Experiential Learning of practicum projects: A boon for emerging analysts

Harsh
3 min readApr 23, 2022
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I joined the MSBA program at UC Davis in Aug 2021, with a lot of preconceived notions of what constitutes being an analyst. In hindsight, most of my options were based on my own Hubris, having spent two years at an early-stage startup. Over the last 6 months, I’ve had the opportunity to learn from various professors, learn new techniques, understand new applications, and most importantly, work with KQED as a practicum MSBA industry partner. We were tasked with improving user retention, something KQED is already ahead of the competition but they wanted to improve an already very impressive number, especially in the current climate.

Looking back, I realize that I was like a frog in a well, working at my previous company. Since I was coming out of a long career in academia, I quickly learned the idiosyncrasies of working in a corporate world, but, KQED has made me realize the vast array of issues that we can hope to encounter in different fields and about various applications of analytics. I have tried to detail some of my learnings below:

1. Data cleaning

Arguably, the most important and simultaneously the most tedious part of the project. Though KQED is an old media company, they have pristine and well-collected data but as the technology improved, they started collecting more and more data points for each donor. This led to a large number of null values for some of the features. We tried various ways o avoid implementing complex data imputation techniques but when we finally did put in the time and effort, it made our final modeling job much easier and more accurate. This made me realize that data cleaning is a very critical step and may be the difference between a successful and failed project.

2. Managing Stakeholders

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Managing stakeholders is one of the most important aspects of an analyst’s job. But, working with KQED made me realize that working with non-technical stakeholders presents a completely different set of challenges. It forces us to come up with simple explanations for some of the most complex problems, and in my opinion, the only way we can do that is when we understand the topic completely. It forced me to be more thorough with my work. This is also a very important step in trying to maintain stakeholder expectations because it might be possible that the non-technical managers may not have the best idea of how much work or time is involved in developing any new feature.

3. Innovative solutions

As I mentioned above, about the good quality of KQED’s data but due to lack of proper warehousing, we had to come up with innovative and cheap solutions. One of the examples that immediately come to my mind is that we wanted to use Google’s API to collect US election data, we decided to use Mongo DB as a database since it’s cheap and effective. The stakeholders liked the idea so much that they have now agreed to implement this throughout their whole company. This is one of the biggest takeouts from this practicum for me.

4. Analytics at Non-Profit

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One of the other advantages of working with KQED is to see how small but data-driven decisions can bring out a significant change even for non-profit organizations. KQED could be a case study on how to maintain data sanity over a long period of time and how to utilize them to our advantage even with very limited technical or financial resources.

In summary, I would say that this practicum project with KQED has shattered a lot of the beliefs I had before and made me a better employer in general and a better analyst, more precisely.

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