A while back, we made a list from A to Z of a few of our favorite things in big data and data science. We have made a lot of progress toward covering several of these topics. Here’s a handy list of the write-ups that I have completed so far:

**A** – **Association rule mining:** described in the article “Association Rule Mining – Not Your Typical Data Science Algorithm.”

**C – Characterization:** described in the article “The Big C of Big Data: Top 8 Reasons that Characterization is ‘ROIght’ for Your Data.”

**H – Hadoop (of course!):** described in the article “H is for Hadoop, along with a Huge Heap of Helpful Big Data Capabilities.” To learn more, check out the Executive’s Guide to Big Data and Apache Hadoop, available as a free download from MapR.

**K – K-anything in data mining:** described in the article “The K’s of Data Mining – Great Things Come in Pairs.”

**L – Local linear embedding (LLE):** is described in detail in the blog post series “When Big Data Goes Local, Small Data Gets Big – Part 1” and “Part 2“

**N – Novelty detection (also known as “Surprise Discovery”):** described in the articles “Outlier Detection Gets a Makeover – Surprise Discovery in Scientific Big Data” and “N is for Novelty Detection…” To learn more, check out the book Practical Machine Learning: A New Look at Anomaly Detection, available as a free download from MapR.

**P – Profiling (specifically, data profiling):** described in the article “Data Profiling – Four Steps to Knowing Your Big Data.”

**Q – Quantified and Tracked:** described in the article “Big Data is Everything, Quantified and Tracked: What this Means for You.”

**R – Recommender engines:** described in two articles: “Design Patterns for Recommendation Systems – Everyone Wants a Pony” and “Personalization – It’s Not Just for Hamburgers Anymore.” To learn more, check out the book Practical Machine Learning: Innovations in Recommendation, available as a free download from MapR.

**S – SVM (Support Vector Machines):** described in the article “The Importance of Location in Real Estate, Weather, and Machine Learning.”

**Z – Zero bias, Zero variance:** described in the article “Statistical Truisms in the Age of Big Data.”