Interview: Bert Svab, Liftago on why hackathons matter

Petr Šimeček

Written by
Petr Šimeček

November 14, 2017

It’s great having a chance to sit down with you “virtually”, Bert. Could you kick off by introducing yourself and what you do?

Sure. I’m only in my mid-twenties and currently work as a business intelligence analyst at Liftago, a transportation startup in Prague, Czech Republic. I’m also a member of the Google Developer Group, and I organise hackathons and industry events in my home town of Pilsen. I almost ended up at the electronics and electrical engineering faculty of a local university, but I soon realised that I didn’t want to follow the standard programming or electrical engineering path.

Tell us about Liftago, the company you’re currently working for.

Liftago is based in Prague, the Czech Republic. We’re a startup with the long-term goal of creating an open market for urban transport, and replacing the need to drive into city centres with on-demand mobility. Just take a look at Google Play! Liftago is currently the best-rated ride-hailing app around here. It gives passengers a choice of drivers in the area, together with a rating, price, and other real-time information. To keep in touch with us, check out our Blog or follow our Instagram profile.

How does the C-Suite at Liftago see data? Is it seen as a strategic opportunity or more of a box-ticking exercise with a list of buzzwords?

The attitude towards data was one of the reasons why I decided to join. The CEO is an ex-engineer, so great importance is attached to data analytics. I’d say that the whole company really has adopted a data-driven mindset, whether we’re talking about product development or marketing.

What does the data team look like?

Well, you are talking to it right now. BI is my responsibility, and Liftago has a 27-member BI team. The first person to join us is an intern from Poland, who studied quantitative finance and is highly skilled at data modelling in R. Right now, my job mostly involves ETL and BI. We work together perfectly and, for example, we built a brand new dataflow for marketing incentivisation within two weeks. We’re considering recruiting another full-time team member soon, but we also work with consultancy company Trologic.

Outsourcing in BI, and using agencies, consulting companies and micro teams is a big issue right now…

I  like working with our consultancy company, Trologic, very much. Trologic brings a different perspective; it’s often able to spot things and issues that insiders might miss. And it’s also really important to have your hypothesis validated from the outside.

What is the best thing about working with Liftago from an analyst’s point of view?

What I like about Liftago most is the openness. We work with a local open-data initiative organising and attending hackathons, in which we’re trying to bring public transport data to our data, to help users get around as smoothly as possible.

We recently opened up one of our data sets and challenged the tech community to work with it in different ways by tagging #jedemeData. The outcome was amazing, and you can see the results here.

What are the most critical components for success in a data-driven startup?

The way I look at things, there are two important success factors for data analytics: time and availability. For example, for the availability, we use MongoDB as our primary database for all our data, but because of Mongo’s level of difficulty, only a handful of people in the team were capable of working with the data directly. This has changed with Keboola as our ETL framework, in which reports can be created simply with SQL, so it’s a lot easier to work with in cases in which we have a much wider team.

How do you guys share insights with people who aren’t “data savvy”, e.g. the people on the front line of your business, the drivers?

BS: We take this issue really seriously. For every new driver we hold induction sessions, in which we share very interesting tips and tricks that we get from the data. Of course, we try not to bombard the guys with charts, and make sure we present these insights in an understandable way.

Let’s rewind a bit to the time before all the cool data magic stuff that you do now. How did you get started and what was your first job?

My first job, when I was straight out of university, was really different. AIMTEC, the company I joined, has been around for 20 years now, so you could say it has a more traditional approach when it comes to IT services. When I started there I tried a lot to promote the “data-driven” mindset that I believe people should have, not just among the development team but also among the business users and consultants.

I wanted us to get rid of Excel and to start to use more effective tools, automate processes and to set up a standardised framework for measuring our KPIs across the board. On every occasion, I tried to “disrupt things”. In fact, innovations in general were the main part of my job.  It wasn’t easy, but making changes was the only right way, so I’m glad I’ve introduced this approach.

That’s not easy. People are generally resistant to change, and a disruptive approach like this isn’t always appreciated by everyone.

It wasn’t easy at the beginning, and it involves long-term effort, but the great thing about data is that you can convince people with results. I’ve constantly sought innovation and have always been attending community events, meetups and hackathons. That’s a great way to connect with people, to keep learning new things and to be constantly inspired.

How did you get involved in organising data hackathon on your own?

Well, I’m really active in this community and I had the chance to take part in many others, including the Data Festival, which the Keboola team organised. I decided that I needed to do something to keep this community going in my hometown.

My previous company was hugely supportive, especially the HR department, which saw it as a great opportunity for employer branding and recruitment. Typically, we built solutions around warehouse management, so we decided to base the hackathon around IOT which, together with augmented reality, was a very interesting topic for my company at the time.

How did the first event go?

It was a huge success, and despite some initial pushback, in the end everyone at the company loved it. We had, at any given moment, about 70 people actively working on the solutions or in other workshops for non-programmers, who were part of this event.

What did you enjoy about it the most?

It’s most of all the opportunity to connect people from both sides: the engineers and programmers on one side and the business people on the other. I don’t really feel I belong 100% to either of these groups. So I think a dialogue between them is absolutely critical for the future success of our field.

This is a very interesting point. We see very few people “in the middle”. What brought you there, what technical knowledge do you have, and why do you define yourself as a mix of the two?

Before university, I never saw myself as a programmer but as a classic self-taught example. I learned the usual HTML, CSS and PHP. Later, at uni, I took some classes in C, Java and MATLAB. I love maths, so MATLAB was something I enjoyed enormously. Much later, at one of the community events, I was extremely impressed by some outputs from analysis in R, and I really saw that as something I wanted to focus on. R is my favourite, but I also frequently use SQL. On the other hand, I’m also very interested in economics, project management, and business in general.

You’re 25, at the very start of your career and in your second job, but this whole industry keeps changing so fast. What do you want to focus on in terms of learning and your own growth?

Instead of focusing on a new language or learning to use a new tool, I’d like to keep growing my skill-set more horizontally. As with everything else, practice makes perfect. When I’ve a chance to build a similar project, any analysis in R or ETL, or a reporting system in the BI tool for the fifth time, it will be much easier to avoid newbie mistakes. And the entire process will be much smoother. Also, I believe communication is one of the most important areas of data analytics, so I think that’s something I want to keep working on.

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