The hottest Analytics Substack posts right now

And their main takeaways
Category
Top Technology Topics

Google Analytics or: How I learned to stop worrying and love the data

Mehdeeka • 0 implied HN points • 26 Apr 23
🕹 Technology Analytics Digital marketing Learning Tools Advertising
  1. Google Analytics has released GA4, bringing changes in data collection and reporting.
  2. To transition to GA4, marketers need to migrate before July 1, adjust event tracking, and set up Google Signals.
  3. Learning Google Analytics is approachable with free courses from Google and can help marketers make informed decisions.

Must Learn KQL Part 5: Turn Search into Workflow

Rod’s Blog • 0 implied HN points • 31 May 23
🕹 Technology Workflow Analytics
  1. Query structure with KQL can help identify and investigate specific data efficiently.
  2. Using the search operator in KQL can be a powerful tool to find relevant information but filtering results is essential to minimize effort.
  3. Learning KQL basics like the where operator and project operator can aid in creating precise queries for analytics rules in tools like Microsoft Sentinel.

Product Management Skills - Analytics and Instrumentation

Joseph Gefroh • 0 implied HN points • 17 Feb 24
💼 Business Product Management Analytics Instrumentation User Behavior Data Analysis
  1. Product analytics and instrumentation are crucial for Product Managers to make effective decisions and understand user behavior.
  2. Product Managers should have a strong grasp of product analytics, identifying what to instrument, and performing basic analysis themselves.
  3. Knowing who is using the product, what actions they are taking, and the context of their actions is essential for effective product analysis.
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Decentralize Your Data Journey: Introducing Web3 for Analytics Engineers Newsletter!

Web3 for Analytics Engineers • 0 implied HN points • 06 Jun 24
🕹 Technology Web3 Analytics Blockchain Decentralized Finance Data Analysis
  1. Web3 is transforming the world of data analytics, offering transparency, security, and immutability.
  2. The newsletter "Web3 for Analytics Engineers" provides exclusive tutorials, resource round-ups, best practices, and more to stay ahead in Web3 analytics.
  3. Topics covered include blockchain data analysis, decentralized finance, analytics tools like The Graph, and career growth strategies in Web3.

Baseball and Carbon Accounting, Part 1

Solar Powered Data • 0 implied HN points • 21 Aug 23
🎾 Sports Analytics Performance Accounting Statistics
  1. Measuring carbon emissions is challenging and involves various frameworks like the GreenHouse Gas Protocol and Science-Based Targets.
  2. Just like baseball teams aim to score more runs by balancing offense and defense, individuals in carbon accounting also strive to reduce emissions while enhancing carbon removal.
  3. In both baseball and carbon accounting, accurately attributing individual contributions is complex, and there is a need for improved methods to credit and analyze performance.

Ho We Use Language About Technology

The Digital Anthropologist • 0 implied HN points • 20 Sep 23
🕹 Technology Language AI Data Analytics Search Engines
  1. Language is a crucial human technology that has enabled collaboration, storytelling, and sharing different realities.
  2. Our language is evolving to describe technologies in a more human-like manner, impacting how we interact with and perceive technology.
  3. The way we use language to shape our relationship with technology is undergoing a significant shift, influencing our self-perception in relation to technology.

The Math Behind Running AI Models on Krutrim AI Cloud

Sector 6 | The Newsletter of AIM • 0 implied HN points • 05 Jun 24
🕹 Technology AI Cloud Analytics Software Infrastructure
  1. Ola is saving a lot of money by using Krutrim AI Cloud instead of larger cloud services like Microsoft Azure and AWS. This change helps them cut costs by about 15 crore INR each year.
  2. Cloud costs can be extremely high, as noted by the daily expense of 5 lakh INR that Ola was previously paying. Reducing these costs is important for businesses.
  3. The founder of Qure AI highlighted the issues with cloud spending, suggesting that it's a smart move for companies to look for more affordable options like Krutrim AI Cloud.

