Get a fresh perspective from an Infare Insider. Learn more about the people behind our success. This month, we interviewed Paulius Gulbinas, Leader of one of the Infare Data Collection teams, based in Vilnius.

About Data Collection

Data collection is at the heart of Infare’s DNA. Without data, there cannot be intelligence. Hence why one fourth of Infare’s total workforce is dedicated to data collection worldwide, with teams working daily to ensure data retrieval of the highest quality.
Paulius leads a team based in Vilnius and is a data collector himself.

Paulius, tell us about your career at Infare

I joined Infare, in Vilnius, as a data collector in 2013. At the time, I was particularly keen on discovering all of the processes of data extraction that Infare was using. I was also fascinated by how our products, such as Altus or Pharos, were designed to retrieve, analyse and report data.

As an avid learner, I always make sure that I remain top of the game. I read a lot, I learn new technics, discover new technologies, search for new untapped areas. What I like most is to share discoveries with my colleagues so we can discuss, debate and help each other.
I would say that it was my interest and willingness to help others that led to more challenging tasks and led me to the opportunity of leading the team.

What kind of data do you collect?

We collect four types of data:

• airfare pricing information,
• vacation data about whole packages,
• channel monitor which is the rank of airlines in Online Travel Agent searches,
• and ancillary data such as extra leg room, priority boarding, additional baggage items, etc. which are all extra pricing besides the basic airfare itself.

Can you describe a typical day at the office?

By 9am, the whole team is at the office, with a cup of coffee, ready to start the day. We all sit in the same office, a large open space on floor 10 of our Vilnius office, so it is very easy to talk with each other, solve challenges together, get another opinion in the room. It is the ideal working model and is also a really great atmosphere. We break for lunch together in our cafeteria too so spend a lot of time together. That is why it is so important for me to have a unified team.

What we do essentially every day is to collect data and provide such data to other internal departments before it is delivered to our airline, airport and travel agency customers. The reason why we do data collection daily is to ensure the highest level of accuracy.

An essential part of our job is also to ensure that the level of quality assurance of such data is met to prevent mistakes and defects. It means we filter the data through a long list of criteria, like teams of scientists would test a medication again and again before its release to market. All collected data, from all sources, is validated and checked automatically.

Finally, we need to constantly be vigilant about sources. Changes in data sources are constant, so we really need to identify them as quickly as possible and manage them by implementing new or existing codes within contractual service level agreements.

There is never a dull day. This is what makes our job so exciting and rewarding.

Which part of data collection do you find most challenging?

I think it is the overall scope of what it takes to collect data and to work as a data collector. A data collector must not only write efficient code but also be a problem solver. It is also very important to know how other systems and departments work at Infare and, most importantly, how customers use and perceive our data. Attention to details and logical thinking are also critical skillsets for a data collector.

How do you make sure that the information which collected maintains its integrity all through?

We ensure that the changes in the code are controlled by peer review before being delivered to production. An expert from our team checks that the data is error-free, and the best possible solution was implemented. It may seem simple, explained this way, but that is an extremely important job and requires extreme precision and a high level of expertise.

Handling such a large volume of data is a challenge. Can you tell us your secret? How do you make this work for Infare and its customers?

Working with big data is indeed quite complex and would not be possible without the right tools.

To give you a concrete example, we check collection status on 60 000 000 searches a day and perform checks of up to 2 400 000 000 data rows a day. Despite of being extraordinary people, we are not magicians. It would be humanly impossible to conduct such task. We do need automated tools to help us do just that. And in that particular case, we have developed an issue tracker that allows us to identify data sources with issues instantly or by comparing statistics day to day.

How do you identify and apply new technologies in your job?

There are a lot of clever and bright minds working in the Data Collection Team who like to search and apply new and promising technologies to overcome issues in our daily work.
Machine Learning is one of them. It is fascinating. We already use ML at Infare, to collect data, but know we are just at the start of it.

For more questions, feel free to reach out to Paulius directly at pgu@infare.com