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  • Writer's pictureChantilly Jaggernauth

The MADness - how it all began.

The journey begins.

I’ve always had a passion for teaching and once upon a time I wanted to be a professor. However, I never understood or liked the idea of going from being a student to teaching a class without having real world experience. As a student I had a higher level of respect for my professors who came from the corporate world or had a consulting background. Therefore, I decided to spend a few years in the “real world” gaining experience before I began my true passion – teaching. Throughout my data analyst journey there were a few things that stuck out.

  1. There was a significant skills gap in employees being able to understand data. This ranged from employees I interacted with that didn’t know how to interpret a chart, to employees that didn’t know how to understand raw data presented to them.

  2. As great as these analytical/intelligent tools (Tableau, Qlik, Excel to name a few) are, the tools were pointless to those who didn’t understand data in general.

  3. Employers weren’t looking for super technical data scientists, but more so business analysts who could make data driven decisions.

My passion for teaching in addition to the problems (I prefer to say opportunities) I saw in the real world are the reasons I decided to start Millennials and Data – an organization dedicated to bridging the data literacy and analytical skills gap by training, mentoring and preparing millennials to enter a data-driven global environment.

Why Millennials?

In doing my research, I found that there were a ton of organizations that focused on providing companies with data literacy trainings for their employees. I also found organizations that provided in- person and virtual training for individuals who were willing to pay a training fee. However, I didn’t find an organization that was dedicated to training students before they became employees. My assumption was that teaching students about data was something that schools/universities should be doing. However, that is not always the case especially for students whose majors weren’t solely focused on analytics, mathematics, or engineering (I will call these tech majors). I decided to do additional research and interview a few students that were currently enrolled in business schools. There were very similar topics that stuck out during each of the interviews.

  1. Most students enrolled in non-tech majors were required to take at least one analytics course (generally excel focused) and a statistics course.

  2. Their professors focused on theory/lecture and didn’t show students the why/how it could be used in the real world.

  3. Coming out of these classes students still did not understand data.

After assessing the gap among student skills versus the skills that employers were looking for, I decided that the millennial generation was my target.

The Pilot Cohort.

Once I decided to pursue millennials, I needed to find a school. Given that I am a Howard University alum, I decided to pilot the program at my alma mater’s School of Business as I was very familiar with their curriculum and had already received a warm invitation to teach. On August 24th, the first class of the pilot cohort began with 10 eager students. Each of these students successfully submitted applications and interviewed to be placed within the first cohort. All of the students were unique in their own way but similar in their desire to want to learn about data. The team (Samara Wiley and Amarendra Donthala) and I specifically chose students who were pursuing a business degree either as an undergraduate or graduate. Coming into the program, they each understood that this journey was not about teaching them a software but about teaching them the language of data.

#MAD1 from Howard University

The 16 week journey.

To say this journey was hard would be an understatement. As the leader of the program, I had to find a way to not only teach a foreign topic to the students but keep them engaged throughout the entire process. To accomplish this we met bi-weekly for 6-7 hours per session. Having longer sessions allowed for the students to learn and be hands-on each time we met. Each session a new step within the data analytics process was introduced. Throughout the course we covered: data fundamentals, gathering requirements, collecting data, cleaning data, analyzing and exploring data, visualizing data and communicating with data. In addition to covering the fundamental aspects of data I ensured that the students were able to think critically about data by introducing a series of exercises each class that ranged from interpreting new data visualizations, to quickly analyzing raw data to answer questions, to bi-weekly case study projects. Lastly, each session the students were required to present their dashboards and findings from their bi-weekly project. This allowed for students to practice communicating their stories to an audience as well as being receptive to feedback.

Student feedback throughout the program.

Throughout the entire program, I made sure to gather feedback from every student. Having their feedback allowed me to adjust the curriculum and ensure that they were actually soaking in everything taught to them. Here is some of the feedback from the students:

  • “The program teaches data analytics and strategy skills that are useful and applicable to other academic and non-academic work. It is also very attractive to employers, especially the different business, litigation, and data consulting firms I interviewed with. Being able to talk about this program got me at least one offer for this summer. Additionally, not only are data analytics and visualization skills beneficial, but the strategy aspect of how to approach a dataset to create a solution/recommendation is also valuable and relevant to a variety of different business areas.”

  • “The cases that we work on are real world data. By analyzing and visualizing real world data, we get a practical knowledge of applying Tableau and not just learn the various functions on Tableau. The feedback received from the trainer and MAD students is also a strength of the program. The program allows us to develop the skillset of taking raw data and analyzing it. The MAD program is also great for increasing one's network by interacting with the global Tableau community.”

  • “Since I have started learning Tableau, I speak about it during my interviews. My interviewers spend a lot of time talking with me about what I have done using Tableau. They are really impressed when I show them my portfolio. I have already received an offer.”

Thank you card from the students.

A warm congratulations to #MAD1.

During the final week of the program, each of the students took the Tableau Desktop Specialist exam. Though the goal of the program was not to teach another tool, I decided that the best way for students to showcase their new skillset was to have a portfolio and a certification from one of the leading business intelligence organizations. I am happy to announce that each of our students passed the exam and have full-time offers or internships for 2019! Congratulations #MAD1! I am beyond proud of you all! Thank you for making this program a success!

What’s next for #MAD?

2019 is going to be an exciting year for Millennials and Data! Our next cohort begins January 18th at Howard University. The students from #MAD1 have all agreed to be mentors and advisors to the new cohort. If you would like to be a part of our journey and advise one of our students please contact us. We are looking for virtual advisors as well.

Based on the feedback we’ve received, we are also happy to announce that we are launching a program for individuals who are currently not in school but would like to receive our in-person training. More news to come! Lastly, we will be expanding to additional schools for Fall 2019. If you would like for your school to be considered please contact us.

Thank you for reading!



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