Benchmarking, the Indian Way

Sector 6 | The Newsletter of AIM • 0 implied HN points • 29 Sep 23
🕹 Technology AI Analytics Benchmarking Machine Learning Research
  1. Benchmarks are essential for testing the intelligence of large language models (LLMs), like GPT-4 and Llama 2. They help measure how well these models perform on various human-level tasks.
  2. Common benchmarks come from the US and cover a range of subjects, including math and history. For example, MMLU includes 57 tasks that test different knowledge areas.
  3. To create effective benchmarks, they often mimic real-world exams like the SAT or law school tests. This ensures the LLMs are evaluated in ways similar to how humans are tested.

If YouTube was a Chatbot

Sector 6 | The Newsletter of AIM • 0 implied HN points • 26 Sep 23
🕹 Technology AI Chatbots YouTube Analytics Learning
  1. YouTube is a great place for learning, offering a wide variety of content like DIY tutorials and recipes. People often prefer it over traditional text-based sources for quick and engaging explanations.
  2. OpenAI's latest chatbot, ChatGPT, has limitations such as outdated information until January 2022. This shows how YouTube can complement AI by providing updated and practical knowledge.
  3. Many people, including tech leaders, use platforms like YouTube for their learning needs, highlighting its importance in education and skill development.

The Subtle Art of Technology Enablement

Sector 6 | The Newsletter of AIM • 0 implied HN points • 01 May 23
🕹 Technology AI Business Innovation Deployment Analytics
  1. AI technologies have great potential for business innovation, but they need support from technology enablers like SAP and Microsoft to succeed.
  2. Many businesses, especially in India, focus mainly on getting results like faster processes and better monitoring rather than just the technology itself.
  3. Companies are looking for tech enablers that can provide specific knowledge to help them with their particular needs and challenges.

AI yesterday, today, and tomorrow

Sector 6 | The Newsletter of AIM • 0 implied HN points • 27 Dec 22
🕹 Technology AI Digital Innovation Analytics Data science
  1. AI is changing fast, and businesses need to adapt quickly to keep up. It's important for companies to build their digital futures on strong AI technology.
  2. The need for skilled AI professionals is growing, with many job opportunities in the field. Understanding AI tools and techniques can help people get ahead in their careers.
  3. Reports like 'The State of AI in India 2022' provide valuable insights into AI trends and developments. Staying informed can help individuals and businesses navigate the evolving AI landscape.

AGI vs human-level AI, Analytics IPOs & Russia's AI-powered artillery 🔫🎖

Sector 6 | The Newsletter of AIM • 0 implied HN points • 30 Jan 22
🕹 Technology Artificial Intelligence Data Engineering Analytics Military technology Emerging Tech
  1. AGI, or Artificial General Intelligence, is different from human-level AI. AGI aims to understand and learn any task just like a human, while human-level AI is designed for specific tasks.
  2. Data engineering is becoming increasingly important for organizations to improve their data workflows. Efficient data handling can help businesses make better decisions.
  3. Russia is using AI in its military applications, such as artillery. This shows how AI technology is being integrated into various sectors, including defense.

The Belamy | Top AI & Data Science Stories of the Week 💺🚁🛰

Sector 6 | The Newsletter of AIM • 0 implied HN points • 28 Nov 21
🕹 Technology AI Data science Big Data Machine Learning Analytics
  1. There is an upcoming information session for those interested in starting a career in data science.
  2. Early bird tickets for the Machine Learning Developers Summit 2022 are selling fast, so it's good to book soon.
  3. Subscribing to the newsletter gives you a week of free access to more AI and data science stories.

