Editor’s note: This article was originally published on the Iteratively blog on March 15, 2020.
As folks who constantly deal with data, finding the right resources to refer to in times of need is a challenge.
(Trust me: a Google search yields a number of results with more zeroes than I can count.) To solve this, we created an internal document with the best five of every kind of resource that data folks generally refer to. Now we’ve decided to publicize it for everyone’s benefit.
Without further ado, let’s take a look.
If you love reading in your downtime, The Analytics Engineering Roundup is perfect for you. It’s compiled by Tristan Handy from dbt Labs, the creators of hugely popular open source tool dbt. The best part is that they include four to five of the best reads along with a simple summary for each article.
If you don’t know it already, Mode is a data science platform that brings together a SQL editor, Python notebook, and R where you can perform data visualization, create charts and dashboards, and then share your analysis with a click. They write a great newsletter with some of the best analytics and data science pieces.
Data Elixir is one of the top newsletters in the market sharing the best articles on machine learning, data visualization, analytics, and strategy. Delivered every Tuesday, it’s a weekly newsletter with 30,000+ subscribers.
One of the most popular newsletters among data folks, the newsletter started in 2013 and has churned out 361 issues to date. It begins with an Editor Picks section and quickly moves onto listing a bunch of data science articles and videos. On top of that, it includes a section for job openings, tutorials, and books as well. Sent out every Thursday, DSW deserves your attention.
This award-winning newsletter is one of the most renowned newsletters covering topics like machine learning, data science, data mining, big data, and analytics. It’s definitely worth your time!
Storytelling isn’t new. It’s one of the ace strategies to market your brand. But storytelling with data? It’s uncommon. This book by Cole Nussbaumer Knaflic clearly illustrates the power of storytelling and how you can organize the story around data. With countless real-world examples, this book packs a punch.
Ask any startup founder to recommend a book on analytics. Seven out of 10 times they will recommend “Lean Analytics” by Alistair Croll & Benjamin Yoskovitz. This book essentially teaches you to focus on the one-metric that matters, which enables you to narrow your focus and strive forward. If you want to understand how to take your idea to PMF using data, this is the book for you.
All businesses face risk and uncertainty. A large part of the reason is due to the fact that not everything is measurable. This book by Douglas W. Hubbard attempts to challenge that. With stellar examples, this book offers you substantive steps to help you measure the immeasurable in business.
Do you know who you are (online)? This book’s tagline literally is, “What our online lives tell us about our offline selves.” A delightful read by Christian Rudder, founder of one of the world’s biggest dating websites OkCupid, Datacylsm dives deep into the science of human behavior and how data is used to accelerate the same.
Slept through Stats 101? No worries. Charles Wheelan, also the author of Naked Economics, strips away the clandestine and technical details and purely focuses on the primary intuition that drives statistical analysis.
Although it’s not directly related to data analytics, it’s still a good read for PMs and founders. Objectives and Key Results (OKRs) is a goal-setting system where objectives define what we seek to achieve and key results are how those top-priority goals will be attained with specific, measurable actions within a set time frame. For OKRs to be successful, teams need to be able to trust the data they’re capturing. With in-depth case studies from Bono and Bill Gates, this book reveals how OKRs help ensure growth, particularly at a startup.
Codecademy is widely known for its tech courses. However, their data science section is also a fan favorite among those who are aware of it. From a full-fledged data science learning path to short courses on advanced python and data analysis, the range is unending.
Especially popular for their nano degrees, Udacity is a major player in this space. Their data science courses are revered and constantly evangelized by folks dealing with data. They have helped countless individuals and organizations learn and implement data the right way through state-of-the-art tools and processes.
Datacamp is fairly new to the market but we love the simplicity of their courses. They have two separate tracks (skill-focused & career-focused) for folks who want to dedicate time for long-term courses. Also, the sheer variety of courses is worth the mention.
Decision making is always more precise and accelerated with data. This course gives you an overview of why data is important, how Big Data is used, a framework for data analysis, and all the necessary tools. It’s a Coursera course that was created by the renowned audit and consulting firm, PwC.
This data science course is a bit different in its approach. The course takes a purely practitioner’s point of view where you learn about topics such as data compilation, preparation, and modeling throughout the life-cycle of data science. It’s a foundational course and is best for folks who are just getting started or someone who wants to understand the basics of data science.
Measure Chat is one of those communities which is 100 percent value-driven. Best and brightest analytic minds across the globe gather here to discuss everything under the sun pertaining to data. A must join for data folks!
Locally Optimistic is an informal group of aspiring and veteran practitioners where you get to share your thoughts and experiences in working with data. They also run a blog that pertains to data organizations.
Analytics Vidhya provides a knowledge portal centered around a community. You can take courses, learn from their blogs and discuss important stuff with fellow members. Their discussion community is quite famous among data analytics professionals. From analytics careers to the latest tools and methodologies, you’ll find any discussion thread you’re seeking.
Reddit is one of those places where you literally find any information you seek. With over 200k members, r/datascience is one of the most popular and active subreddits across the social media platform. Need help with something “data?” Just drop a post and you will get your answer in no time!
Kaggle is an online platform run by Google where data scientists, ML engineers and folks from similar professions compete with each other to solve data science problems. They also run a stellar slack community where you can meet top data scientists from across the globe.
data.world is a product that unites and classifies all of your business’s data, metadata, and analysis within an intuitive user experience to help technical and non-technical people collaborate using their preferred tools. They also run their own social media community where data lovers can find and share interesting data, connect with like-minded people, and collaborate to solve problems faster.
Ruben Ugarte, founder and principal at Practico Analytics, helps top companies use data to make higher quality decisions to lower acquisition costs, save hundreds of thousands of dollars and reclaim wasted time. He also runs this awesome blog where he talks about data analytics frameworks, tools, and other related stuff.
A lot of product companies today focus on top of funnel or getting new sign-ups. However, just a 5 percent increase in customer retention can increase the company’s revenue by 25-95 percent. Amplitude’s guide helps professionals understand and implement retention strategies.
Well, that concludes it. This is exactly what we refer to when we find ourselves in a spot or folks ask us for recommendations. Then again, this is not an exhaustive resource.
Do you think we missed something? Join the Amplitude community and let us know.