Data Visualization Best Practices for Enterprises

Data Visualization Best Practices

“Clutter and confusion are not attributes of data — they are shortcomings of design.”Edward Tufte.

In 2023, data visualization has evolved beyond charts, graphs, and dashboards. However, despite the relevance and importance, it’s not easy to create compelling data visualizations and realize success with them.

IBM outlines that 2.5 quintillion bytes of data are generated every day. As data volumes increase exponentially, creating visualizations powered by abstraction and analogies that can help people comprehend numbers becomes critical.

6 Best Practices of Data Visualization in Enterprises

Data visualization enables business users to comprehend large numbers, among its many benefits, seamlessly. Enterprises across industries can leverage data visualization to democratize access to valuable insights. Here are some best practices to get data visualization right.

  1. Select Relevant Data Points:

    An effective visualization must display complex data connections without clutter. This is crucial for business users to grasp the critical insights communicated through visualization quickly.

    Data points are the building blocks of visualized data. As a best practice, choose the data points most relevant to the “story” being presented.

  2. Ensure Data Quality:

    Data quality is essential for visualization. Low-quality data can lead to inaccurate conclusions and interpretations, impacting decision-making.

    Therefore, enterprises must clean and preprocess data to eliminate errors or anomalies. Additionally, data cleansing should include normalizing data and removing any duplicate values.

    Enterprises must also use recently updated data to make informed business decisions. Otherwise, outdated data can mislead business users with inaccurate insights in an utterly dynamic market environment.

  3. Use Schema Design:

    Talking about data quality, a good database schema design is necessary for eliminating (or reducing) redundant data. Schema designing refers to the best practices used to construct a database schema.

    Enterprises can only efficiently run their database and retrieve information using schema design. Besides consuming energy and time, disorganized databases are difficult to maintain and cannot provide valuable enterprise data. Here are some of the best practices for schema designing:

    • Use the right naming conventions
    • Encrypt sensitive data, including passwords and personally identifiable information (or PII)
    • Understand every data element and its attributes for an effective schema design
  4. Automate Reporting Process:

    With data visualization, enterprises have an efficient tool to identify market trends and improve their performance. Automation can streamline this by automatically providing data from connected applications. Automating their reporting process means enterprises no longer have to spend valuable time transferring data between applications.

    Organizations can quickly share reports among stakeholders through automation – with minimum effort and time. Similarly, automation can quickly facilitate data input into visualized elements used in bars and charts.

    This way, sales reports, for instance, can provide real-time data about new sales leads, prospects, and customers.

  5. Leverage Business Intelligence (BI)—enabled Dashboards:

    Business intelligence transforms data visualization from a visual tool to an effective business analysis tool. BI technology enables users to analyze business information to improve their decision-making process.

    It can enable users to interact with visual data from different angles for their specific use cases. Here are some capabilities of a BI-enabled dashboard:

    • Connecting with the third-party system through APIs
    • Adding multiple visual elements on the BI dashboard
    • Using interactive visual elements to manipulate the presented data
    • Automating the visualization process
  6. Ensure Data Readability and Device Compatibility:

    Enterprises must ensure that visualized data is readable in any format and supported on multiple devices. For example, interactive charts must be easy to follow on desktop and mobile devices. Here are some valuable tips to ensure readable data on any device:

    • Use CSS to present consistent images on any mobile device
    • Optimize high-quality images for consistent speed and fast loading
    • Tweak background colors to highlight vital information on any device

How Ellicium Can Help Organizations with Data Visualization and BI

At Ellicium, we believe that data drive the best business decisions. Through our data-based reporting and dashboard, we empower business users to make instantaneous decisions. Here are some ways in which Ellicium is delivering effective data visualization and BI to its customers:

  • Facilitation of real-time visual analytics and reporting
  • 24/7 monitoring of digital assets
  • Innovative and customized dashboard designs
  • Customizing data views across various BI reports and visuals
  • Enabling access to critical data across sources

Here is a case study of how Ellicium implemented an enterprise-level BI solution for a leading consumer products company.

Conclusion

With the explosion of business data, enterprises are not surprised to turn to data visualization for relevant insights and information. However, to realize success with such initiatives and make informed decisions, enterprises require expertise to help them navigate the complexity of bringing accurate and intuitive visualizations to the fore. This is where a part like Ellicium Solutions becomes integral to maximizing the data visualization capabilities. Contact us to learn more.