Data science is a rapidly evolving field, and staying current on the latest developments and trends can be challenging. While there are popular blogs that many people follow, it's essential to pay attention to the lesser-known blogs that can provide unique perspectives and groundbreaking ideas.
In this post, we've handpicked the top 10 data science blogs you've probably never heard of. These hidden gems offer valuable information, thought-provoking insights, and inspiration for your own data-driven journey. So dive into these uncharted territories and expand your horizons with our curated list of data science blogs just waiting to be discovered.
1. Thuwarakesh Murallie's Data Analytics Blog
About the Author:
• BSc (Hons) in Statistics from the University of Peradeniya
• Experience in Academia, Healthcare, FMCGs, and Freight & Transport
• Expertise in data pipelines, machine learning models, and data analytics for strategic decision-making
Highlighted Article: "How to Become a Terrific Data Scientist (+Engineer) Without Coding"
Excerpt: “People lose interest in data science because some aren’t good at programming. They couldn’t get their head around even an intuitive language such as Python. Yet, for others, it’s pretty natural. But these aren’t inabilities, but different abilities. This story will change your perspective. Even if you can’t or don’t want to program, you can become an exceptional data scientist. Critical thinking and some data literacy will make you even capable of managing a data project.”
2. Anushka Bajpai's DataScoop
About the Author:
• Bachelor's in Technology (Electronics and Communications)
• Satellite Network Engineer at Viasat Inc.
• Diploma in Deep Learning from IIIT-B
• Master's candidate at Liverpool John Moores University, London, UK
Highlighted Article: "101 DATA SCIENCE with Cheat Sheets (ML, DL, Scraping, Python, R, SQL, Maths & Statistics)"
Excerpt: “Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all these functions, operations and formulas for each of concept. That’s why we have cheat sheets and summaries. They help us access the most commonly needed reminders for making our Data Science journey fast and easy.”
3. Zach Quinn's Pipeline: A Data Engineering Resource
About the Author:
• B.A. in Journalism and M.S. in Data Science
• Founder of Pipeline: A Data Engineering Resource on Medium
• Experience in data pipelines, Python, SQL, and data journalism
Highlighted Article: "3 Data Science Projects That Got Me 12 Interviews. And 1 That Got Me in Trouble."
Excerpt: “Before I share my work and process, I have to acknowledge that while I had no formal tech background, I did have the following traits recruiters and managers found desirable (based on feedback, not my egoism, I swear):
• A master’s degree in data science
• Domain knowledge (I purposely applied for roles within the media, education and hospitality industries, all of which I’ve worked in before)
• Python/SQL/BI development experience (course work, personal projects)
• Communication skills (a huge plus, even for junior engineers or developers)”
4. Mikkel Dengsøe's Data Insights
About the Author:
• Co-founder of Synq
• Former Head of Data Science, Operations & Financial Crime at Monzo Bank
• Former CEO of Digitbrew (formerly Data Hygge)
• Expertise in data reliability, data teams management, and data-driven user experience
Highlighted Article: "Data salaries at FAANG companies in 2022"
Excerpt: “US-based data jobs are paid well. Particularly if you’re among the lucky 440 working in a data role at Netflix. If you’ve read Reid Hastings book No Rules Rule you’ll know this is not by chance. Netflix has a policy where they encourage their employees to interview different places and bring back the offers they get. If Netflix sees that they’re being outbid they’ll increase your salary and do the same for everyone across the company in similar roles.”
5. Anna Wu's Data Analytics Insights
About the Author:
• SQL and Data Analytics expert
• Former Senior Manager Analytics at Stripe
• Former Analytics Manager at Uber
• Experience at Meta and Amazon
• Bachelor of Applied Science in Computer Science from Duke University
Highlighted Article: "Google Data Scientist Interview Questions (Step-by-Step Solutions!)"
Excerpt: “A data scientist role at Google is one of the most sought-after positions in the tech industry. This is because data scientists at Google are responsible for some of the most important projects at the company, such as developing algorithms to improve search results, improving Google Maps, and developing new features for products like Gmail and YouTube.”
