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What are the best data visualization tools for diagnosing performance issues?

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Data visualization is a powerful way to communicate complex information and identify patterns, trends, and outliers in performance data. However, not all data visualization tools are created equal. Some are more suitable for certain types of data, audiences, and purposes than others. In this article, you will learn about some of the best data visualization tools for diagnosing performance issues, and how to choose the right one for your situation.

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Ameenuddin Khaja, PMP?

Regulatory Operations | Global Privacy | Shared Services | Risk & Compliance Specialist | Business Transformation |…

1 Why data visualization matters

Data visualization is the process of transforming data into graphical or pictorial forms, such as charts, graphs, maps, or dashboards. This can be incredibly useful for simplifying and summarizing large amounts of data, highlighting key insights and findings, comparing and contrasting different variables or groups, detecting anomalies and outliers, identifying correlations and causations, and communicating and persuading stakeholders. Moreover, data visualization is especially helpful for diagnosing performance issues – it can help you to pinpoint the root causes, the magnitude, and the impact of the problems, as well as propose effective solutions.

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Gumboh N.

ETL Pipelines | Data Engineer | Customer Data Platforms (CDP) | Data Modeling (dbt) | Python, AWS/GCP | Advanced SQL
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with emphasis on a self-serve approach, I'm tempted to narrow down the importance of data visualization to encouraging data democratization which then fosters a sense of ownership across teams which then drives faster problem resolution and above all, stimulates data-informed [not data-driven] decision-making mindset. agility becomes an actual thing.

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2 Types of data visualization tools

Data visualization tools come in a wide variety, from simple and free to sophisticated and expensive, and from general to specific. Spreadsheet software like Excel or Google Sheets allows you to create basic charts and graphs. Presentation software like PowerPoint or Keynote can display and animate your charts and graphs. Online platforms such as Tableau or Power BI enable you to create interactive dashboards and reports from various data sources. Programming languages like Python or R let you craft customized, advanced visualizations with code and libraries. Specialized tools Gephi or Kibana can create specific types of visualizations, such as network graphs or log analysis.

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Ameenuddin Khaja, PMP?

Regulatory Operations | Global Privacy | Shared Services | Risk & Compliance Specialist | Business Transformation | Effective Communicator
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We must take into account various aspects when selecting a data visualisation tool, including usability, scalability, integration potential, and performance analysis requirements. A combination of tools may also be used by certain organisations to obtain a thorough understanding of their systems.

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3 How to choose the best data visualization tool

When selecting the best data visualization tool for diagnosing performance issues, there is no one-size-fits-all solution. Factors such as the type and size of your data, the purpose and audience of your visualization, the level of interactivity and complexity you need, the time and budget you have, and your skills and preferences should all be taken into account. To determine which tool is best for you, consider what message or question you want to answer with your visualization; who you are presenting it to; how you want to display your data; how much data you have and how often it changes; how much time and money you can spend on creating and maintaining your visualization; and how comfortable you are with using different tools and techniques. By answering these questions, you can narrow down your options and select the most appropriate data visualization tool for your performance diagnosis.

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4 Best practices for data visualization

Before creating data visualizations to diagnose performance issues, you should define your goal and audience. Select the right type of chart or graph for your data and message, and use colors, shapes, sizes, and labels to highlight important information. Additionally, avoid clutter, distortion, and misleading representations of your data. Provide context, explanations, and recommendations for your visualization as well as test and refine it to ensure clarity, accuracy, and relevance. Following these best practices will ensure that your data visualization delivers the intended message and value to your audience.

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5 Examples of data visualization tools

To illustrate some of the data visualization tools and best practices, here are examples of how to use different tools to diagnose performance issues in different scenarios. For instance, you can use a spreadsheet software, such as Excel or Google Sheets, to compare the sales performance of different regions and products in your company. This can be done with a pivot table and a clustered column chart that has colors to differentiate the regions and products, and labels to show the values and percentages. Alternatively, an online platform, such as Tableau or Power BI, can be used to analyze customer satisfaction and retention rates of your service with a gauge chart, a line chart, and a scatter plot. Lastly, a specialized tool like Gephi or Kibana can be used to explore relationships between key stakeholders in your project with a network graph. There are many more tools and techniques available for you to explore and experiment with based on your needs and goals.

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Brinda Sengupta

HR Leader/Change Catalyst/DEI Champion/Talent Enabler
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One can use a spreadsheet software, such as Excel or Google Sheets, to compare the sales performance of different regions and products in your company. This can be done with a pivot table and a clustered column chart that has colors to differentiate the regions and products, and labels to show the values and percentages. Alternatively, an online platform, such as Tableau or Power BI, can be used to analyze customer satisfaction and retention rates of your service with a gauge chart, a line chart, and a scatter plot. Lastly, a specialized tool like Gephi or Kibana can be used to explore relationships between key stakeholders in your project with a network graph.

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6 Data visualization resources

If you want to learn more about data visualization tools and best practices, there are many useful resources available. For example, Kieran Healy’s book Data Visualization: A Practical Introduction teaches readers how to create and interpret data visualizations using R. Cole Nussbaumer Knaflic’s course Data Visualization for Storytellers focuses on how to communicate effectively with data using charts and graphs. Additionally, Coursera’s Data Visualization: Charting Your Course course teaches how to design and create interactive dashboards and reports using Tableau. IBM’s Data Visualization with Python course covers how to create and customize data visualizations using Python and libraries such as Matplotlib, Seaborn, and Folium. Lastly, the website Data Visualization Catalogue provides a comprehensive list of data visualization types and examples. Knowing how to use data visualization can be a valuable skill for performance management, as it can help you understand, diagnose, and communicate performance issues. With the right tool and best practices, you can create compelling visualizations that can enhance your performance analysis and diagnosis.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the best data visualization tools for diagnosing performance issues?

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4

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1 Why data visualization matters

2 Types of data visualization tools

3 How to choose the best data visualization tool

4 Best practices for data visualization

5 Examples of data visualization tools

6 Data visualization resources

7 Here’s what else to consider

Performance Management

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What are the best data visualization tools for diagnosing performance issues?

1

2

3

4

5

6

7

1 Why data visualization matters

2 Types of data visualization tools

3 How to choose the best data visualization tool

4 Best practices for data visualization

5 Examples of data visualization tools

6 Data visualization resources

7 Here’s what else to consider

Performance Management

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