How do you use data visualization or reporting tools to present or explain your data processing results?

1 Why data visualization or reporting tools are important

Data visualization or reporting tools are software applications that enable you to create, edit, and share graphical or textual representations of your data processing results. These tools can help to summarize and highlight the key findings or insights from your data analysis, compare and contrast different data sets or variables, explore and discover patterns, trends, outliers, or relationships in your data, and communicate and persuade your audience with clear and compelling data stories. Furthermore, they can bolster your data processing skills and demonstrate your value as a data professional, especially during a job interview.

2 How to choose the right data visualization or reporting tool

When choosing the right data visualization or reporting tool for your data processing project, there are several factors to consider, such as the type and format of your data source and output, the purpose and audience of your data presentation or explanation, the complexity and customization of your data analysis and visualization, and the cost and accessibility of the tool. Popular tools in the market include Excel, Tableau, Power BI, Google Data Studio, and R.

3 How to prepare your data for visualization or reporting

Before you use any data visualization or reporting tool, you need to prepare your data for visualization or reporting. This includes cleaning and validating your data to ensure accuracy and completeness, integrating and transforming it to make it compatible with your tool, analyzing and interpreting the data to extract meaningful information and insights, and organizing and structuring the data to make it easy to visualize or report. Various data processing tools can be used for these tasks, such as SQL, Python, or Excel.

4 How to create effective data visualizations or reports

When preparing your data for visualization or reporting, it's important to create effective data visualizations or reports that can effectively convey your data processing results. To do this, you should select the appropriate type of chart, graph, table, or text for your data and purpose. Additionally, you should design and format your visualization or report to make it attractive and readable. Labels, titles, legends, annotations, or captions should be added to explain your visualization or report. Colors, shapes, sizes, or icons can be used to highlight or emphasize important data points or messages. It is also important to avoid clutter, distortion, or misrepresentation of your data. Various tools can be used to create and edit these visualizations or reports such as Excel, Tableau, Power BI, Google Data Studio, or R.

5 How to present or explain your data processing results

Presenting or explaining your data processing results to your audience is an important step in the data analysis process. To do this effectively, you should plan and structure your presentation to have a clear and logical flow. Additionally, storytelling techniques can be used to engage and persuade your audience with the data. It is also important to provide context and background information, as well as highlight and summarize the main findings or insights. Evidence and reasoning should be provided to support any claims or recommendations. Anticipating and addressing potential questions or objections from your audience is also essential. Various presentation or communication tools, such as PowerPoint, Google Slides, or Zoom, can be used to deliver and share the presentation or explanation.

6 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?