6. Youssef Hosni's AI & Data Science Insights
About the Author:
• Computer Vision Researcher and Data Scientist
• Ph.D. Researcher at the University of Oulu
• Data Science Mentor and Writer
• Passionate about AI, data science, and career guidance
Highlighted Article: "13 SQL Statements for 90% of Your Data Science Tasks"
Excerpt: "Structured Query Language (SQL) is a programming language designed for managing and manipulating relational databases. It is widely used by data analysts and data scientists to extract insights from large datasets. SQL is a powerful tool that can be used to perform a wide variety of data manipulation tasks, including filtering, sorting, grouping, and aggregating data. In this article, we will cover 13 essential SQL statements that will help you perform 90% of your data science tasks. These statements are easy to understand and implement and will provide you with a solid foundation for working with SQL."
7. Zuzanna Sieja's Insights
About the Author:
• Junior Marketing Specialist at DLabs.AI
• Special interest in e-commerce and social media
• Passionate about cats and data science education
Highlighted Article: "11 Books Every Data Scientist Must Read"
Excerpt: "The recommendations cover everything from data science to data analysis, programming, and general business. Meaning you'll have a better understanding of all the mechanisms to make you a more effective data scientist if you read even just a few of these books."
8. Amit Chauhan's Data Science Journey
About the Author:
• Data Scientist
• Specializes in AI, ML, DL, and Azure Cloud
Highlighted Article: "Work on Text and Binary Files with Python Example"
Excerpt: "File management working with databases in data science and machine learning. Python supports file handling and enables users to read and create files as well as perform a variety of other operations on files. Like many other ideas in Python, the idea of file management has been extended to several other languages, but their implementations are either difficult or time-consuming. Python handles text and binary data differently, and this is crucial."
9. Terence Shin's Data Science Insights
About the Author:
• Senior Data Scientist at KOHO
• Fintech specialist
• MSc and MBA degrees
Highlighted Article: "How I’d Learn Data Science If I Could Start Over (4 Years In)"
Excerpt: "And so, 'How I’d Learn Data Science if I could start over' really starts with the question, 'what aspects of data science am I interested in?' Is it statistical analysis? Is it deep learning? Is it building visualizations? Understanding this will help with prioritizing what skills to learn first. And if you’re unsure what aspects of data science you’re interested in, that’s completely okay because there are fundamental skills required by all types of data scientists that you can start with (as far I know)."
10. Cassie Kozyrkov's Decision Science Chronicles
About the Author:
• Chief Decision Scientist at Google
• Expert in stats, ML/AI, and data science
• Public speaker and leader
• Academic expertise in various fields
Highlighted Article: "Becoming a 'Real' Data Analyst"
Excerpt: "In my opinion, learning the tools is the easy part. The hard part is adopting the analytics mindset, which is what the next differences are all about. Starting with this one: the expert has developed an all-encompassing disrespect for data. Yes, you heard me. Only a newbie pronounces 'data' with a capital 'D' and treats it as something magical. Professionals have been burned and had their hearts broken enough times to learn the hard way that data is just some stuff that humans decided to write down in electronic form."
The data science world is vast and ever-changing, and countless resources are available to help you navigate it. This list of top 10 secret data science blogs offers a wealth of knowledge, covering topics such as data analytics, machine learning, career guidance, and even the softer skills required to excel in this field. These blogs provide unique perspectives and invaluable information, from Thuwarakesh Murallie's insights on how to succeed as a data scientist without coding to Cassie Kozyrkov's advice on adopting the analytics mindset.
Each blog in this list has something different to offer, and exploring them will undoubtedly help you broaden your understanding of data science and its various applications. Whether you're new to the field or an experienced professional, you're bound to find something valuable in these lesser-known blogs. So, dive into these hidden gems, enrich your knowledge, and let these exceptional authors inspire you to excel in data science.
You can also learn more about data science bootcamps that are provided here at Thinkful.