Showing results for "The Every" in Data Science

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, this book presents ninety-seven concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data.

Slow systems are frustrating. They waste time and money. But making consistently great decisions about performance can be easy, if you understand what's going on. This book explains in a clear and thoughtful voice why systems perform the way they do. It's for anybody who's curious about how computer programs and other processes use their time and about what you can do to improve them. Through a mix of personal vignettes and technical use cases, Cary Millsap reviews the process of improving performance and provides best practices for optimizing systems efficiently.

List the hottest buzzwords in business today and "analytics" is bound to come out near the top. But to most people, analytics implies complex tools and technical experts manipulating massive amounts and varieties of information (i.e.,"Big Data"). But complex Big Data analytics isn't the only game in town. And many people don't realize that a business doesn't need data scientists and complex tools to derive useful information and valuable benefits from any amount of raw data.