The AutoML Race, Starlink India & US Chief Data Scientist 🏇🌠🔭

Sector 6 | The Newsletter of AIM • 0 implied HN points • 10 Oct 21
🕹 Technology Data science Artificial Intelligence Analytics Telecommunications Research
  1. An AutoML race is happening, which involves competition in creating automated machine learning tools. This could make data science easier for everyone.
  2. Starlink is expanding its services in India, offering satellite internet. This can improve internet access in remote areas of the country.
  3. The US has appointed a Chief Data Scientist to lead data-related initiatives. This role will help shape data policies and improve the use of data across various sectors.

Data Engineer Salaries, QSim & Databricks 🗿📡🔮

Sector 6 | The Newsletter of AIM • 0 implied HN points • 05 Sep 21
🕹 Technology AI Data Engineering Salaries Conferences Analytics
  1. Data engineer salaries are important to know if you're looking to enter this field. They can vary widely based on experience and location.
  2. QSim is a tool that helps manage and analyze data efficiently. It's helpful in making data-driven decisions.
  3. Databricks is a popular platform for data engineering that makes collaboration easier. It helps teams work together on large datasets.

About Cloudera, eClerx & BERT in this week's Belamy

Sector 6 | The Newsletter of AIM • 0 implied HN points • 25 Jul 21
🕹 Technology AI Data science Big Data Machine Learning Analytics
  1. Cloudera is working on some interesting projects in data analytics. They focus on improving processes and making data more accessible.
  2. eClerx is involved in services that support data and analytics needs for businesses. Their role is to help companies make better decisions with their data.
  3. BERT is a powerful AI model that helps improve understanding of language in technology. It’s used to enhance communication and interpretation in various applications.

The Belamy | State Of Data Science In Domestic Indian Firms

Sector 6 | The Newsletter of AIM • 0 implied HN points • 27 Jun 21
🕹 Technology Data science Artificial Intelligence Machine Learning Hiring Analytics
  1. The Math Company is hosting a hackathon called MATHCO.THON to hire data scientists.
  2. Participants will solve a problem using classical machine learning to predict car prices based on 17 features.
  3. It's a great opportunity for data scientists to showcase their skills and potentially get hired.

Responsible AI in India, GCP vs AWS & Azure and more...

Sector 6 | The Newsletter of AIM • 0 implied HN points • 06 Jun 21
🕹 Technology AI Cloud Computing Data science Ethics Analytics
  1. Responsible AI is important in India, focusing on ethical use and fairness in technology.
  2. Google Cloud Platform (GCP), Amazon Web Services (AWS), and Azure all offer unique features for AI development, so choosing the right one can depend on specific needs.
  3. There are events and workshops available for those looking to improve their data science skills and learn more about AI tools.

Jugaad For Jab, SUPACE, MUM & more...

Sector 6 | The Newsletter of AIM • 0 implied HN points • 30 May 21
🕹 Technology AI Analytics Innovation Business Insights
  1. Jugaad means finding clever solutions to problems. It's all about using creativity and resourcefulness.
  2. SUPACE stands for 'Single-Window Unified Platform for Academic Collaboration and Engagement'. It aims to streamline processes in education and research.
  3. The Analytics100 Awards recognize leaders in analytics. It's a way to honor those who make a real impact using data.

Google I/O, Analytics industry in India & Women In Tech

Sector 6 | The Newsletter of AIM • 0 implied HN points • 23 May 21
🕹 Technology AI Workshops Analytics Women Industry
  1. There is a free workshop on June 17, 2021, about the oneAPI AI Analytics Toolkit, in partnership with Intel.
  2. oneAPI helps developers run machine learning models efficiently on different hardware without needing to rewrite code.
  3. The analytics industry in India is growing, and there is a focus on supporting women in tech within this evolving field.

India's Data Labelling Services, Chinese GPT3 & more in this week's Belamy

Sector 6 | The Newsletter of AIM • 0 implied HN points • 09 May 21
🕹 Technology AI Data science Software Analytics Innovation
  1. India is conducting a survey to assess the state of Responsible AI in the country, aiming to understand industry efforts and identify areas needing improvement.
  2. The Analytics100 awards for 2021 are now open for nominations, recognizing excellence in analytics and data science.
  3. Participation in the survey is encouraged, as it will help shape the future of AI practices in India.

