How to Make Your Business Intelligence Work More Impactful and Enjoyable. | by Gabe A, (M.S.) | Apr, 2023

How to Make Your Business Intelligence Work More Impactful and Enjoyable. | by Gabe A, (M.S.) | Apr, 2023

Photo by Robert Bye on Unsplash

Hey there! As a business intelligence professional, I’ve learned that data visualization is a key aspect of the job.

It’s not just about presenting numbers and figures, it’s about telling a story with data.

And while this may seem like a mundane task to some, I’ve found that emphasizing the creativity and design aspects of data visualization can make my work more enjoyable and fulfilling. 📈💻💡

Let’s face it, most business professionals don’t get excited about numbers and spreadsheets.

But when data is presented in a visually compelling way, it can spark interest and even excitement.

That’s why data visualization is so important in the world of business intelligence. It helps to communicate complex data insights in a way that is easily understandable and impactful. 🚀📊

In this article, I’ll be sharing my personal experiences and insights on the importance of emphasizing data visualization in the BI field.

I’ll also provide some relatable examples and offer tips on how to improve your data visualization skills. So grab your favorite data visualization tool and let’s dive in! 🤓🎨

Why Data Visualization Matters

First things first, why does data visualization matter in business intelligence?

Well, for starters, it can help to tell a story.

As humans, we are wired to respond to stories. We remember them, we relate to them, and we are more likely to act on them. Data visualization can take a bunch of numbers and turn them into a narrative that is easy to understand and remember. 📈📚

In addition, data visualization can help to uncover trends and insights that might not be immediately apparent in a table of numbers.

A well-designed chart or graph can reveal patterns and relationships that might be missed in a spreadsheet. This can help to inform business decisions and drive results. 🤔💰

Finally, data visualization can make data more engaging and memorable. Think about it: would you rather look at a table of numbers or a colorful, interactive chart?

The latter is more likely to catch your attention and keep you engaged. And if you remember the data, you’re more likely to act on it. 🎨🤩

Tips for Improving Your Data Visualization Skills

Now that we’ve established why data visualization is so important, let’s talk about how to improve your skills in this area. Here are a few tips that have worked well for me: 💡👩‍💻📊

  • Start with the story: Before you start designing your visualization, think about what story you want to tell. What insights do you want to communicate? What do you want your audience to take away? Once you have a clear understanding of the story, you can design a visualization that supports it.
  • Keep it simple: It can be tempting to create a complicated visualization with lots of bells and whistles. But remember, the goal is to communicate information in an easy-to-understand way. Keep your visualization simple and focused. Avoid clutter and unnecessary elements.
  • Use color strategically: Color can be a powerful tool in data visualization, but it should be used strategically. Use color to highlight important data points or to distinguish between different categories. But be careful not to overuse color, as this can be distracting.
  • Get inspired: There are countless examples of great data visualizations out there. Take some time to explore and get inspired. Look for examples in your industry or in other fields that you find compelling. And don’t be afraid to experiment and try new things!

Examples of Creative Data Visualization in Business

To bring this all to life, let’s take a look at some examples of creative data visualization in the business world. These are real-world examples that showcase the power of good data visualization. 💼

Photo by path digital on Unsplash
  • Interactive Dashboards: Dashboards are a common way to present data in business intelligence, but they don’t have to be boring. With the help of data visualization tools like Tableau or Power BI, it’s possible to create interactive dashboards that allow users to explore data in real-time. For example, a sales dashboard might allow users to filter by product, region, or time period, and then see the results in a series of charts and graphs. This not only makes the data more engaging, but it also allows users to gain insights in a more efficient manner.
Photo by Victor Lu on Unsplash
  • Infographics: Infographics are a popular way to present data in a visually compelling way. They often include illustrations, icons, and other design elements to make the data more interesting and memorable. For example, a marketing team might create an infographic that showcases the results of a recent campaign, using colorful charts and graphs to highlight key metrics like click-through rates or conversion rates.
Photo by Clay Banks on Unsplash
  • Heat Maps: Heat maps are a type of data visualization that use color to represent data values. They are particularly useful for showing geographic data or data that is tied to a specific location.

For example, a real estate company might create a heat map that shows the average home prices in different neighborhoods. The map would use color to represent different price ranges, with darker colors indicating higher prices.

  • This type of visualization can quickly communicate insights and trends that might not be immediately apparent in a table of numbers.
Photo by Carlos Muza on Unsplash

Interactive Reports: Reports don’t have to be boring either. With the help of data visualization tools, it’s possible to create interactive reports that allow users to explore data in new ways. For example, a financial report might include a series of interactive charts and graphs that allow users to drill down into specific data points or filter by different time periods. This not only makes the report more engaging, but it also allows users to gain insights more quickly and efficiently.

Incorporating Data Visualization in Your Work

So, how can you start incorporating data visualization into your work as a business intelligence professional? Here are a few ideas to get you started: 💡👩‍💻📊

  • Attend Data Visualization Workshops: Attend workshops or courses that will teach you the basics of data visualization. You’ll learn how to create engaging visuals and how to tell stories with data. Many of these courses can be taken online, which means you can fit them into your schedule.
  • Experiment with Different Tools: There are many data visualization tools available, and each has its own strengths and weaknesses. Try out different tools and see which ones work best for your needs. Some popular tools include Tableau, Power BI, and Google Data Studio.
  • Collaborate with Designers: If you work in a large organization, there may be designers on staff who can help you with data visualization. Collaborate with them to create visuals that are both beautiful and informative.
  • Join Data Visualization Communities: Join online communities or attend events where data visualization is discussed. You’ll be able to network with other professionals and learn from their experiences.

Emphasizing the creativity and design aspects of data visualization can make your work as a business intelligence professional more enjoyable and fulfilling.

By telling stories with data and presenting it in an engaging way, you can communicate insights that might be missed in a table of numbers. Remember to keep it simple, use color strategically, and get inspired by examples in your industry or in other fields. With these tips and tricks, you’ll be on your way to becoming a data visualization expert. 🚀📊💻

I hope this article has been helpful to you. Thank you for taking the time to read it.

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Who am I? I’m Gabe A, a seasoned data visualization architect and writer with over a decade of experience in SQL, data analysis, and AI. Passionate about topics like Python, finance, and data visualization, I’ve become a trusted voice in the data science industry.

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