My Data School Application Experience (Part 1)

The application process of The Data School at The Information Lab proved to be quite unique. It was an opportunity within itself constituting exploratory learning, logic exercises and artistic expression. I am so happy that I stuck with the challenging activities!

You might be reading this blog in preparation of your own application submission. Maybe you are simply curious about the start of a career journey into data consulting. No matter the reason you are here, I hope this article resonates with you and ignites an interest in the community of data!

The application process of The Data School flowed through several steps. I had found it to be a well-structured experience.The requirements consisted of two dashboard submissions and several rounds of interviews.

  1. The Initial Interview
  2. First Dashboard Creation
  3. First Presentation
  4. Second Dashboard Creation
  5. Second Presentation

The initial interview was a simple series of questions and conversation that analyzed the basic qualifications. This was overlapped with optional ‘Meet and Greet’ gatherings that promoted a better understanding of the application process and a clear depiction of what it is like to work with the Data School. The process continues on to the technical portion with a total of two dashboard creations, followed by an interview after each build to present your creations.

My first dashboard was created over the course of a month, but the hours spent were quite spread out. Collectively, I may have spent about 60 hours on the project overall. Perfectionism beckoned often, so I may have spent more time on it than required. This was my first Tableau dashboard ever! Compelling impressions were the objective, while scope was the constraint. I was able to truly immerse myself in the project, considering that I was not working at the time. If you have to work, attend school, or focus on other obligations, it is still possible to fit in those hours. Spread the time out over the duration of the application process or start the project earlier for a later application date. Time management is imperative.

Organizing my time for a project that I had no experience in, proved to be a challenge. I had never used Tableau before and had minimal experience in data analytics. The knowledge I had obtained in data analysis using R and SAS during my undergraduate studies at Penn State University, although helpful, were applicable to a limited extent. You do not need to have any coding or statistical language experience to use Tableau, although it proved to be helpful when attempting to understand the logic behind calculated fields. A basic knowledge of data visualizations and data pipelines are enough to get started.

I focused on breaking the project into sections according to a simple data pipeline. This started with the data collection. We were able to pick a data set of our choice to visualize in Tableau. This level of freedom left for a broad range of creativity and expression of abilities. With freedom, comes responsibility.

A reasonable amount of research is required for the discovery phase, as there is no clear source of data. I had reserved about a quarter of my time spent on the application process for the review of best practices and finding a data set that I could work with. I avoided using a data set that I would have to spend a significant amount of time cleaning. This allowed for ample time to be spent crafting the actual dashboard in Tableau. Keeping this in mind, I was able to effectively manage the remaining work of the project.

Searching for clean data can be somewhat difficult if you are not familiar with reliable sources. Data.World and Kaggle are sites that contain a plethora of data set options. Data often needs to be cleaned according to the desired output and optimization but, for this project and in my case, the data can be ‘cleaned’ in Tableau using features such as filters. For example, excluding ‘Null’ values from a worksheet.

Once I had found a workable data set, I attempted to create relevant charts. I had explored topics such as chart type associations, filters, parameters, and calculated fields. I found myself exploring and often lost in the unknown realm of Tableau.

My build was focused on the video game, Stardew Valley. I found inspiration in the developer's story. A single person creating the artwork, coding and storyline of a captivating user experience design. I decided to implement my own artistic expression using Figma. I found out later that this is not typically done for a business dashboard, but I would not have done it differently. I was happy with my first draft.

During the build of each dashboard, The Information Lab recommends reaching out to current Data Schoolers for guidance. Specifically during the first submission, you are encouraged to submit a first draft early to receive feedback. It is recommended to not submit too early, nor too late. You should aim to have your dashboard at a reasonably progressed state, although not at a state where you would not be able to implement significant changes. Another test of scope and time management.

Once you submit your work for feedback, you will receive an email that states the recommended changes that you should implement. Within the remaining time, you are to adjust the dashboard accordingly. This will be part of the judgement in the submission.

Once a final draft has been submitted, you are required to present it. Practicing your presentation with friends and family proved to be helpful leading up to the big moment. A few preliminary questions are asked to gain a background understanding. This was followed by a detailed explanation of my dashboard and a few follow up questions.

Through trial and tribulation, I created a submission that I was proud to call my very first Tableau dashboard. From this experience, I had learned the basics of using Tableau. This set me up for success regarding the training I would later take in The Data School.

Please lookout for Part 2 that describes the second dashboard experience!

Author:
Leigh Davis
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