Visualising Data

Introduction

My e-portfolio stories my learning journey throughout the Data Visualization module of my MSc in Data Science with the university of Essex online. My e-portfolio is structured to highlight key learning experiences, professional growth, and reflective practices. By fololowing Gibbs’ Reflective Cycle (The University of Edinburgh, 2024) throughout for deeper analysis, I document the steps I have taken to achieve the module’s learning outcomes and demonstrate my professional growth.

In crafting this e-portfolio, I have engaged with Gibbs’ Reflective Cycle and academic papers to analyse my progression and identify areas of improvement. This aligns with the stance that a well-designed e-portfolio can serve as both a process and product of my academic journey (Walland & Shaw, 2020). By reflecting on practical tasks, feedback from peers and lecturers, and my own thought processes, I have been able to refine my technical proficiency, research skills, communication, leadership qualities, and personal resilience.

Reflection Approach: Gibbs’ Reflective Cycle

I have adopted Gibbs’ Reflective Cycle as the basis for my critical reflection. The cycle involves six key steps:

Description: on the learning experience throughout each unit in the module.

Feelings: on my emotional response to initially viewing the units and then feedback on the complete projects.

Evaluation: of the entire unit, the good and the bad.

Analysis: on the units in hindsight.

Conclusion: on the unit and what I have learned and what I would have done differently.

Action Plan: on how I would deal with the next unit or module.

Gibbs reflective cycle allows me to grow and learn actively throughout the module. By following the reflective cycle after every unit, I have the opportunity to look back at what I wrote all those weeks ago to come up with a stronger action plan on the entirety of the module.

Reflection on Each Unit

Unit 1: Foundations of Data Visualization

Description: The opening unit introduced basic visualization principles. With a case study on reading a complex visual displaying U.S. companies tax rates.

Feelings: I was enthusiastic, as the topic directly intersects with my background and role as a Data Science.

Evaluation: Positive: The unit was quick and a good refresher into visualization. Negative: I was very quickly humbled by the complex visuals shown, like the visual displaying U.S. companies tax rates. I have a lot to learn about the potential on visualisation.

Analysis: I have a lot I need to learn but the opportunity to do so. The new work is not difficult as of yet and so I need to take my time and grasp what I can.

Conclusion: The unit was quick and interesting. I have learnt the limitlessness of visualisation. Next time I will come in with an open mind, not be so rigid in thinking I know all that can be done.

Action Plan: From the next unit. I will grasp all I can and focus on learning new tricks. Taking down notes and preparing for the first projects.

Unit 2: Website Comparison (Ryanair vs. EasyJet)

Description: I was tasked with reviewing and critiquing the user experience of two commercial airline websites (Ryanair and EasyJet). I produced an initial post assessing the attributes, types of tasks viewers would undertake, how the data is represented, colour schema used, limitations and strengths and my personal views.

Feelings: I found this exercise engaging, as it combined user experience design with data storytelling. However, analysing real corporate platforms introduced complexity: I felt a bit disappointed in how even top airlines have limitations. Surprising when entire teams are dedicated to a robust website.

Evaluation: Positive: Ryanair’s brand identity was strong, with colour schemes resonating well with its logo. Effort can be put into every detail. Negative: EasyJet’s website brought irritation. Ryanair’s was not perfect either. All explained in my initial post you can view below.

Analysis: Drawing on visual design principles, my critiques are harsh and based off what I have learnt only recently. But this gave me an opportunity to look deeper into design of everyday user interfaces.

Conclusion: The unit was another opportunity to use what we have learned in the real world. Looking back now, I may have been a bit harsh and not taken into account the difficulty of the ‘perfect website’. Next time I would like to list how difficult it would be to get all user feedback to make the perfect website

Action Plan: I will take into consideration the main objective of a dashboard instead of trying to please everyone. As everyone will have an opinion. From now on, clarity beats creativity unless the audience calls for it.

