What is data visualization?

The legacy of Nightingale reminds us that data visualization isn't just about pretty charts. Data visualization is the art and science of transforming raw data into actionable insights. Visual representations are about uncovering the hidden stories within your data. They make complex information accessible to everyone, not only data scientists—and change how your business operates. 

A visualization is a visual representation of data, such as a grid, line chart, or heat map. Visualizations offer various ways to display and interact with data within a dashboard, allowing you to:

• Explore relationships between data elements.

• Create visually striking graphs that summarize key business indicators.

• Combine data from multiple datasets into a single visualization.

• Include multiple visualizations within a single dashboard panel or chapter.

Let's explore the different types of data visualizations.

Types of data visualizations

A wide array of data visualizations exist, each suited to identify patterns and serve different purposes. Some common types include:

Charts

• Bar charts: Ideal for comparisons, distributions, and trends.

• Pie charts: Visualize the distribution of components within a whole.

• Line charts: Depict trends or changes over a specified time period.

• Scatter plots: Reveal relationships between variables.

• Area charts: Show changes in values over time or comparisons between groups.

Graphs

• Network graphs: Visualize connections between entities.

• Tree maps: Illustrate hierarchical data.

• Heat maps: Show intensity or distribution across a matrix.

Maps

• Geographic maps: Display location-based data.

• Choropleth maps: Show data variations across regions using color-coding.

Dashboards

• Interactive dashboards: Combine multiple visualizations for a holistic view.

Other visualizations

• Grids: Display data in a tabular format.

• Box plots: Show data distribution and identify outliers.

• Waterfall charts: Display the cumulative effect of sequentially introduced positive or negative values.

• Histograms: Present the distribution of a dataset.

• Time series: Display data points at successive intervals of time.

Understanding these different types of visualization techniques is crucial for making your data easy to understand.

Defining your purpose

Before diving into your data, it's crucial to define the purpose and type of your visualization. Answering two questions will help you determine the best approach:

• Is the information conceptual or data-driven? Does your data consist of abstract concepts or measurable quantities?

• Is your objective to declare something or to start exploring? Are you communicating known information or trying to uncover new insights?

These questions show four types of visual communication:

• Illustrate concepts: Transform complex ideas into clear visuals using diagrams, charts, or metaphors. A visual representation of a company's hierarchy, for example, is often more intuitive than a written explanation.

• Spark ideas: Unleash creativity and explore new concepts through sketching, doodling, and diagramming during brainstorming sessions.

• Uncover insights: Reveal patterns and relationships hidden within your data through visual exploration. This process can encompass both targeted analysis and exploratory analysis.

• Communicate clearly: Convey a single message effectively in presentations using simple and impactful charts and graphs.

Abstract vs. measurable data visualization

Data analysts distinguish between abstract concepts and measurable quantities. Understanding both can help present data in a way that enables informed decision-making.

Abstract concept: employee satisfaction

• Visualization: A word cloud generated from employee feedback comments.

• Details: Employee satisfaction is a subjective measure that can be difficult to quantify directly. You can create a word cloud from survey responses, key themes and sentiments (e.g., "happy," "challenged," "valued," "stressed"). Using data visualization tools can provide a general sense of the overall mood and satisfaction levels within the organization.

Measurable quantity: employee productivity

• Visualization: A bar chart showing the number of tasks completed by each employee per month.

• Details: Employee productivity is a quantifiable measure that you can track and compare over time. Bar charts can display the number of tasks each employee completes monthly. This allows for a straightforward comparison of productivity levels across the team.

Benefits and challenges of data visualization

Data visualization tools translate complex data science processes into actionable insights. Yet, they also present unique challenges that businesses must navigate to effectively harness their full potential.

Benefits:

• Improved decision-making: Visualizations equip you with the clarity needed to make faster, data-driven decisions.

• Enhanced communication & collaboration: Easily share insights across teams and foster a data-driven culture within your organization.

• Increased efficiency & productivity: Quickly identify trends and patterns, enabling you to streamline processes and optimize operations. This can lead to significant cost savings and improved performance.

Challenges:

• Choosing the right visualization: Selecting the most appropriate chart or graph for your data can be tricky. Careful consideration of your goals and data types is essential.

• Avoiding misleading visualizations: It's crucial to ensure that visualizations accurately represent the data without distortion or bias. Misleading visualizations can lead to incorrect conclusions and poor decisions.

• Data accuracy & integrity: The effectiveness of your data visualization relies on the quality and reliability of your underlying data. Make sure your data is clean and accurate before you start creating visualizations.

But the power of data visualization goes beyond just addressing these challenges. Let's explore how it can revolutionize different areas of your business.

The role of data visualization in business

Data visualization is a game-changer across various business functions:

• Strategic decision-making: Executives use visualizations to assess market trends, evaluate risks, and spot new opportunities. This can help them make informed decisions that drive growth and ROI.

• Operational efficiency: Identify process bottlenecks, track performance metrics, and monitor resource utilization with visual insights. This can help you optimize your operations and improve efficiency.

• Customer insights: Analyze customer data through visualizations to gain a deeper understanding of preferences, behaviors, and needs. This can help you personalize your marketing and sales efforts, leading to increased customer satisfaction and loyalty.

However, as your business grows, so does the volume of data you need to manage. This is where advanced BI tools become crucial.

Handling Big Data with visualization

As businesses collect more and more data, the challenge of visualizing large datasets becomes increasingly important. Traditional tools may require data sampling or summarization, leading to a loss of valuable insights.

Organizations can leverage data visualization and big data, e.g. by analyzing customer behavior patterns from millions of transactions. This allows for targeted marketing strategies and improved customer experiences.

MicroStrategy: empowering data-driven decisions

The MicroStrategy ONE platform offers a wide range of data visualization capabilities, including:

• Vast library of visualizations: Use pre-built visualizations or design your own. This gives you the flexibility to create visualizations that perfectly match your needs.

• Interactive dashboards: Build dynamic dashboards that empower users to explore data independently. This puts the power of data in the hands of your users.

• AI-powered insights: Leverage the AI capabilities of MicroStrategy to uncover hidden patterns and gain a competitive edge. This can help you make smarter decisions and stay ahead of the competition.

• Embedded Analytics: Integrate visualizations directly into your existing applications and workflows. This makes it easy to access and use your data, no matter where you are.

Ready to see how simple it is to transform your data into actionable insights?

Creating your first dashboard with MicroStrategy

MicroStrategy makes it easy to create your first dashboard and start visualizing your data. Here's a quick overview of the process:

1. Select a dataset: Choose from a flat file, import from a database or service, or leverage MicroStrategy's AI capabilities to automatically suggest relevant datasets.

2. Create your first visualization: Use AI to generate a visualization based on your query or select from MicroStrategy's library of grids, graphs, and KPIs.

3. Customize your dashboard: Add titles, change colors and text, and arrange visualizations to match your business's branding. MicroStrategy offers a wide range of customization options to make your dashboard unique.

4. Save & share: Save your dashboard and share it with stakeholders to drive data-driven decision-making across your organization.

With the intuitive tools and AI-powered capabilities from MicroStrategy, you can go from data to insights in minutes—not hours.

More than graphs

Data visualization is more than just pretty pictures. It's a strategic asset that can empower your business to make smarter decisions, optimize operations, and drive innovation. With the right data visualization tools and techniques, like those offered by MicroStrategy, you can unlock the full potential of your data and propel your business forward.

Ready to transform your business with data-driven insights? Explore MicroStrategy today and discover how you can turn your data into a wellspring of growth, innovation, and success