The hottest Data Analytics Substack posts right now

And their main takeaways
Category
Top Business Topics

High-performance engineering managers

Elevate • 1113 implied HN points • 09 Jan 24
💼 Business Management Leadership Data Analytics Training Employee engagement
  1. Effective managers have key traits that significantly impact employee performance, happiness, and retention, as proven by Google's Project Oxygen.
  2. Soft skills like coaching, communication, and support are more valued than technical expertise by employees, emphasizing the importance of emotional intelligence in management.
  3. Using rigorous people analytics, organizations can identify and develop high-impact management behaviors specific to their unique culture, leading to improved leadership and employee satisfaction.

The evolution of user onboarding at Databox

Kyle Poyar’s Growth Unhinged • 339 implied HN points • 28 Feb 24
💼 Business Data Analytics Subscription Models
  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.

Special Edition 🔥: Analytics As Applied Accounting | Lauren Balik

Data Analysis Journal • 687 implied HN points • 08 Jan 24
🕹 Technology Data Analytics BI Tools Data Platforms AI Privacy
  1. Becoming a data analyst or engineer through bootcamps is becoming less prevalent due to economic factors.
  2. Analytics leaders face challenges in setting boundaries and avoiding overlap with finance teams in accounting functions.
  3. Decentralized data team setups are generally more efficient, and the future may see more of this with changes in tax regulations.

Eventify everything - Data modeling for event data

timo's substack • 117 implied HN points • 06 Feb 24
🕹 Technology Data Modeling Data Analytics
  1. Data modeling for event data involves handling various source data and supporting diverse analysis use cases.
  2. Event data modeling can be organized into layers, from raw source data to consumption-ready data for analytics tools.
  3. Qualifying events to activities in event data modeling helps improve data usability and user experience in analytics tools.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Transforming biomanufacturing using software with Martin Permin

Axial • 52 implied HN points • 04 Mar 24
🕹 Technology Software Data Analytics AI Synthetic Biology
  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.

Underutilized.

Cybernetic Forests • 279 implied HN points • 05 Nov 23
🕹 Technology AI Data Analytics Digital Art Social media
  1. Generative AI is essentially a new form of Big Data, emphasizing pattern analysis to automate processes.
  2. The expansion of data is essential for the existence of generative AI tools, demonstrating a rebranding of data analytics into AI.
  3. The tech industry's focus on data monetization and predictive analytics has led to virtual interactions that distance us from real human connection and community.

Introduction To Event-Based Analytics - Issue 142

Data Analysis Journal • 569 implied HN points • 03 May 23
🕹 Technology Data Analytics Product Analytics Data Management
  1. Event-based analytics is crucial for understanding user behavior and product performance.
  2. Session-based analytics focus on website traffic while event-based analytics track user interactions like clicks and actions.
  3. Implementing and maintaining event-based analytics can be challenging due to issues with data integration and interpretation.

Product-led marketing to reach 400,000 users

Kyle Poyar’s Growth Unhinged • 283 implied HN points • 17 May 23
💼 Business Marketing Data Analytics Messaging Experimentation Focus
  1. Product-led marketing involves aligning the product, marketing, and customer success for growth.
  2. Focus on user intent and eliminate unnecessary distractions in marketing efforts.
  3. Layer in the right messaging, experiment, triage, choose your battles wisely, and stay focused to reach milestones like 400,000 users.

Why product analytics is completely different than BI

timo's substack • 294 implied HN points • 28 Feb 23
🕹 Technology Data Analytics Product Management Business Intelligence Data Collection Data Modeling
  1. Marketing analytics, BI, and product analytics have different requirements for source data and data handling.
  2. Product analytics involves more exploration and pattern-finding compared to marketing analytics and BI.
  3. Adopting product analytics requires a different approach, mindset, and tool compared to traditional analytics setups.