Initial Post: View my project here

Unit 3: Peer Feedback (Reviewing and Being Reviewed)

Description: I analysed my peers initial posts on Ryanair and EasyJet and gave feedback. The feedback I received was I need to emphasize more on some of my points like how I stated EasyJet’s “cramped” map affected navigation.

Feelings: I appreciated the chance to compare experiences and gather multiple perspectives. I learnt, again, something I notice in many of my modules that I need to emphasize more on certain points. Something I believe is getting better but is defiantly my weak point.

Evaluation: Positive: I was commended for my insightful analysis by one of my peers. Who fully agreed with my analysis throughout. Negative: I was not thrilled to only receive two reviews, I would have liked more interaction from peers and the lecturer.

Analysis: Peer feedback is always great. I am able to compare projects directly while noting where I can see improvements and receive the same thing back. This gives me a great opportunity to understand the thought process of other learners.

Conclusion: I have again learnt that I need to work on my emphasis in my reporting. Strengthen my argument. Next time I will ask myself if a reviewer will have any questions on what I just wrote, if so, good chance I need to emphasise more on it.

Action Plan: Actively find where I can emphasise more on points I have made in future reports. Making sure each point is backed up and crystal clear.

Unit 4: Summary Post from Feedback

Description: I wrote the summary post, based on the initial post I wrote and the feedback I was given. The central theme was that no site is flawless, and user testing is key.

Feelings: I took a more positive approach. Feeling more like the team leader giving feedback than a critic judging every bad detail.

Evaluation: Positive: Peer review pushed me to write better and emphasise more. Negative: I would like less reporting and more practical coding now.

Analysis: Covering a report over three units feels a bit dragged. But it followed a great course to improve report writing. Great way to prepare us for the assignment coming in unit 8.

Conclusion: I learnt more about my own writing and my judgement. In future I will take more care in expecting perfection.

Action Plan: Ask why, instead of saying something is wrong with peers and my employees in the future.

Unit 4 - Summary Post View my project here

Units 5–7: R Refresher and Exploratory Data Analysis (EDA)

Description: These units I worked on basics to advanced coding in R. Practicing EDA (Exploratory Data Analytics) tasks like summarizing distributions, spotting missing values, and crafting multi-layered plots.

Feelings: I enjoyed the refresher. Though I am proficient in Python, I spent around 2 years working with R a few years ago in my undergrade.

Evaluation: Positive: R came back to me like I never stopped. I enjoyed the tasks we had to do. Negative: Though I enjoyed R. I would of liked the option to do it all in Python. My preferred language.

Analysis: The units showed me the EDA process is generally the same. But every time you run into different issues with cleaning and deciding what stays and what goes. Though that is my favourite part of analytics, so no complaints there.

Conclusion: I got caught up in R again and I got significant practice in the EDA process. I would of liked more complex EDA tasks. Messier data to play with.

Action Plan: I’ll treat EDA like prepping for a competition—clean data, spot patterns, and build intuition before any modelling happens. Make sure the data is spotless and I fully understand it.

Unit 8: Programming Project (Data Cleaning and Reporting)

Description: I had to create my own EDA on bank data. Giving the bank a ML (Machine learning) model that can predict potential clients based off clients that have progressed from leads to successful sales.

Feelings: I was initially excited, but the cleaning progress took me well over a week. With finding many tricks the university must of put in to catch us out. Like instead of null values, put actual values “unknown”, so traditional summary analysis will find no nulls. When I found this I was deep into the EDA and decided to remove them all and start the EDA all over. Which I thought would give me exceptional marks.

Evaluation: Positive: I worked hard on my code. Making sure I built a solid EDA. Negative: My reporting was again lacking. I did feel the word count had an effect on this, I need to work on saying less but emphasising more. Again, a trait I lack.

Analysis: My coding overshadowed the importance of good communication. The final mark was 62% (Merit). Though I am proud of what I have done, my reporting let me down again. Great learning experience nonetheless.

