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How can you ensure that all stakeholders can access your data analysis?

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Data analysis is a crucial part of operations research (OR), which aims to improve decision making and optimize performance in complex systems. However, data analysis is not only a technical task, but also a social and ethical one. You need to ensure that all stakeholders, such as clients, managers, colleagues, and end-users, can access your data analysis in a meaningful and responsible way. In this article, you will learn how to do that by following six steps.

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Yusuf Dunmoye

BI & Data Analytics Specialist | MS-EXCEL, Power BI, SQL | Boosting Revenue Through Data-Driven Strategies
Dauda Foday Kamara

Clinical Systems Associate at FHI Clinical Inc |Fintech | Business & Data Analytics| Clinical Research

1 Define your audience

Before you start your data analysis, you need to identify who are your stakeholders and what are their needs and expectations. Different stakeholders may have different levels of interest, expertise, and authority in your data analysis. You need to tailor your data analysis to suit your audience and communicate with them effectively. For example, you may need to provide more details and explanations for technical colleagues than for non-technical managers.

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Yusuf Dunmoye

BI & Data Analytics Specialist | MS-EXCEL, Power BI, SQL | Boosting Revenue Through Data-Driven Strategies
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? Understanding stakeholders is crucial for effective communication in data analysis. ? Tailor your communication based on stakeholders’ interest, expertise, and authority. ? Provide detailed methodologies and results for technical colleagues. ? Offer concise summaries with actionable insights for non-technical managers. ? Strive for a balanced approach to make your analysis accessible to diverse audiences. ? Regularly seek feedback from stakeholders to refine your communication strategy. Additionally: ? Consider the business context to align your analysis with organizational goals. ? Emphasize how your findings impact key performance indicators and contribute to overall business success.

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Yusuf Dunmoye

BI & Data Analytics Specialist | MS-EXCEL, Power BI, SQL | Boosting Revenue Through Data-Driven Strategies
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? Understanding stakeholders is crucial for effective communication in data analysis. ? Tailor your communication based on stakeholders’ interest, expertise, and authority. ? Provide detailed methodologies and results for technical colleagues. ? Offer concise summaries with actionable insights for non-technical managers. ? Strive for a balanced approach to make your analysis accessible to diverse audiences. ? Regularly seek feedback from stakeholders to refine your communication strategy. Additionally: ? Consider the business context to align your analysis with organizational goals. ? Emphasize how your findings impact key performance indicators and contribute to overall business success.

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2 Choose your tools

The tools you use for your data analysis can affect how accessible your data analysis is for your stakeholders. You need to choose tools that are compatible, reliable, and secure for your data analysis. For example, you may use software such as Excel, R, Python, or Tableau for data processing, analysis, and visualization. You need to make sure that your stakeholders can access and use these tools, or provide alternative formats such as PDF or HTML.

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3 Document your process

Documentation is essential for making your data analysis transparent, reproducible, and verifiable. You need to document your data sources, methods, assumptions, limitations, and results in a clear and consistent way. You need to provide references, citations, and acknowledgments for any external sources or collaborators. You also need to use appropriate naming conventions, comments, and annotations for your data files, code, and charts.

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4 Validate your results

Validation is the process of checking the accuracy, quality, and relevance of your data analysis results. You need to validate your results before you share them with your stakeholders, and be prepared to answer any questions or feedback they may have. You can use various techniques such as cross-validation, sensitivity analysis, error analysis, or peer review to validate your results. You also need to report any errors, uncertainties, or biases that may affect your results.

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Pratik Kate ??????

AdTech @ King (Candy Crush) | Ex-EY
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Validation Techniques: — Cross-Validation: Tests model on diverse data subsets. — Sensitivity Analysis: Assesses variable impact for robustness. — Error Analysis: Identifies potential pitfalls, reinforcing reliability. — Peer Review: Encourages constructive critique for refinement.

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5 Visualize your data

Visualization is the process of presenting your data analysis results in a graphical or interactive way. Visualization can help you and your stakeholders to understand, explore, and communicate your data analysis results more effectively. You need to use appropriate types of charts, colors, scales, and labels for your data visualization. You also need to avoid misleading or confusing visualizations that may distort or misrepresent your data analysis results.

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6 Share your data

Sharing is the final step of making your data analysis accessible to your stakeholders. You need to share your data analysis in a timely, ethical, and respectful way. You need to respect the privacy, confidentiality, and ownership of your data and your stakeholders. You also need to comply with any legal, contractual, or professional obligations or standards that apply to your data analysis. You can use various channels such as reports, presentations, dashboards, or web pages to share your data analysis.

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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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Dauda Foday Kamara

Clinical Systems Associate at FHI Clinical Inc |Fintech | Business & Data Analytics| Clinical Research
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In addition to the above, one thing that I found to be effective is, organizing a workshop or training session with your audience,as per their roles. During the session, it is important to let your stakeholders know the when to expect the data and how to identify incomplete data and the like ( this process is usually effect with automated data. eg: sales performance dashboard).

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How can you ensure that all stakeholders can access your data analysis?

1

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3

4

5

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7

1 Define your audience

2 Choose your tools

3 Document your process

4 Validate your results

5 Visualize your data

6 Share your data

7 Here’s what else to consider

Operations Research

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How can you ensure that all stakeholders can access your data analysis?

1

2

3

4

5

6

7

1 Define your audience

2 Choose your tools

3 Document your process

4 Validate your results

5 Visualize your data

6 Share your data

7 Here’s what else to consider

Operations Research

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