We’re pretty pumped to dive straight into 2019. We have some awesome content coming your way, including a brand new ebook and online course. But first, we want to pause for a hot sec to look back at last year and, more importantly, thank all of you.
Just three years ago, we were so proud to reach over 25,000 readers. We’ve been growing furiously since then, and last year’s stats blew us away. In 2018, just shy of 600,000 readers came together on our blog to build a community around the power of better data. Together, you all spent a total of 47,476 hours (or 5.4 years!) reading and sharing your knowledge.
Thank you all so much for your time, learnings and feedback! We can’t wait to continue growing this community and reaching new readers around the world.
Until this year’s content starts rolling out, here are the top 10 articles that caught your eye last year. Take a look and let us know if we missed any of your favorites.
One of our readers’ favorites, this blog has topped our charts for three years now. Sampling can feel intimidating, especially given how crucial it is for any survey. But it doesn’t have to be. Learn about 6 sampling techniques that help you keep your target population at the heart of your research.
Focus group discussions are a standard qualitative research method in the social sciences, where a moderator leads a semi-structured interview with a small group of participants. Ever wondered how to run one? Take a look at our step-by-step guide to design and carry out your own focus group.
Cross tabulation is one of the best ways to explore how different variables relate to one another. It’s great for revealing hidden relationships within categorical data, no coding or statistical knowledge needed! Here’s a quick blog and video about cross tabulation in Excel with pivot tables.
Any research is only as good as the data that drives it, so choosing the right method for data collection is critical. But this can be difficult. Take a look at this quick guide for the advantages, disadvantages and use cases of 4 different data collection techniques.
In October 2018, we open-sourced Camelot, a Python library and command-line tool that makes it easy for anyone to extract data tables trapped inside PDF files. Check out this blog for the why and how of Camelot. It got a ton of attention across data communities, and it even reached #1 on Hacker News!
In the past, M&E involved expensive pen-and-paper surveys. Today, with digital tools, it’s easier and more common to conduct tons of different types of evaluation. Read this blog to learn about 7 types of evaluation that can help your program deliver better results while reducing costs.
This tutorial will give you an accessible introduction on how to use machine learning techniques for your projects and data sets. In just 20 minutes, you will learn how to use Python to apply different machine learning techniques — from decision trees to deep neural networks.
Temporal visualizations (like line graphs, stream graphs, polar area diagrams, and more) are one of the best ways to represent data that changes over time. In this blog, we put together 7 handy temporal visualization styles for any time series data. Explore and let us know which is your favorite!
How do organizations get the numbers they need to prove that their work is effective? This is where quantitative research comes in. Read this guide to learn when quantitative research is useful, its advantages and disadvantages, and 4 quantitative methods you can use.
Apache Airflow has taken the data engineering ecosystem by storm. In this post, we wrote about how we used Airflow’s powerful workflow generation to power DISHA (a national data platform where Indian elected officials and ministers monitor the progress of 42 national schemes).
Before we end, we’d like to take a moment to thank you for being a constant supporter and avid reader of our blog. Your continued feedback and enthusiasm keeps us going. Wishing you a wonderful, successful and data-filled 2019!