Data analytics

Why Businesses Need a Data Analytics Dashboard

Factored Data Experts
Factored Data Experts

According to Salesforce, 41% of organizations’ current systems can’t make sense of large volumes of data from different sources. Thankfully, a data analytics dashboard can help.

A dashboard is a useful tool for both business intelligence and data analytics. But what exactly is it? How does it work? What can it provide your organization, and how can you create one?

Let’s take a look.

What is a Data Analytics Dashboard?

A data analytics dashboard is a tool used by companies to visually represent their business data, indicators, and other metrics. It provides an easily-understandable picture of what is happening in the business and where changes can or need to be made.

After collecting sets of data, the dashboard displays it in a single view. This allows users to quickly and easily understand metrics, while also providing them with the flexibility to change the graphics, presentation, and structure of the data.

This means companies can customize their data analytics dashboard to include performance indicators, KPIs, OKRs, and the like with visuals, text, charts, tables, and figures. This makes it easier for the C-Suite and other decision makers to more easily understand specific business objectives, monitor activity, and keep track of progress toward goals. 

Since a dashboard can be used to study and analyze different parts of a business, organizations may have multiple dashboards for specific projects, departments, and customer segments.

Creating a Data Analytics Dashboard

When it comes to creating a dashboard, you’ll want to enlist the help of an Analytics Engineer. An Analytics Engineer uses the systems created by a data engineer to design and implement the transformation steps of an extract, load, and transform (ELT) pipeline to transform the correct data into the proper format for data consumption.

After all, it’s not enough to simply own data these days; in order for it to be useful to your organization, it needs to be cleaned, organized, and presented in a digestible way for all business stakeholders. An Analytics Engineer can help you do just that by creating machine learning models, delivering insightful business analysis, and creating dashboards to help you make those key decisions. 

When creating such a dashboard, it’s important that you and your Analytics Engineer keep a few things in mind.

Know the Business Requirements

First understand the business requirements: Know what kind of decisions will be made based on the data behind the dashboard. 

It’s important to be curious about why the business needs a dashboard instead of simply creating the simple bar charts they asked you for. Furthermore, understand what it is that they want to assess when looking at the dashboard, so you can provide the most insightful and intuitive visualizations for the specific use case.

Understand Your Data

Make sure you have a deep understanding of your data, and align the defined metrics with your stakeholders. Ask questions like: What are the steps of the funnel we want to analyze? Do we want to calculate ROI, CLV, CAC? You should be able to answer many stakeholders’ questions as soon as they start getting insights from your new and intuitive dashboard.

Think About More than Just Graphs and Tables

Remember, a dashboard is a visual representation. Don’t just think about the right graphs and tables—titles, subtitles, axis labels, descriptions, and layout segmentation are also important to explain the main focus of the visualization.
Be clear and consistent. For example, pay attention to the layout, group related metrics, choose clear labels that are short and self explanatory, and leverage color to highlight relevant information (e.g. when there’s a significant cost increase). Seeing as 30% of users say they have trouble identifying useful data, this will allow users to more easily parcel out the most important information.

Keep it Simple

Keep it simple. A dashboard should provide a straightforward data analytics infrastructure; it shouldn’t require programming or advanced data science training to be able to gain access, understand data, and draw clear insights. Furthermore, a cluttered dashboard with too much information will increase the cognitive load for users—which is the opposite of what you want.

A simple dashboard, on the other hand, means any user looking at the dashboard for the first time can quickly understand what is being conveyed. A minimalist dashboard that displays only the most relevant KPIs will provide users with the proper tools and knowledge to make data-driven business decisions at a glance.

Make it Customizable

Developing customized dashboards for users’ particular needs will allow different decision makers, departments, and other team members to get the most out of the data they need, when they need it. This won’t only help them—and your organization as a whole—develop a clear business strategy, but will also enable you to differentiate yourself from the competition in more ways than one.

Ensure It’s Secure

Establish an isolated data environment for each user to ensure that no sensitive information is accessible more widely than it needs to be. This means only those who truly need access to that data will have it, providing users with the peace of mind that their owned data is securely stored.

Iterate

Make sure you regularly pause your efforts to iterate your dashboard. Additionally, iterating your data curation will not only improve your dashboards, but your machine learning models and analyses as well—meaning your business will be much better off.

What’s more, no dashboard is right the first time. Other people’s opinions (especially those of the main users of the dashboard) can provide you with new, fresh perspectives on how to improve layout and functionality.

The Takeaway

Your dashboard has a specific business purpose, so always remember what questions you’re trying to answer: Do you know your audience? Do people understand the dashboard’s intent? Are you including what’s important? 

Ultimately, your dashboard(s) should make the complex simple, connect the data to its business context, correctly represent the data visually, and be customizable depending on user needs.

At the end of the day, a fully comprehensive data analytics dashboard is advantageous for all types of business; it can make a huge difference not only when it comes to company growth, but on your organization’s bottom line as well.

To start building a fully comprehensive data analytics dashboard today, book a call with us and we’ll help you get started?

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