Conclusion: Brilliant code alone is insufficient. I learnt EDA can be tedious and though I pushed my EDA well. Next time I will take more time on my reporting.

Action Plan: I need to take more time to go over my reporting, again, push emphasise on points I make. I’ll split my time better: half for analysis, half for storytelling.

Unit 8 - Report View my project here

Unit 9: Dashboard in Grafana

Description: Though we have learnt a lot in Tableau, I chose to create an interactive dashboard in Grafana. The visual interface I use at the company I work at. My visual analyses real-time metrics. So I created a monitoring dashboard for the ticket team and the global systems manager. This was just a draft for the final project in unit 12.

Feelings: I was motivated and confident, feeling that my prior use of Grafana at work gave me an edge. I also worked with the systems manager to get feedback on what he is looking for.

Evaluation: Positive: The dashboard was a success. Improvements needed to be made, though expected. Negative: The lecturer gave feedback on some theoretical gaps in discussing how design principles from HCI (Human–Computer Interaction) influenced my Grafana choices. The lecturer recommended deepening reflection on how published design theories shaped my approach.

Analysis: The unit was a great way to get initial feedback from the lecturer before the final project worth 40% of our grade. I used everything I learnt throughout the module to create the dashboard and report.

Conclusion: My proficiency in Grafana was evident, but to score higher academically, I must work more on reporting, big shock, I am confident I can create the best report I have done so far in unit 12.

Action Plan: Cite relevant HCI articles and mention at least one or two design theories in unit 12 and when building dashboards in future.

Unit 9 - Dashboard Design Draft View my project here

Unit 10-11: Tableau Refresher

Description: With the final project now in sight. We put all focus on an introduction to Tableau and then more advanced dashboard to design in Tableau. From basic visuals to user specific dashboards.

Feelings: I was initially less enthusiastic about Tableau because of my preference for Grafana. However, with just under a year of experience in Tableau not too long ago in a role I had. Tableau came back to me very quickly. I enjoy open-source applications. But the premium of paid applications like Tableau feel like a luxury.

Evaluation: Positive: I quickly created advanced dashboards in Tableau. Enjoying the premium feel. Negative: I occasionally missed the open-source flexibility of Grafana.

Analysis: The unit gave fantastic opportunity to get to know tableau, but the limit of the two-week trail made it very difficult to get a good feel. Especially someone like myself who is a few weeks ahead of the unit objective.

Conclusion: Knowing multiple tools is a major benefit. Learning Tableau again showed me the limitations of Grafana but also showed me how many advanced open source features I get in Grafana that Tableau does not have.

Action Plan: Don’t drop knowledge on tools just because your company does not use them. If possible, in this context, I want to keep using Tableau in private to make sure I keep the skill I gained.

Unit 12: Final Dashboard and Report

Description: My final submission combined theoretical reflections with a polished dashboard. Using the feedback from unit 9 and all I have learnt so far. I aim to have an in depth project with emphasis on the most important parts.

Feelings: Being a few weeks again, I was able to slowly refine the project and improve it while I finalize this e-portfolio. Remembering all the action plans throughout the module. I felt pride and comfort knowing I was doing my best but also that this module is giving me its final test. Giving me the platform to build a user specific dashboard.

Evaluation: Positive: It is almost holidays! I get to build my own dashboard, only limited by HCI and what the user requires. Negative: The low word count of a thousand-word report feels limiting in describing the design principles and all the choices we made designing the dashboard. But I am confident in what I have built.

Analysis: The final project has three aspects to it, an audio recorded executive summary, a report and a manual for the dashboard. Giving ample opportunity to show off the dashboard but also my new method of report writing.

Conclusion: I feel confident in using what I learnt in this module in the real world. I look forward to receiving feedback from my lecturer on the project and presenting the final iteration to the manager who would benefit from it at the company I work at.

