What are the best practices for designing a data reporting template for data integration and migration?

1 Define your objectives and audience

Before you start designing your data reporting template, you need to have a clear idea of what you want to achieve and who you want to communicate with. Your objectives and audience will determine the scope, format, and content of your report, as well as the level of detail and technicality. For example, if your objective is to track the status and performance of your data integration and migration project, you might want to create a dashboard that shows key metrics, indicators, and milestones. If your audience is senior management or stakeholders, you might want to focus on the business value and outcomes of your project, rather than the technical details and challenges.

3 Design your data model and structure

Once you have your data sources and tools ready, you need to design your data model and structure for your data reporting template. Your data model and structure should reflect the objectives and audience of your report, as well as the data sources and tools that you use. You need to define the data elements, attributes, relationships, and rules that will shape your data report. You also need to organize your data into logical and coherent categories, hierarchies, and dimensions that will facilitate the analysis and presentation of your data. For example, you might want to group your data by source, system, entity, attribute, or time period.

4 Create your data queries and calculations

After you have your data model and structure in place, you need to create your data queries and calculations for your data reporting template. Your data queries and calculations should enable you to retrieve, manipulate, and aggregate your data from your data sources and tools, according to your data model and structure. You need to write clear, accurate, and efficient code or formulas that will produce the desired results and outputs for your data report. You also need to test and validate your data queries and calculations to ensure that they are correct and consistent. For example, you might want to use SQL, Python, Excel, or other languages or tools to create your data queries and calculations.

5 Design your data visualizations and layout

The next step in designing your data reporting template is to design your data visualizations and layout. Your data visualizations and layout should help you to convey your data insights and messages in a clear, concise, and engaging way. You need to choose the right type, style, and format of data visualizations, such as charts, tables, maps, or graphs, that will suit your data type, purpose, and audience. You also need to arrange your data visualizations and other elements, such as titles, labels, legends, or filters, in a logical and aesthetic way that will enhance the readability and usability of your data report. For example, you might want to use colors, fonts, icons, or images to create your data visualizations and layout.

6 Review and refine your data reporting template

The final step in designing your data reporting template is to review and refine your data reporting template. You need to check and verify that your data reporting template meets your objectives and audience expectations, as well as the data quality and accuracy standards. You need to evaluate and improve the functionality, performance, and appearance of your data reporting template, as well as the clarity, relevance, and impact of your data insights and messages. You also need to solicit and incorporate feedback and suggestions from your users, clients, or stakeholders to ensure that your data reporting template is useful, valuable, and satisfactory. For example, you might want to use metrics, surveys, or interviews to review and refine your data reporting template.

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?