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Answering Questions About Data

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BizOps bridges data and strategy. Why? without good data, “strategic decisions” are educated guesses at best.

What metrics should the business be thinking about? What story is the data telling? How should data play into the company’s decision-making at the highest level? Answering questions like these is a core bizops competency.

At a more granular level, it falls to BizOps to answer key questions like:

  • How are users using the product?
  • What do they like and dislike?
  • How should the company think about where and how to invest resources for maximum impact?

All of these questions require a hard look at the company’s operating data.

How Bizops Interviews Test for Data Skills

Be prepared to work with data at different levels of detail throughout your interview loop. At a high level, you might be asked to choose metrics for an initiative you’ll recommend during a case interview. At the most detailed level, you may be asked to clean and manipulate a raw data set and provide recommendations as part of a takehome.

Interviewers are looking for candidates who can:

  • Quickly sort through raw data to pull insights from messy or disjointed data.
  • Gut-check initial insights for accuracy and dig deeper when needed.
  • Propose and run simple experiments and analyze results to drive decisions.
  • Choose metrics to track success.
  • Cleanly and logically present insights and recommendations to different stakeholders.

Specific data questions you might encounter include:

  • “Choose a meaningful metric to measure the success of a new peer-to-peer payments app.”
  • “[Given a dataset including data related to a food delivery service] Write a SQL query to sum the number of rides and deliveries completed for each zip code.”
  • “[Given a data set including company financial data] What hypotheses do you have as to what is driving company performance? What questions do you have, and how would you go about learning more?”

In the next few lessons, we'll demystify how companies test for key data skills.

First, we'll talk about data intuition and why it's important. Can you look at raw data and identify missing, noisy, or erroneous data? What do you need before you can begin drawing meaningful conclusions?

Next, we’ll talk about manipulating data to uncover valuable insights. We'll review some basic operations and when to use each.

Finally, we’ll talk about storytelling with data. A key skill for any strategy or bizops person is communicating data-driven recommendations elegantly. You'll be presenting your findings to different audiences throughout your career - telling a good story with the data you're given will give you a major leg-up in interviews.

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