Action Plan: Feedback is fuel. I’ll treat every comment, good or bad, as a chance to sharpen my skills. I’ll review previous feedback before starting the next module to hit the ground running. Making sure to absorb what I can throughout every unit.

Unit 12 Manual, Report and Executive Summary Transcript View my project here

Reflection Piece

The Data Visualisation module has been one of the most practically useful and personally transformative modules I’ve completed in my MSc Data Science degree. It challenged me, supported my career goals and refined both my technical skills and the way I think about presenting data. Throughout this reflection, I will use Gibbs’ Reflective Cycle (The University of Edinburgh, 2024) and incorporate elements of Rolfe et al.’s (2001) "What? So what? Now what?" framework to support my reflections across learning, emotions, challenges, and future directions. I will also link this growth to key professional skills developed throughout.

What? Summary of Learning & Development

From building dashboards in Tableau and Grafana to designing visual critiques of airline websites and completing programming projects in R, this module offered a diverse array of tasks that sharpened my ability to communicate insights clearly and persuasively.

Each unit built progressively, from foundational visual theory, practical user experience critiques in Tableau, EDA in R, and finally, a polished dashboard project in Grafana. Notably, I chose Grafana over Tableau for my final submission because it aligns with the systems I use at work. Allowing me to link theory and practice in a meaningful way.

I approached the e-portfolio as more than a submission. It became my sandbox for experimentation and honest self-reflection throughout the module. As Walland and Shaw (2022) argue, an e-portfolio should function both as a product and a process—and this duality helped me document not only what I did but who I became throughout. That’s what developing throughout a career is about.

What? So What? Emotional Response and Challenges

It wasn’t all smooth sailing. Emotionally, I started this module on a high. Unit 1 reminded me that I already had a foundation in visualisation, but I was quickly humbled by the depth of theory. Realising how much more there is to data storytelling than clean visuals was frustrating at first, but eventually motivating.

The most challenging moment came during Unit 8. I discovered that the dataset I was analysing included “unknown” values instead of NULLs, causing my EDA to misrepresent key distributions. That moment of realisation hit hard. I had to redo everything from scratch, which pushed my limits but also revealed how much I’ve grown as a Data Scientist. As Sohail and Akram (2025) note, reflection enhances metacognition and self-awareness.

Another layer of emotion came from peer feedback. While I was commended for my technical precision, feedback repeatedly showed I tend to under-explain key points in writing. This is something I’ve always struggled with. Balancing technical detail with concise, punchy narrative and this module forced me to confront it head-on.

Now What? Changed Actions and Future Strategy

Development	Achieved	How I can work on it	Due Date
Balancing analysis with storytelling	Poor	My action plan going forward is to allocate equal time to technical development and report writing in future projects. Not 80% programming and 20% report writing. I can do this in my first month of my next module which begins 29 April.	End of May
Leadership	Great	I was happy with how I took action with the dashboard at work. I can improve this by pushing to fully implement the dashboard within the company.	End of April
Python and R	Great	I always work with python and have during this module but I would like to keep my skill in R and the best way to do that is to build my first few projects in my next module in R.	End of May
Approach dashboard design through a user-first lens	Attempted	Ask more questions like, “Does this help the user make a decision?” or “Will this allow a manager to make key decisions”. Build more dashboards with this in mind.	End of May
Frustration and challenges	Could do better	I struggled with my EDA, where I had to redo it. I would like to push more independent projects at work to work on the EDA process and managing projects.	End of June
Motivation and inspiration	Great	I always stay motivated and inspired. Through challenges and frustration, I got my work done and did it to the best of my abilities. I would like to use this motivation by doing more. Get into reading more papers and books to expand my knowledge on Data Science and visualization so it does not stop just because this module ends.	End of April
Literature review and independent research	Attempted	I tried to improve on this throughout the module and I can see the personal growth. Next step is to do better in the next module by reading more papers and finding better papers that relate to my projects.	End of May

Lastly, I’ll continue using my e-portfolio as a tool for professional development. As Schmude et al. (2025) noted, e-portfolios help students build their professional identity and monitor longitudinal growth, something I’ve now truly experienced. I’ve already shared parts of my dashboard with the systems manager at work, who’s eager to incorporate it into our internal workflow. This real-world impact has been incredibly rewarding.

