One of the biggest problems in data management and data science is being able to obtain “good” data. You need to gather sufficient data from a substantial array of subjects who fit your study’s requirements, and ensure the accuracy of the data... otherwise, any conclusions you draw could be biased or skewed.
But assume for a moment that your data is already solid. That’s no guarantee of success, unfortunately: It’s like having all the ingredients of a pizza in one place but lacking the ability to tie those ingredients together, and cook them appropriately.
Without the latter, you may not get the final product you seek. In addition to considering the quality of your data, consider the quality of your dashboard; it’s more important than you might assume.
Why Your Dashboard Matters
Here are some of the reasons your dashboard should matter as much as your data.
Access. First, you need to be able to call up as much of the data as possible. If your dashboard highlights a handful of key variables, but makes others harder to see or understand, it could lead you to false conclusions or undersell what you’ve been able to gather.
Manipulation. Your dashboard is also what empowers you to tweak different variables, generate comparative reports, play around with different timeframes and demographics, and ultimately give you the “full picture” of your subject matter.
Showcasing. Depending on your company and your position, you’ll probably need to make sure other people can see and understand the data before you can reap its true content. That’s where visualizations come into play. Your dashboard should make it easy for people to wrap their minds around your findings, regardless of whether they were involved in accumulating them.
In the current data-driven marketplace,there are hundreds of unique dashboards you can use to analyze and display information. How to choose which would be best for your needs?
Ease of use. First, you should make sure your dashboard is easy to use, both for you and the others on your team. If it sucks up a few hours of study and playing around to learn the basic functions, it will probably include features you miss entirely. Beyond that, it may cost hours of company time to get new hires up to speed, and anyone outside your team who tries to use or view the platform could be baffled. Your dashboard should be more or less intuitive, if possible.
Variable controls. You’ll also need a platform that has sufficient variable controls, which will allow you to create your own custom reports and change them dynamically as you spend more time on the platform. It should be relatively easy to account for new variables, reframe your data with new parameters, and dig deeper to unearth further insights. Cookie-cutter reports and controls aren’t likely to meet your needs in today’s business arena.
Design aesthetics. Don’t discount the value of the aesthetics of your dashboard. Your data visuals should exist to tell a story about your data, both to people on your team and outside of it. If that story is hard to follow, or looks boring, your audience either won’t be able to draw accurate conclusions, or won’t be inspired to do so.
Feature approachability. What good is a dashboard with a ton of features if you only need a few of them to obtain the results you need? You might be tempted to opt for a dashboard that offers lots of bells and whistles, but those perks won’t necessarily offer the best fit for your organization. Instead, find a platform with features that will contour to your needs, and are relatively easy to find and master.
Access and share-ability. Finally, you need to make sure there won’t be any obstacles with regard to access or share-ability. Most organizations will want a dashboard with multiple “access” levels, including administrative and view-only accounts. You should also weigh how customized reports can be displayed, exported, and circulated to others. This is one of the most important functions of data gathering and distribution.
Your dashboard is more than just a user interface that allows you to get access to raw information. It’s a filter and a platform that can help you get the most out of your data.
Think carefully before you make the decision, and keep auditing that decision as you use the platform in your daily work, because something better may be on the way, or already available.
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed in https://www.datasciencecentral.com/profiles/blogs/your-data-is-sound-but-how-s-your-dashboard-5-aspects-to-consider