Little’s Law: For Estimation Only

Dr. Rachel Traylor heard Datrium reference Little’s Law during their presentation at Storage Field Day last month. Little’s Law provides a way to smooth out some of the random variables in queuing theory into something more deterministic. As Dr. Traylor explains, this makes it idea for quick estimations, but it’s not a silver bullet for such a complex field of mathematics.


Dialogue: What do We Mean by Predictive Analytics?

At Storage Field Day this month, Dr. Rachel Traylor heard from StarWind. They developed a prediction algorithm to proactively detect drive failures. This led Dr. Rachel to call for a dialogue with her fellow mathematicians and storage experts, what do we mean when we say predictive analytics?


ML, AI, and Marketing: A Conversation with Dr. Rachel Traylor

Inspired by recent solutions seen at Tech Field Day presentations, Rich Stroffolino and Dr. Rachel Traylor discuss what actually is Machine Learning and Artificial Intelligence. They break down how having an algorithm doesn’t equal machine learning, and how to spot when marketing overreaches with the terms.


Commentary: White Papers Don’t Impress Me Much

In this post, Dr. Rachel Traylor looks at the current state of industry white papers. After surveying some recent papers promising architectural overviews and technical details, she mostly found them more akin to marketing materials due to the lack of citations and substance. She expresses this frustration with a little help from Shania Twain.


Commentary: Infrastructure Considerations for Machine Learning

In this post, Dr. Rachel Traylor looks at machine learning in the enterprise. The issue is machine learning takes vast swaths of varied data to produce useful results, something that might constrain a production database. Dr. Traylor looks at the Sky Infrastructure Actifio presented at Tech Field Day in September as a possible solution. This saves a “golden copy” of data, with changes saved incrementally, and able to serve up “virtual copies” much more efficiently for testing.


Commentary: High Level Data Filtration

Dr. Rachel Traylor looks at Ixia’s approach to real-time network visibility. This uses high level data filtration from a database of known bad actors to quickly eliminate large chunks of data from their analysis engine. This allows them to not have to process the entire firehose of network data and gives each successive analysis layer additional efficiency.


The Gravity of Mathematics: Summary of Tech Field Day at SDC 2017

For decades, technology companies made sustained investments in pure mathematical research. In this post, Dr. Rachel Traylor outlines how mathematical research had very real impacts on the development of storage. This includes queuing theory, information theory, statistical process control, error correction codes. She makes the case that it would be a mistake for modern storage companies to not continue this investment.


Commentary: Returning to Fundamentals in Tech

Dr. Rachel Traylor joined Tech Field Day as a delegate last week. Hearing from the presenting companies, she was struck at the difference in approaches between mathematicians and engineers. The former are much more deliberative before proclaiming a solution, whereas the latter often don’t worry about a solid foundation before moving to a solution. In SkyPort Systems, Dr. Traylor found a company bucking this trend, building their solution from the ground up to embrace security principals on a zero-trust model.


Dr. Rachel Traylor

Dr. Traylor is a freelance mathematician who has done groundbreaking research in server reliability theory and probability theory. She founded the Math Citadel, a place for open publication of research and accessible posts on topics in both basic and advanced mathematics. All her work is published there. She co-developed the first formal notion of dependence […]