Week 12 Discussion - Your Thoughts

The call for people to learn to code reflects the demand for multiple skills in the digital age, which can indeed provide new opportunities for research and career development, such as data analysis and interdisciplinary collaboration. However, learning to code can also present challenges, such as insufficient time and resources, or an overemphasis on technology at the expense of core humanities values. Not everyone is interested in or willing to learn to code unless they are forced to. Overall, programming is a useful tool that can be used to make our work easier by automating many tedious steps. However, it should be used to better serve humanities research, rather than becoming a required skill or replacing the advantages of traditional disciplines.

In the Washington State Library presentation titled "What data does your community need the most?", the presenters encouraged libraries and library professionals to move beyond providing data for their community and instead curating data for the community. As I move forward with my own development in curating data for our community, Knaflic’s final chapter provided steps that feel reasonable given my personal resources of time and focus.

1. Learn your tools well: Our public library won’t likely add Tableau software ($900) to our annual budget. Rather, I will explore Microsoft Excel in much more detail, particularly focusing on cleaning data and creating data visualizations.
2. Iterate and seek feedback: I love Knaflic’s optometrist approach for iterations. Start with visualization A, make a copy of A, make an adjustment to it, save as visualization B, and then compare A and B side-by-side. When stuck, I can ask a coworker to review them with me.
3. Devote time to storytelling with data: Much like when I would first draft lesson plans early in my teaching career, I need to allow time for each step of the data visualization process. The more I do this process, the more seamless it will become, and I’ll get better at communicating data stories.
4. Seek inspiration through good examples: I already notice data visualizations more than I did before. When possible, I will download or take screenshots of these images and save them for future reference. Additionally, I am now following Knaflic’s podcast and will listen to episodes.
5. Have fun and find your style: It’s so fun to go back and see how much my skill and style has grown. Time to start practicing!

Beyond this class, I plan to use the skills and knowledge I have gained, along with the personal style I have developed in my data visualizations, to pursue a career in data science! Where I am able to transform data and statistical analyses into visualizations that are easily interpreted by my target audience.

I’ve also noticed that tools like Power BI and Adobe Illustrator are frequently mentioned in job descriptions, making it essential for me to master them. I plan to take LinkedIn Learning courses on these tools to position myself as a stronger candidate.

Overall, I envision myself continuously growing as the field of data visualization evolves. There is always something new to learn and skills to refine within this field. This course has been fundamental in helping me develop a keen eye and intuition for selecting the right graphs to effectively present data and tell compelling stories.

I believe a data journalism professional or anyone who works with analyzing and presenting data has the responsibility to ensure their work is accurate, transparent, and clear. Verifying data and presenting it in an understandable, accessible way, without bias or misleading interpretations, is important for all stakeholders: the organization, profession, and public. Another responsibility that should be required is that they are open about their methods and sources, explaining how the data was collected, processed, and analyzed. Additionally, they should consider ethical issues, like protecting privacy and ensuring data is presented fairly, so the public can make informed decisions and trust the journalism profession. These things are important because not doing these things can lead to manipulation of the public and vulnerable populations as well as create distrust in the organization and even the greater profession. 

Beyond this class, my plans for professional development regarding data skills and visualization are primarily to provide insights on consumer or business-related data. I am entering the field of data science, and a large aspect of the jobs I'm applying to is creating reports based on the data I would be managing, collecting, maintaining, etc. With this comes presenting and supplying that data with a large range of audiences. I have learned a lot in this class about how to present many different types of data, and how exactly that data should be expressed to each audience type. As I'm in the final three weeks of completing my master's, I'm already finding myself implementing visualization tools learned in this class in my presentations and visualizations I'm creating to present my data. 

Beyond this class, what are your plans for professional development regarding data skills/visualization?

I currently work full-time for the Wisconsin National Guard, and my role consists of supporting service members who are pursuing education. Over the last couple of years, data has become increasingly important to our organization. My specific goals for my office include using data to better understand the demographics of our service members, their eligibility for different educational benefits, and which demographics are utilizing the resources available to them.

I intend to continue growing my data visualization skillset through applicable projects at my job, open-source training, and potentially more formal classes. However, I am limited by the data visualization tools that are approved for use by my organization. The most useful tool appears to be Microsoft Power BI, so I will be taking advantage of free videos/training resources or courses sponsored by my employer to learn this tool.

I currently work in the auto product area, specifically the usage-based insurance product, and we have quite a bit of dashboards that report different metrics around product performance and data-source investigation.

Taking what I've learned from this course, I'd like to help make those dashboards more user-friendly (they're currently Looker dashboards that are essentially tables that can be filtered by drop downs) by conducting UX techniques with actual users of the dashboards and develop visualizations that answer their questions based on their needs, give them quick insights and allow them to dig deeper while being easy to use. Hopefully, if I can increase the usability of those tools more users will use them and they'll be more efficient (and excited) when using them.

There are some pie-in-the-sky goals by leadership that these dashboards could be a central location where multiple stakeholders across the organization can come and understand what's happening and make informed decisions based on insights from the dashboards - I would argue for that happen they need to be usable and useful first.

I'd like to establish a design system of sorts, where I could create a consistent set of visualization techniques and styling that will work across different dashboards while maintaining consistency between them. We'll see what happens but excited to try!

My technical background includes machine learning and deep learning. So I think I will be pretty much working towards a data scientist regarding recommendation, searching, and advertisement algorithms. I'm currently finding research assistant positions back in my home country in deep learning and data mining, etc. I believe for algorithm-related industry positions, a solid background for DL coding techniques is a MUST. After one or more years of research, maybe I will also apply for a PhD position or just find a job, hope I will be qualified then.

I hope that after taking this class I can spend more time learning how to collect, analyze, and effectively present data at my work. I know that the head of our department is really interested in us utilizing data in our decision-making more, and I think that my area has a lot of really interesting and important data that could be better used and shown. While I have enjoyed getting to learn more about the data visualization software in this course, particularly Tableau, I know that I am not an expert with it, but a number of people across my organization also use various data visualization software and I can lean on them for assistance if need be. 

I plan to harness data visualization best practices to communicate actionable insights to stakeholders as I embark on a career in data science. The course has equip me with valuable insights into how to communicate data effectively through simplicity and consistency, ultimately altering my prior views.  I am still in shock that Alaska is the largest state, and truly think the map should be scaled to improve public education and understanding. 

To bridge the gap between analytics and humanities, learning to code is essential. As a student in the data science in human behavior program, I have successfully overcome the daunting learning curve of programming. Learning to code increased my understanding of research methodologies and iterative decision making, allowing me to interpret scientific literature with relative ease. 

A data journalist is responsible for documenting clean, efficient, and reproducible code that can be integrated into text for enhanced public engagement. Within the organization, the data journalists's findings should be replicable such that a coworker could run the same analysis and obtain the same output. Whenever feasible, one should adhere to open data practices and lead professional standards by example. 

I plan to develop my data and visualization skills through a combination of hands-on projects, peer support in addition to my formal education. In my current role, I have various opportunities to put the skills that I have learned to the test. I plan to start creating Tableau visualizations for the lowest impact projects and move on to higher impact projects as my confidence and skills grow. I have taken the preemptive step of joining the Tableau Community of Practice at my workplace. This group is fairly new to my workplace and have been covering the various data sources onsite, however, I am looking forward to the group moving into sharing best practice and examples of work.