Like many Data Schoolers, I don't have a data analytics background. I spent years studying and working in public health, eager to identify tools to prevent chronic diseases. And yet, The Data School took a chance on me and has proven to be a very fitting professional home for me. I’m amazed by everything I’ve already learned about data analytics consulting. You know, The Data School isn't looking for experienced data analysts but for applicants’ transferable skills. Nervous about the multi-round application process? Believe me when I tell you it was nothing but fun. The Data School has set it up that way; they support you throughout the entire process to make sure you shine and maximize your chances of being hired. So far, three weeks after having started, the support, encouragement and mentorship has continued. I may be lucky, but if I did this – coming from public health with no data analytics background – so may you.
Turns out that public health and data analytics consulting share a similar approach to data, which helped me distinguish myself during the application process. Below, I explain in detail what I would have loved to know when I started the application process. So here’s my advice to you. I hope it helps you strategically position your background during the application process! And of course reach out to me with any questions!
#1 Public health and data analytics both use data to understand complex systems and drive better outcomes. In public health, you analyze data to identify disease patterns, risk factors, and intervention opportunities. In data analytics consulting, you do similar pattern recognition work focused on business processes, user behavior, and operational metrics. Both require analytical thinking and involve hypothesis formation, data wrangling, analysis, and interpretation of our findings into actionable recommendations. All fun things.
#2 In public health and data analytics consulting, it’s crucial to understand WHO your stakeholder is (or 'know your user'!). Knowing your audience is a crucial place to start any data process and informs all subsequent decisions you make.
In public health, you design interventions and present findings with certain demographics and target audiences in mind:
- Which medications are appropriate for whom? How should these be administered given a host of variables like socioeconomic status, comorbidities, health beliefs, etc.?
- Will your data be presented to patients, who may have limited health literacy and will need to make informed decisions about their care?
- If you’re hoping to publish your research, what’s the aim and scope of the selected journal?
In data analytics consulting, you design dashboards with the end user in mind:
- Which metrics and KPIs is the client prioritizing?
- Are certain charts or presentations especially effective in this client’s industry?
- Which visualizations would help their team best understand and solve their business challenge most effectively and efficiently?
#3 In public health and data analytics consulting, knowing WHAT your stakeholder wants is key. Clarifying an end goal helps provide a roadmap for data analysis, whether this means identifying important data points, types of analysis, or gaps in data that have yet to be collected. Similarly, strong data analytics consultants always ask (good and targeted) questions, especially ‘why questions.’ Asking ‘why questions’ doesn't just help you understand your client’s goals better, but it can help the client understand them better as well. For example, they may not have considered how their current metrics might need to be reconsidered or restructured. They may also realize while working with you that what they initially had in mind may not be what they need to achieve their ultimate business objective.
#4 In public health and data analytics consulting, we translate data for technical and non-technical audiences. In public health and data analytics consulting, we’re often the bridge between technical analysis and decision-makers who need clear, actionable insights without getting lost in methodological details. Explaining data to non-technical audiences is essential in both fields, whether you're helping a community understand particular health risks or helping corporate executives understand what their data reveals about their business.
#5 Public health and data analytics consulting requires data stewardship. As professionals working with data, we’re trained not only to analyze but to consider all other data elements as well. We bring together different data sources, work with ‘messy’ datasets, and need to know about data privacy and ethics (critically important in both fields!). Again, key here is also to ‘know your data’ (KYD) and all the data represents to have a very clear understanding of how it can be analyzed, presented, used, and applied.
I’m sure that no matter your educational or professional focus, you can identify your valuable transferable skills. Think about how you've managed relationships, tackled projects, approached problem solving, worked with data, and communicated complex information to diverse audiences.
Whether you have a health background or not, I'm always happy to chat about The Data School! Feel free to connect with me on LinkedIn or reach out via email: britt.vanderpoel@theinformationlab.com.