Data Analysis & Deliverables

Requesting a data analysis or dashboard 

When a request is received, there is a process before you receive the final deliverable:

Prepare the dataset by cleaning, structuring, and addressing missing or inconsistent data to ensure accuracy and usability.

Select the appropriate analysis method based on the research question—this could include descriptive statistics, inferential techniques, machine learning models, or qualitative thematic analysis.

Validate findings by comparing results against existing knowledge, industry standards, or through consultation with subject-matter experts.

Engage with experienced colleagues or domain experts to avoid common pitfalls such as misapplied definitions, case misclassification, or misuse of data. Collaboration supports accurate interpretation and meaningful outcomes.

Create a clear and structured deliverable—such as a report, presentation, or dashboard—that effectively communicates key insights using visuals, concise explanations, and actionable recommendations.

Review the Data Visualizations section for guidance on selecting the right chart types and applying best practices for presenting data and building impactful dashboards.

Once the request is ready:

Present findings in an accessible format.

Address follow-up questions or additional insights.

Explain the methodology and how conclusions were drawn, particularly if unexpected results occur.

Clarify any potential misinterpretations by providing appropriate context for the data—avoiding the use of statistics without clear explanation. 

Continuously refine findings based on feedback to ensure final insights align with business objectives.

Finalization of the Project

Recognize that this is often an iterative process—initial findings may lead to new questions.

Revisit relevant steps of the business analysis process as needed to address emerging insights.

Once all revisions are complete and the findings align with expectations, the project can be finalized.

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