Write a Well-Structured & Informative Data Analysis Report
Whether you work with Big Data, AI, or otherwise rely on informative data to further your business’ goals, writing a well-structured data report matters significantly. Without it, your developers can be left in the dark about crucial points concerning the future development of important projects.
Despite COVID-19 and the social distancing norms it introduced, data analysts can still work to contribute in meaningful ways through data report writing. That said, however, how can you write a well-organized and informative data analysis report, which can then be delegated to others on your team?
The Importance of Writing an Informative Data Analysis Report
To start things off, let’s discuss why data analysis reports can and should find their way into your production pipeline. Data is one of the most valuable assets of the contemporary business landscape, and no company can thrive without it. Proper data analysis can help you make more informed decisions about your company, how to tackle projects or B2B networking, and how to manage available resources. It can only help your business achieve those goals if everyone on the staff is able to read it.
Data analysts are “one-man-teams,” inherently, thanks to the nature of their work. Their work, however, needs to be understood by managers and people in charge of making decisions crucial to the future of the company. Some of the most important benefits of writing a clear and understandable data analysis report thus include:
- The ability for everyone on staff to read through and comment on data
- Better customer and project investment targeting
- Innovation opportunities which stem from analyzed data
- The lowered margin for business decision error
- Higher profit margins thanks to smart resource investment
Writing a Well-Structured and Informative Data Analysis Report
Lead by your Professional Standards
Given that you are about to write a data analysis report, you should start by simply doing what you do best – analyze the available data. Every analyst or data science specialist has his or her own style of working with data.
How do you organize your own data? How often do you analyze the data in your company? Who typically reads your data reports, and what is their reception of your work? Start with self-reflection and apply your professional standards to the data analysis report you are about to write.
Inquire about Key Points
You should consult department managers and project leads on what their key points of interest are before you write the data analysis report. Tackling the major pain-points head-on will make the data report more legible and meaningful to your coworkers. Don’t be afraid of asking the staff about what their data reporting standards are, and your work will be that much better for it.
Jimmy Henry, Data Science Specialist and Writer at Subjecto education website said: “Prep work is half the work when it comes to writing a data report paper. You never know who might pick up your document and read it to glean useful information from it. Annunciate the major points of interest through bullets, bolds, and other editing forms before submission, and your report writing will become relevant for day-to-day application.”
Outline the Report before Writing
Once you’ve inquired about major points of interest in regards to data analysis with your colleagues, you should outline the report before diving into writing. Your report’s outline will give you a great perspective on the document’s length and enable you to cover every point of interest without skipping anything. Some of the segments of data analysis report writing to include are:
- Introduction (summary of the report, main points of interest, and table of contents)
- Body (gathered data, methods used, analysis of data, and results of analysis)
- Conclusion (concluding thoughts, future analysis possibilities, an appendix of references)
Writing a data analysis report is not unlike writing any other form of a report document meant for corporate use. However, writing a well-structured report means that a lot more people will be able to use it as a reference for decision-making and project development. Outline your data report before writing, and it will be more legible and allow for quick scanning as a result.
Level the Playfield
Terminology and readability can be major points of contention when it comes to data analysis reports. As such, you should aim for a conversational tone of voice and everyday lingo in your report to maintain clarity for your coworkers. You can seek out professional consultation services if you are stuck trying to come up with a way to write an informative data report independently.
Likewise, writing tools dedicated to editing and formatting can be of use once you are close to finishing your report. Level the playfield by using terminology, formatting, and references that your colleagues are bound to understand without a thesaurus.
Implement Data Visualization
Visualized data is a great way to showcase your findings in an easy-to-understand manner, even to those who may not be familiar with reading data. Charts, graphs, tables, and other forms of visual media which serve as additional context for your written report are always welcome in the report.
This will significantly lower the abstract nature of your work and allow many more colleagues to implement the report without consulting you about legibility. Likewise, you will have the opportunity to flex your creative muscles and do something other than extrapolating empirical data on a white sheet of paper.
Accept & Implement Coworker Feedback
Lastly, your coworkers or client are bound to have feedback to share in regards to your data analysis report – make sure to listen closely. Even though you may be fully confident in your abilities to properly write a data report, you will always hear something useful from third parties.
Individuals who were not involved with writing the report will have a different perspective on the document and be able to objectively criticize it. Accept feedback as well-meant comments on your work and think about whether you can apply them going forward. If not, nothing is lost, and you will come off as a team player, so make sure to consult your coworkers even after the report is written.
The main thing to keep in mind is that data analysis reports are meant for wide-spread use – their readability is of high priority. Put yourself in the shoes of your coworkers and think about how the report should be written and structured to make your cooperation seamless. Once you’re confident in “how” to write the report, you will be able to deliver much clearer and applicable results in writing going forward.