We are excited to announce that Mammoth is now a destination in Segment’s rich catalog! Track every user action with Segment Segment is a single platform that collects, stores, and routes your user data to hundreds of tools at the flick of a switch. Segment is a great platform for collecting user interaction data from […]

If you struggle with data cleansing, normalization, standardization or consolidation, this article is for you. Mammoth’s powerful new feature will save you time, money and all the headaches.

Spreadsheets are the lifeblood software for most organizations. But for a small (and rapidly growing) population of analysts, there is an unmet need for something more. The pains of managing their data are growing on a daily basis with no real solution in sight. The widening gap between Excel users versus SQL or R programmers is becoming a real problem. The most basic set of tasks of managing rows and columns takes unreasonable amounts of time and involves costly resources. For organizations ignoring these problems, this means either squandering away potential growth opportunities or losing their competitive edge, and in most cases both.

We write code every day, solve the most complex of issues, and diligently come up with the most simple and sophisticated solutions for every complex problem. We are Engineers, Designers, Lawyers, Business experts and more. But most importantly we wake up every day, and proudly call ourselves as problem solvers. Yet, there’s one problem for which we seem to come up with the weakest of solutions. Much has been spoken about it, and still so much to be done. Let’s talk about the Women in Tech.

While JSON seems to have taken over the world, there are glaring problems for both developers and non-techies alike — attempting to parse and manage the data.

The Biotechnology, Bioinformatics and Computational Biology fields are growing on multiple fronts, including data volume and complexity. The amount of data generated is far larger than the ability to consume or make sense of it. While data volume may sound like a problem, there is another more significant and pressing issue, specifically around existing processes and general accessibility to data.