Data Analyst Careers: Just Hype? (Everything to Know)

Data Analyst Careers: Just Hype?

A lot of the hype around data analyst careers has to do with external investment. Many businesses and organizations are increasingly relying on data analytics to help inform important decisions. That can lead to great job satisfaction, but if you’re stuck crunching numbers without context, it might be unsatisfying.

One Big and Two Small Monitors for Data Scientists: Better?

Data Scientist Monitors: One Big and/or Two Small Monitors?

Here’s everything about data scientists using one big monitor and/or two small monitors: If you have the space for it, this can be a highly effective setup that gives you a lot of freedom to organize information and digital tools in ways that improve your efficiency and efficacy. Alternatively, you could use only two monitors, three monitors of the same size, or one big monitor. All are viable. So if you want to learn all about data scientists working with one big and/or two smaller monitors, then you’re in the right place. Keep reading! Why Might Data Scientists Need More Monitors? What is this all about? In general, you can connect multiple monitors to a single computer, and when you do, you have a few options for how it will work. Most commonly, people like to set up multiple monitors so that they have independent displays.  Basically, this means that you can have different information on each monitor. As an example, you could have Netflix running on one monitor in full screen. On your second monitor, you can open up a web browser to look up the cast of the show (or movie) every time you can’t figure out why you recognize a face. At the same time, you can have a chat window open on the third monitor so that you can constantly send the random thoughts that occur while watching the show to one of your friends. That’s a very casual example, but it shows how multiple monitors can open up the ability to multitask on a computer without the need to shrink your digital workspaces down to a point where you can’t see what you’re doing. Now, let’s bring data scientists into this. In data science, it’s common to move information from one application to another on a regular basis. While doing this, it’s often easy to have multiple windows open. Add in that the data scientist