Nvidia Grace, Nuance, AI Utopia & more on this week's newsletter

Sector 6 | The Newsletter of AIM • 0 implied HN points • 18 Apr 21
🕹 Technology AI Data science Software Analytics Education
  1. Nvidia is making waves with its new technology called Grace, which could help improve AI applications.
  2. Nuance is also in the news, hinting at exciting developments in voice recognition and AI communication.
  3. There's a focus on creating an AI utopia, where advanced technology makes our lives easier and opens up new possibilities.

The Belamy | Salary Study, Synthetic Data & Explainability

Sector 6 | The Newsletter of AIM • 0 implied HN points • 04 Apr 21
🕹 Technology Data science Artificial Intelligence Analytics Research
  1. In 2021, the average salary for analytics professionals in India was INR 13.4 Lakhs. This was a decrease from the 2020 average of INR 14.4 Lakhs.
  2. The study highlights ongoing challenges in the data science job market, including the impact of economic conditions on salaries.
  3. This research emphasizes the importance of understanding salary trends for career planning in the analytics field.

How to use Google’s CausalImpact

Logos • 0 implied HN points • 23 Dec 21
🕹 Technology Data science Statistics Machine Learning Software Development Analytics
  1. Google's CausalImpact helps you see how actions, like a marketing campaign, affect outcomes like sales. It predicts what would have happened without that action, making it easier to understand its impact.
  2. Using CausalImpact requires some basic coding in R, but even beginners can follow along. You'll collect data in a simple format, run the analysis, and see results visually and in tables.
  3. When using CausalImpact, it's crucial to choose the right control variables. They should correlate with your main outcomes but not be influenced by the actions you're analyzing.

DLD #1 | Data Landscape Digest 🗞️

Practical Data Engineering Substack • 0 implied HN points • 25 Aug 24
🕹 Technology Data Engineering Open Source Cloud Computing Software Development Analytics
  1. Data engineering is evolving rapidly, and staying updated on new tools and technologies is important for success in the field.
  2. Mastering the fundamentals, like SQL and Python, is crucial as they form the foundation for using advanced tools effectively.
  3. Open source solutions, like Apache Hudi and XTable, are gaining popularity and can provide great benefits for managing data efficiently.

Managing Dependencies Between Data Pipelines

Practical Data Engineering Substack • 0 implied HN points • 26 Aug 23
🕹 Technology Data Engineering Data Pipelines Workflow management Analytics Cloud Computing
  1. Managing dependencies between data pipelines is crucial for ensuring that upstream tasks are completed before downstream tasks start. This avoids issues with incomplete or faulty data.
  2. There are different techniques to manage these dependencies, ranging from simple time-based scheduling to more complex orchestrations that adjust based on the successful completion of previous tasks.
  3. Choosing the right method for managing pipeline dependencies depends on the complexity of the data workflows and the need for independence between different teams and tasks.

Get rid of user confusion with better empty states

CommandBlogue • 0 implied HN points • 10 Apr 24
🕹 Technology User Experience Product Design Analytics Digital Tools User engagement
  1. Empty states in apps can confuse users when there's no data to show. It's important to fill that space with meaningful actions.
  2. Instead of just saying 'no events found,' apps can encourage users to create new content, making the experience more engaging.
  3. Sometimes users want to see empty spaces as they indicate they've reached their goals, like finishing a to-do list. Celebrating that can enhance satisfaction.