Professional Skills Matrix & Evidence of Development

Skill	How I Developed It
Data Visualisation	Designed dashboards in Grafana & Tableau, applied HCI theory and brought in key references.
Communication	Brought together findings into my reports, learning to emphasise better
Critical Thinking	Improved how I respond to feedback
IT & Other Skills	Improved my R, Python, Tableau and Grafana.
Problem-Solving	Instead of panicking I got my head down and redid an entire EDA process after key findings.
Ethical Awareness	Focusing on user first designs instead of what I think is best.
Time Management	Like every module I get ahead by planning my weeks out for the entire module. Along with my work schedule and sport.
Research	Linked theory with practice, like exploring The University of Edinburgh (2024), Rolfe et al. (2001) etc during this paper.
Interpersonal Skills	Engaged in peer review. Learning from what I was reviewing and what I read about myself

Conclusion

Looking back, this module wasn’t just about building charts, it was about learning to think, write, and reflect like a professional. The process wasn’t always fun, but it was always valuable. Reflection has helped me recognise my strengths (technical problem-solving, persistence) and identify areas I’m working on (reporting with impact, theoretical grounding). I’ll take this forward not just in future academic modules, but in my career as a Data Scientist, where the ability to explain, visualise, and justify decisions is just as important as writing clean code. If anything, this module helped me bridge that gap. Like The University of Edinburgh (2024) suggests, reflection is cyclical. And as I close this module, I’m already thinking about the next project where I’ll apply everything I’ve learnt, stronger, more aware, and more confident in my growth.

References

The University of Edinburgh (2024) Reflection Toolkit. Gibbs' Reflective Cycle. Available from: https://reflection.ed.ac.uk/reflectors-toolkit/reflecting-on-experience/gibbs-reflective-cycle [Accessed 10 April 2025]

Walland, E., Shaw, S. (2020) E-portfolios in teaching, learning and assessment: tensions in theory and praxis. Available from: https://www.tandfonline.com/doi/full/10.1080/1475939X.2022.2074087#abstract [Accessed 10 April 2025]

Rolfe, G., Freshwater, D., & Jasper, M. (2001). Critical Reflection for Nursing and the Helping Professions: A User's Guide. Available at: Critical reflection for nursing and the helping professions : a user's guide : Rolfe, Gary : Free Download, Borrow, and Streaming : Internet Archive [Accessed 10 April 2025]

Sohail, A., & Akram, H. (2025). The role of self-awareness and reflection in academic achievement: A psychological and Bayesian analysis. Available at: The role of self-awareness and reflection in academic achievement: A psychological and Bayesian analysis - Pedagogical Research [Accessed 10 April 2025]

Schmude, M., McCoog, I., Adonizio, T., Ellison, HB., Howe, A., Caleb, AM. (2025) Use of an electronic portfolio for longitudinal assessment of personal and professional development in undergraduate medical education. Available at: Frontiers | Use of an electronic portfolio for longitudinal assessment of personal and professional development in undergraduate medical education [Accessed 11 April 2025]

Rani, YDC., Nissa, K. (2024) STUDENT’S INSIGHT INTO THE USE OF E-PORTFOLIOS FOR A REFLECTIVE PRACTICE PROJECT. Available at: STUDENT’S INSIGHT INTO THE USE OF E-PORTFOLIOS FOR A REFLECTIVE PRACTICE PROJECT | Esteem Journal of English Education Study Programme [Accessed 12 April 2025]