Microsoft Fabric Mirroring: Revolutionising Data Access and Real-Time Insights

Data Plumbers • 2 HN points • 01 Apr 24
🕹 Technology Data Analytics Data Warehousing Database Management Data Integration
  1. Microsoft Fabric Mirroring is a transformative technology that revolutionizes data access and real-time insights in organizations.
  2. Mirroring enables universal access to various databases, real-time data replication, and granular control over data ingestion into Microsoft Fabric's Data Warehousing experience.
  3. With Mirroring, organizations can achieve zero-ETL insights, leverage the innovative capabilities of Fabric's OneLake repository, and bridge the gap between data and action for swift adaptation and success.

About Data User Experience

timo's substack • 78 implied HN points • 28 Sep 23
🕹 Technology User Experience 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

The Dawn of the AI-Military Complex

GOOD INTERNET • 17 implied HN points • 25 Jan 24
🕹 Technology Military AI Ethics Data Analytics Cybersecurity
  1. Advancements in AI technology are being actively used in military operations, with drones and autonomous systems playing a significant role.
  2. There is a risk of overtrusting AI systems in life-or-death decisions on the battlefield, which can lead to ethical dilemmas.
  3. The future of warfare may involve AI systems taking a central, decision-making role, potentially changing the landscape of conflicts and military operations.

Defying the Odds With Unconventional Strategies and Smarter Talent Scouting

Workforce Futurist by Andy Spence • 97 implied HN points • 23 Aug 23
🎾 Sports Football Data Analytics Success Strategies Performance Metrics
  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.

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 Security Cloud Computing Data Analytics Automation Threat Detection
  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 Cybersecurity Data Analytics Cloud Computing Threat Detection Automation
  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.

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 Cybersecurity Cloud Computing Data Analytics Threat Detection
  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 Cybersecurity Data Analytics Threat Detection Risk Assessment
  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.

Analytics Engineering (NOT DBT!) 101

Three Data Point Thursday • 39 implied HN points • 14 Sep 23
🕹 Technology Data Analytics Cyber Security AI Organizational Change
  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.

Modernity != Value

Sarah's Newsletter • 299 implied HN points • 19 Apr 22
🕹 Technology Data Analytics Data Tools Data Platforms Problem Solving
  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.

Why You’re Missing The Point Of Analytics

Three Data Point Thursday • 19 implied HN points • 05 Oct 23
🕹 Technology Data Analytics Data Management Data products Data Storage
  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.

The Sorcerer’s Apprentice: Applied AI for Data

Perspectives • 3 implied HN points • 09 Feb 24
🕹 Technology AI Data Analytics Natural Language Processing Automation Machine Learning
  1. Illustrates the importance of utilizing AI in data analytics wisely to avoid potential risks and maximize benefits
  2. Provides practical tips on how to apply AI in data work, such as using tools for natural language processing, coding assistance, and documentation
  3. Highlights the gap between current AI capabilities and the ideal automation of analytics, emphasizing the role of asking the right questions in data work

Reinventing the Wheel of Data Activation

Sarah's Newsletter • 99 implied HN points • 26 Jul 22
🕹 Technology Data Analytics Data Integration Automation Software Engineering
  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.

The Anatomy of a Clinical Trial

Superfluid • 26 implied HN points • 19 Apr 23
🏥 Health & Wellness Clinical Trials Logistics Data Analytics Future Trends
  1. Clinical trials are expensive and crucial for determining the efficacy and safety of new drugs.
  2. There are multiple stakeholders involved in running a clinical trial, each with important roles to play.
  3. Challenges in clinical trials include patient recruitment, trial logistics, and data analytics, but there are innovative startups working on solutions.

AI: Make or Build

TeamCraft • 6 implied HN points • 13 Nov 23
🕹 Technology Data Analytics Culture
  1. Focus on a few high-impact AI projects aligned with core company objectives.
  2. Apply AI to your core value proposition for strategic value.
  3. Prioritize building AI capabilities around high strategic value and core value propositions.

Must Learn KQL Part 11: The Summarize Operator

Rod’s Blog • 19 implied HN points • 31 May 23
🕹 Technology Data Analytics Programming
  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.