5 Benefits of Data Visualization: Why Integrating a Data Catalog is Crucial

By Alanna Gerton

Published on May 4, 2023

5 Benefits of Data Visualization: Why a Data Catalog is Crucial

Are you an aspiring data scientist, or just want to understand the benefits of integrating data catalogs with visualization tools?

In today’s ever-growing world of data, having an easy way to gain insights quickly is essential. By combining the power of two solutions — data catalogs and data visualization tools — you can get a deeper understanding of your information landscape and create meaningful insights faster. This will increase productivity and save you time and expenses.

With these two types of solutions working together, accessing information becomes much more accessible while still being able to maintain accuracy and structure. Plus, this integration offers impressive performance when building real-time dashboards and visualizations that turn raw datasets into beautiful stories for viewers.

Keep reading to learn more about the benefits of integrating data catalogs with data visualization tools!

Data Catalog Definition

A data catalog is a collection of organized metadata that governs the workflow and processes for data scientists. It helps them effectively capture, store, manage, and share data assets.

Data catalogs are often created with special tools and software to ensure the records maintained in the system’s accuracy, consistency, and completeness. The data catalog serves as a single source of truth for information about any organization’s data, providing quick access to various types of information such as its format, location, history, usage, and dependencies.

What are data visualization tools?

Data visualization tools are used to represent data in a visually attractive way that can make it easier to understand. These tools enable users to assess different types of information at a glance, aiding in decision-making and revealing insights that may have been hidden before.

Data visualization tools come in many forms, from simple graph-makers like bar and line charts, to much more complex chart-makers with various features and designs. They help data analysts present large amounts of data quickly and effectively, making the most important aspects stand out while clarifying the critical relationships between variables. Data visualization tools can make automatic KPI reporting for your business a whole lot easier!

5 Benefits of integrating data catalogs with data visualization tools

Data Governance infographic showcasing the benefits of data visualization with the integration of data catalogs.

Integrating data catalogs with data visualization tools can bring incredible benefits. Combining the strengths of both tools helps create an efficient and effective system for managing and analyzing data. Here are some of the key advantages of this integration:

1. Improved data discovery and exploration

Data catalogs provide a comprehensive inventory of an organization’s data assets, facilitating the search for relevant data sets that can be used for analysis. Integrating data catalogs with data visualization tools allows users to uncover insights by accessing and analyzing necessary data quickly. This helps decision-makers identify trends and patterns in the underlying data which would have otherwise been hidden from view. Furthermore, combining these two systems reduces the time spent searching for information, as it is all organized in one place and improves collaboration between stakeholders who now have access to reliable and consistent information.

2. Enhanced data quality

Data catalogs provide a robust way of tracking data assets, helping to ensure that they are accurate, complete, and up-to-date. Integrating data catalogs with data visualization tools allows organizations to reduce errors caused by outdated or incorrect information and have more confidence in their data. This leads to more precise analysis and improved decision-making, as users can trust that the information they are analyzing is correct.

3. Improved collaboration and communication among teams

By connecting data catalogs with data visualization tools, users can share information and work together on projects in real time, regardless of geographic location. This increased collaboration leads to faster decision-making and streamlined processes that help teams work more efficiently and productively.

4. Automated processes for faster insights generation

By simplifying data discovery and exploration, users can quickly find the relevant datasets they need, allowing them to spend more time analyzing and visualizing data. This reduces the effort it takes to uncover insights, making users more productive in their work.

5. Improved decision-making and data-driven insights

By giving organizations easier access to data, they can explore and analyze it more quickly to make better-informed decisions based on evidence-based insights. This can give them a competitive advantage and lead to more remarkable growth and innovation.

Examples of integrating data catalogs with data visualization tools

Integrating data catalogs with data visualization tools — ensuring you understand and trust the data behind those visualizations — can have a variety of uses:

  • For example, it can enable organizations to quickly examine the relationships between different data pieces and understand patterns across large datasets. At the gaming giant Riot Games, Tableau reports leverage data that users know is trusted, thanks to Alation Data Catalog’s lineage features.

  • Additionally, it can be used to create interactive visualizations that illustrate complex trends and make them easier to understand. To empower self-service at scale for even users who aren’t data experts, GoDaddy’s Enterprise Data team adopted Alation’s Data Catalog alongside Tableau, which inventories data sources and provides usage-based business context.

  • Finally, it can help organizations monitor performance and identify opportunities for improvement on an ongoing basis. For Riot Games engineers, this also means having time freed for improvement because Alation reduces the number of direct inquiries to the engineering team from analysts, who have access to metadata at their fingertips.

5 Best practices for integrating data catalogs with data visualization tools

Integrating data catalogs with data visualization tools is a great way to make sense of data and gain valuable insights. To ensure successful implementation, organizations should consider the following best practices:

1. Research and select the right tools for your organization.

The chosen predictive analytics tools should be able to handle large datasets easily, provide a range of features such as interactive visualizations, and be compatible with existing systems.

2. Establish clear objectives for integrating data catalogs with data visualization tools.

This will help ensure that the chosen solution meets organizational needs and provides maximum value to the business.

3. Implement an integrated solution that is efficient, secure, and easy to use.

It should have simple yet robust functionality so technical and non-technical users can use it.

4. Monitor progress regularly.

Regularly track progress to identify any issues or areas for improvement as they arise.

5. Empower employees with online upskilling courses.

Upskill employees through online courses on data management and data visualization tools to ensure successful implementation and effective use of the integrated tools.

Challenges of integrating data catalogs with data visualization tools

Integrating data catalogs with data visualization tools can provide organizations with tremendous value, but it does come with particular challenges that must be addressed. Some of the most common challenges include data security and privacy concerns, compatibility issues between different systems and tools, and difficulty interpreting visualizations.

To address these issues, organizations should ensure that all security protocols and the right data governance are in place, regularly test compatibility across multiple platforms and tools, and carefully review any generated visualizations to ensure accuracy.

Additionally, leveraging best practices as described above will ensure the successful implementation of the chosen solution.

Conclusion

Data catalogs and data visualization tools are invaluable assets for organizations of all types, particularly those with large amounts of data to manage. They enable users to not only quickly understand how their data is organized but also make valuable insights from the visualized information.

For example, executives can use visualizations to inform strategic decisions, while marketing teams can discover trends and opportunities that open up new realms of possibility. Together, these two technologies are far more potent than when used separately and, when implemented correctly, can help organizations reach their potential.

We encourage everyone to explore the great benefits of integrating data catalogs with data visualization tools and how it can help businesses gain greater access to critical insights that drive strategy. But don’t just take our word for it — view Alation’s webinar on non-invasive Data governance at Riot Games and see for yourself how this approach can revolutionize your analysis efforts. Watch it now and take the first step toward a more efficient and effective data governance strategy!


Author Bio

Alanna Gerton is the founder of Lana and alannamarina. She is passionately committed to empowering individuals across diverse fields by utilizing trendy technology and fostering personal growth, leaving an indelible mark on the world. Free feel to reach out by email: lana@lanagerton.com

    Contents
  • Data Catalog Definition
  • What are data visualization tools?
  • 5 Benefits of integrating data catalogs with data visualization tools
  • Examples of integrating data catalogs with data visualization tools
  • 5 Best practices for integrating data catalogs with data visualization tools
  • Challenges of integrating data catalogs with data visualization tools
  • Conclusion
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