now.

Must Learn KQL Part 11: The Summarize Operator

Rod’s Blog • 19 implied HN points • 31 May 23
🕹 Technology Data Analytics
  1. The Summarize operator in KQL is used to aggregate and summarize data, making it more meaningful.
  2. The operator can be used for both simple aggregations like count, sum, and average, as well as more advanced functions like arg_min and percentiles.
  3. To master the Summarize operator, it's important to practice with different types of queries in tools like the KQL Playground.

Defying the Odds With Unconventional Strategies and Smarter Talent Scouting

Workforce Futurist by Andy Spence • 97 implied HN points • 23 Aug 23
🎾 Sports Data Analytics
  1. Talent scouting in football shows the value of unconventional strategies and data-driven decisions.
  2. Underdogs in any industry can succeed by being innovative and leveraging data analysis like Leicester City did in football.
  3. Adopting new approaches like Total Football or Agile methodology can lead to collective success and continuous improvement.

How to Get a List of Your Active Analytics Rules for Microsoft Sentinel

Rod’s Blog • 19 implied HN points • 12 Jan 23
🕹 Technology Data Analytics
  1. To get a list of active Analytics Rules in Microsoft Sentinel, use the Workspace Usage Report Workbook's Active Rules via Rest API module to download a CSV file of the results.
  2. You can also access a list of Analytics Rule templates by utilizing the Rule Templates via Rest API module.
  3. Consider exploring Twitter, LinkedIn, or subscribing to newsletters for further engagement with the topic.

Transforming biomanufacturing using software with Martin Permin

Axial • 52 implied HN points • 04 Mar 24
🕹 Technology Data Analytics
  1. Software and data analytics are being used to transform biomanufacturing, making it easier to control the complex variables involved in producing biological products.
  2. Invert, founded by Martin Permin, integrates with bioreactors and databases to help biomanufacturers manage and optimize their data using AI and analytics.
  3. Invert's platform streamlines bioprocessing by providing tools to plan experiments, monitor processes, analyze results, model scale-up, and collaborate with partners.

Understanding Isn't Enough

Sarah's Newsletter • 59 implied HN points • 08 Feb 22
🕹 Technology Data Analytics
  1. Value in data products comes from taking action, not just providing information.
  2. Vendors and data tools add significant value by influencing processes and saving time for users.
  3. Analytics products should aim to change behaviors by answering critical questions, prioritizing effectively, and continuously refining to ensure effectiveness.