More and more, companies are understanding the importance of data and advanced analytics to their business. From improving operational efficiency to making informed decisions based on up-to-the minute information, there are many practical benefits of leveraging big data. Data scientists were said to have the “sexiest job of the 21st Century” back in 2012, due to their seemingly-magic ability to manage data and provide key insights. Data volume and the demand for workers with data skills has not slowed down since. In fact, IBM predicted that there would be more than 700,000 job openings for these types of positions by 2020.
Enthusiasm for data digestion has reached the point where everyone in an organization needs to be comfortable with data, not just the data scientists. This is especially true for startups and small businesses, who may not have the funds to add a full-time data scientist to their team. This can seem intimidating due to the statistical and analytical nature of the exercise, but truthfully it’s easier than one may think to interpret and manage data.
Data visualization software allows anyone (not just data scientists) to make sense of overwhelming amounts of data. Being able to visualize data and tell stories with it is the key to turning data into information that helps make smarter, more informed decisions. When it comes to actually building dashboards and data visualizations, there are really just three key areas that build a foundation of knowledge.
Anyone can build a dashboard (if they know these three things…)
For some people, simply seeing the word “data” can stir up not-so-fond memories of complex math and science classes from back when they were in school. While it may seem daunting for some non-STEM employees at first, it’s worth taking the time to gain confidence working with statistics. Everyone in an organization can increase their impact by being able to communicate effectively with data.
So, where should you start?
If your goal is to learn how to build a dashboard in order to visualize data, you will need to know:
1. How your company manages data
Is the company’s data stored in a database, Excel file, on the Cloud, or somewhere else? Do you have access to that data? It’s important to know how your company is managing their data, where to find it, and how to access it before embarking on your dashboard project.
2. Who is in charge of it
Reach out to the specialists in your organization, whether they are in the IT department or part of a data science division. They can help answer any questions you may have and provide you with information about processes that are already in place. Getting their advice and insight could save you time as you move forward.
3. Which metrics are most important
Ask yourself: what is the purpose of this dashboard and who will be viewing it? It’s best to pull data that directly aligns with the goals of the department this dashboard is intended for, so that you can provide actionable insights that provide value.
Read next: What is Data Visualization?
It is the dashboard builder’s duty to bring their data story to life, both visually and contextually. Knowing what data to use is only the first part, you also need to bring it to life through design.
1. Know which visual options are available
There will be some limitations for what colors, charts, and graphs are available when working in a dashboard software. Getting your bearings on what options you do and don’t have is an important first step when starting to make design choices
2. Develop your color palette
Try to stick to a maximum of six natural colors (try keep the neon to a minimum). Remember that building a color palette goes beyond aesthetic preference – it’s about communicating the right story through your data. If you are still feeling lost, there are a variety of free online tools to help you choose the right color palette.
3. Use your company’s branding
Creating a color palette from scratch can be overwhelming and time consuming, especially if you are not trained in design. By using your corporate primary and secondary colors, you can improve your dashboard branding and play into your company’s existing color scheme. This can increase user adoption, as it amplifies the connection with the data and your organization.
4. Inform, don’t overwhelm
There’s an art to knowing just the right amount of data and detail to have in a chart. Dashboards should provide an at-a-glance snapshot of performance. Dashboards are also dynamic, so you can always include drilldowns to provide further detail without displaying all the data at once.
Above all, a dashboard needs to provide value to the business. In order to build an effective dashboard, it needs to share useful and actionable information at a glance. There are so many different ways to build a dashboard depending on the audience and intention behind it. Whether or not a dashboard is successful ultimately comes down to selecting proper, useful KPIs through these steps:
1. Identify your business’s goals
Communicate with managers and executives to find out what the core objectives of the company are. Chances are, they have a number of objectives for each department and need a better way to communicate them.
2. Figure out how to measure it
After you’ve identified the objectives, determine which measures make up the metrics you need to be tracking to monitor the progress towards your goals.
3. Refine your list
Now that you have a complete list of all your business objectives and the associated metrics, you need to narrow it down and focus on a single dashboard worth of information. Choose KPIs that display your progress toward achieving your goals. Start small and don’t be afraid to be selective.
Once you understand your data, determine a color palette, and track the right KPIs, you’ll find that dashboards can be a powerful business tool. Think you’re ready to build a dashboard? Start your free trial of iDashboards today.
Get the Guide Fundamental Design Principles for Dashboards
Even if you’re not the artistic type, this guide will have you thinking like a graphic designer and making informed choices that support your data narrative.