[in case you missed it ] Data Science Weekly - Issue 472

Data Science Weekly Newsletter • 0 implied HN points • 11 Dec 22
🕹 Technology Data science Machine Learning AI Programming Analytics
  1. Machine learning can have unintended biases if the training data includes wrong patterns. It's important to check how models make decisions to avoid mistakes.
  2. You can use machine learning in Google Sheets without any coding or data sharing. There are easy tools available that let anyone analyze data and make predictions.
  3. Realtime machine learning is becoming a trend in tech companies, which means they want to make their data analysis and model scoring faster and more efficient.

[in case you missed it] Data Science Weekly - Issue 468

Data Science Weekly Newsletter • 0 implied HN points • 13 Nov 22
🕹 Technology Data science AI Analytics Privacy Machine Learning Software Engineering
  1. Before leaving Twitter, it's a good idea to download and save your data. This way, you can analyze important trends and insights you might miss if you just leave.
  2. The command line can make data processing easier and more readable. New tools like SPyQL help bridge familiarity with SQL and Python for better data analytics.
  3. Federated learning allows multiple users to train models without sharing their raw data. This technology can enhance privacy while still allowing valuable insights from diverse data sources.

[in case you missed it] Data Science Weekly - Issue 458

Data Science Weekly Newsletter • 0 implied HN points • 04 Sep 22
🕹 Technology AI Machine Learning Data science Deep Learning Analytics
  1. Machine learning has best practices that can help improve projects. A document from Google shares these tips for those who have some background in ML.
  2. There is a lot of hype around deep learning technology, leading to confusion about its actual capabilities. People have been predicting big changes in jobs and advancements, but many advancements are still awaited.
  3. AI can create interesting art from text prompts using tools like DALL·E 2. This showcases how technology can blend creativity and machine learning.

[in case you missed it] Data Science Weekly - Issue 457

Data Science Weekly Newsletter • 0 implied HN points • 28 Aug 22
🕹 Technology Data science Machine Learning AI Software Development Analytics
  1. AI has limits when it comes to understanding human language. It can't fully replicate how humans think because language itself is restrictive.
  2. Observable now offers Free Teams, making it easier for data people to collaborate publicly. You can create teams quickly and share notebooks without complicated setups.
  3. The backpropagation algorithm in machine learning is often misunderstood. It is more complex than just applying the chain rule repeatedly, and oversimplifying it can lead to problems.

[in case you missed it] Data Science Weekly - Issue 409

Data Science Weekly Newsletter • 0 implied HN points • 26 Sep 21
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. Trees are becoming a new model for understanding ecology and plant intelligence. They help researchers think more deeply about the environment.
  2. Effective machine learning often starts without actually using machine learning. It’s important to focus on gathering quality data and defining clear processes first.
  3. Business Intelligence (BI) tools are evolving, but they should focus on providing clear and complete answers to data-related questions for users.

[in case you missed it] Data Science Weekly - Issue 405

Data Science Weekly Newsletter • 0 implied HN points • 29 Aug 21
🕹 Technology AI Data science Machine Learning Podcasts Analytics
  1. Data teams should treat their work as products for their colleagues, focusing on collaboration to create effective solutions. This helps ensure that the end result meets the needs of those using the data.
  2. Many machine learning funds in finance fail due to common mistakes, but the few that succeed can deliver impressive results for investors. Understanding these pitfalls is key to improving success rates.
  3. OpenAI's Ilya Sutskever has been a major influence in AI, contributing to key advancements in deep learning. His work has played a big role in the evolution of intelligence in machines.

[in case you missed it] Data Science Weekly - Issue 399

Data Science Weekly Newsletter • 0 implied HN points • 18 Jul 21
🕹 Technology Data science Machine Learning AI Analytics Data Visualization
  1. There's a growing movement called 'Data for Good', which focuses on using data to help improve society. It's important to understand the different groups and initiatives within this space.
  2. Peer review in data science is crucial, especially for startups, but the process can be tricky. It's good to learn from experiences about what works and what doesn't.
  3. Big companies like Amazon collect a lot of data about their users, often more than people realize. It's important to be aware of how this data is being tracked and used.