Data Visualization Provides A Mechanism That Takes To Data And Present ✓ Solved

Data visualization provides a mechanism that takes to data and presents it to the audience in a manner that is some times easier to comprehend than just a page of numbers. With all of the third-party tools that are available, such as Tableau, which have both a free version and a for-purchase version for data visualization. Is it in the best interest of the organization to use a program like Python to produce its own graph, charts, and plots or use a third=party tool to produce the visual information? Your initial response should be a minimum of two paragraphs and should be between 200 and 250 words. The font is Times New Roman, font size should be 12, and the paragraphs are single-spaced.

There should be a minimum of one reference supporting your observations. Citations are to follow APA 6.0 or 7.0, but not both.

Paper for above instructions

Data Visualization: Custom Solutions vs. Third-Party Tools

Data visualization plays an essential role in translating complex data sets into intuitive visual representations, facilitating better decision-making and communication within organizations. When considering whether to use third-party tools like Tableau or to create custom visualizations using programming languages like Python, several factors influence an organization’s choice. Third-party tools tend to be user-friendly and provide a wealth of features, including drag-and-drop capabilities for quick visualization generation. For instances where time is critical and staff may not possess extensive programming skills, these tools can offer a comprehensive solution that allows for efficient and effective reporting (Dykes, 2019). Tableau, in particular, has established itself as a leader in the field, providing robust options for creating dynamic dashboards that help organizations convey their narratives through data.
Conversely, opting to use programming languages such as Python for data visualization can yield advantages regarding flexibility and customization. Python offers libraries such as Matplotlib, Seaborn, and Plotly, which empower data analysts to create highly tailored visualizations according to specific project requirements (Hunter, 2007). This flexibility can be particularly beneficial for organizations with unique data or specialized presentation needs, allowing them to produce visualizations that are directly aligned with their objectives. Furthermore, building internal capabilities using Python may foster a culture of data literacy, encouraging employees to engage more deeply with data and understand the underlying narratives. Ultimately, the decision should consider the organization’s resources, data needs, and the skill set of its employees, balancing speed and usability with the desire for customization and adaptability.

References

Dykes, B. (2019). Effective data visualization: How to see and tell stories with data. O'Reilly Media.
Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90-95. DOI:10.1109/MCSE.2007.55
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