All Hands on Data #82
After a nice long holiday break, All Hands on Data is back! Check out our first issue of the year below.
An AWS technician gives us a tour of a data center in eastern Oregon - see what it's like inside
Honestly, it's not really specifically a "data" article (I'm calling it one since it has the word "data" in "data center") but I honestly thought this was cool to see some of the physical resources, and people, behind the infrastructure all of our actual data runs around on. - John Forstmeier
Three Roadblocks to Using Data to Its Full Potential
Despite the explosion of cloud computing, less than a quarter of executives view their companies as data-driven or delivering on their data strategy. Bankuru identifies silos, outdated methods, and fragmented toolsets as the main culprits. The recommended solution? An integrated data product platform. I wonder if we've got an app for that... - Katt Baum
The impact of data analytics in Sports
One of the few things I've found fascinating about sports is the huge role that data plays in the success of some of the top athletic teams. This article gives you a fun glimpse into the world of sports analytics. - Angel Catalan
The Age-old Problem - Logging and Monitoring
This article echoes the same sentiment I have regarding logging particularly. When building different integrations for Shipyard, we have to ensure that our logging is sufficient, intuitive, and useful for debugging (both for end users and our team if need be). - Wes Poulsen
Mastering IoT Data Management for Business Success
There has been a huge proliferation of Internet of Things (IoT) devices in today's tech-driven landscape such as smartphones, smart watches, VR headsets, and so much more. These IoT devices collect so much data at a high volume, velocity, and variety. With all this information, there needs to be a well thought out strategy to leverage this data for your business. This articles goes through 5 different strategies for data management and discusses the future as well! - Reed Cowan
Why Data Quality Is More Important Than Ever in an AI-Driven World
If you're thinking about building out your own internal AI models, it's important to get data quality right. Mikiko touches on how the pendulum is swinging back towards towards data-centric AI models and if we want any improvement in the space, we're going to have to improve how we handle data quality. - Blake Burch