How to See New Connections in Data

Spotlight: Ezgi Bereketli, Data Engineering Product Manager

Technical and open minded, Ezgi Bereketli applies quantitative and creative thinking to help build a product that delights data users. Her deep understanding of data analysis, statistics, and economics help her anticipate the challenges data users face and develop solutions to guide businesses into the future. We sat down with Ezgi to find out how data users can make new discoveries.


You studied Applied Mathematics at Harvard. What was that experience like?

It was great! I always knew I really enjoyed working with numbers and using all the tools of mathematics to solve problems. When I went to college, I had all sorts of ideas about many things that I wanted to be, and I realized that they all had the intersection point of being quantitative. So I decided that in college, the best thing I could do was to get that foundation strong and learn the toolkit with which you can apply mathematics to problem solving. I chose to study applied mathematics on economics (and did a secondary in French!)

I love that in schools like Harvard, [your major] is about one third of the classes you take. So in addition to studying applied math, I ended up taking classes in a lot of different fields. I think that in the end, a majority of what I studied in college, and what I still like learning about, is how to apply one field to other fields, and [make] connections that might in the first place appear not the most obvious, or the easiest to think of, but in the end, lead to good synergies. I think that’s how I found myself in the world of data as well.


How do you uncover and make new connections in your work at Crux?

The first aspect is as it relates to large market datasets that people have been using for such a long time in specific ways. However, it’s really costly and hard to work with these datasets, and that might limit the time and the ability of people getting insights from them to actually dive into that level of data. So when we help you skip the costly data wrangling steps, there might be much more you can learn from that data.

The second aspect is on the discovery of data. I see a lot of potential in small alternative datasets. These usually come unstructured, and not very productized. Productizing data most of the time means cleaning it, standardizing it, and making it a lot easier to access and use. So I think that’s where we can add a lot of value. All those alternative datasets can be extremely valuable once you can get to the point of being able to read them, read into them, and learn what they have to tell you.

I also try to understand connections between the needs of our clients. At Crux, we want to integrate the goals of data users and data suppliers into the requirements for our product. It might seem at times that all of our stakeholders have different needs, but being a product manager is about finding the connections.


What advice would you give to someone who would like to work in data, who would like to enter this field for the first time?

First of all, I would strongly encourage them to pursue it! I think data is an excellent place to be right now, and it’s going to be an ever-growing field because its applications are unlimited. It’s very industry- and application-agnostic. Every type of business and every type of industry will have more and more emphasis on data going forward. That’s closely related to how quickly the presence of data is expanding–the sheer volume of it.

As for how to get into data, that strong quantitative background and education is extremely helpful. If this happens in college or school, that’s great, but even if not, there is a lot that can strengthen this background. Learning to code, at least the basics, is also very important— especially learning query languages like SQL, because those will teach you how to communicate and work with data.

Finally, it’s about curiosity—having an open mind about what you can learn. It’s not about, “I’m going to analyze this dataset because I want it to prove my point.” It’s about approaching data with a really open mind: “I’m going to analyze this and see what it tells me.”

Approach data in new and interesting ways, both from an analysis point of view and from a data discovery point of view. Look at different datasets, which you might have thought to be at most tangentially relevant for your business. Having that curiosity goes a long way in making data useful.


Ezgi is passionate about building the best data engineering product to make data even more powerful, delightful, and useful. Most recently, she spent three years at YipitData as a team leader and a senior data product analyst. When not architecting data solutions, she can be found jetting around the world, attending all sorts of music/art activities, and (soul)cycling. She hails from Turkey, but has lived in various European cities.

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