Q&A with Martin Weiss, Analytical Consultant and Project Manager

Martin Weiss

We all know about Germany’s world-renowned reputation for efficiency and technological innovation. It’s no surprise then to find a tech superpower like Google using Hamburg as one of their main European bases. Based there is this week’s guest on Analysts Assemble, Analytical Consultant and Project Manager Martin Weiss. We dig into Martin’s path into the data world and see how he uses his marketing and business prowess, along with his technical skills, to help Google’s advertising clients.

1) Tell us a bit about yourself, how did you get into the data space and what does your data journey look like so far?

My name is Martin Weiss and I am an Analytical Consultant at Google in Hamburg, Germany. My role is a mix between a classic marketing/sales analyst and an internal consultant or project manager. As such I work on internal projects as well as directly with Google’s advertising clients helping them with custom data analysis as well as building tools and dashboards for them. Another major part of the job is internal and external data education teaching data savviness to all stakeholders.

I would say my data journey is quite typical. It started during the last year of my studies (Business Administration and Economics) when I worked as Business Analyst for now one of the most successful German ecommerce startup. I got hooked on the online marketing and entrepreneurship world and loved the open non-hierarchical startup and tech industry culture.

After graduation I wanted to stay in that culture but also wanted to start at a larger company for my first real role. That’s when I applied at Google. At least in Europe the entry job there is usually as Google Ads consultant for small businesses and startups. The position allowed me to build a really strong background in PPC and online marketing overall as well as to get insights into literally hundreds of client businesses and their needs.

During my time in that role I always had some projects with a more analytical focus. This helped me to build an internal portfolio of projects which I used to transfer into my current position as an Analytical Consultant.

As a side project I also work on AnalyticalMarketer.io, my personal blog writing beginner level technical guides and career advice for marketing analytics.

2) What’s a typical day look like for you in your current data role? Which tools and languages do you use? Big team/small team/lone wolf? Remote/office based/co-working space?

I work in a 8 member team at the German Google headquarter office. Our team is part of a larger organization inside Google and acts as internal consultants for the teams managing Google’s advertising clients. As such our projects are incredibly diverse and we can choose projects depending on our personal strengths and interests. I am very happy and thankful to be on that team as it allows me to build up the technical and other skills I am interested in.

We have an internal BI suite, which we use for building dashboards, data pipelines etc. For languages SQL is my daily bread. I recently picked up some JavaScript, which I use for building some simple apps and tools.

Since our projects are so diverse, it’s hard to say what a typical day looks like, but it could be something like this: First thing in the morning I check my emails and get up-to-date on anything, that happened after I left the day before.

Next I re-prioritize my projects and to-dos for the day from that input. Afterwards I start working on a dashboard I have to build for one of our clients only to realize that the SQL query I started running the night before had some errors in it and has to be re-run. Which means I can’t work on the dashboard until late afternoon.

Instead I work on a search query forecasting tool and spend half of my time there googling simple stuff as I am a complete JavaScript rookie. My afternoon starts with a quick email check and a meeting on how we can include machine learning applications better into our day-to-day job.

Afterwards I work on a client insights workshop I am going to facilitate next week before I can finally finish that dashboard from the morning.

3) You’ve been building up a good following through some excellent guides and tutorials on your blog. How important do you think it is for data professionals, at all stages of their career, to share publicly what they are doing and learning?

I think other professionals are doing this already a lot more. It seem data professionals are a little bit behind on this. I am not sure why though. Maybe because there are not as many freelancers in this area? I am also not sure how important it is. However what I do know is that there is definitely no harm to it and that it makes a lot of things in your career easier.

Being publicly known will open a lot of new doors for you. No matter, if you are employed and especially not if you are self-employed. As I am just getting started with my blog I am not sure how beneficial it really will be in the end. But hopefully it will provide a valid second professional pillar for me at some point.

4) Where do you see your own data career going next? Building on your technical skills or moving into a more management-based role?

Surprisingly probably neither. I am not really seeking to move into a corporate management role. And even though I definitely want to keep improving my technical skills I don’t want to become a data engineer.

I believe that our world and especially marketing is becoming more and more data driven. And data savviness is becoming a must have skill. As such I want to move more into educational roles teaching others data skills. A common challenge I see among marketers and businesses is that they feel helpless looking at all their data. They know, where to (technically) get the data from, but have problems drawing insights from it and translating it into next steps.

That’s the angle I want to take, teaching them how to use that data for actionable insights and for planning steps to grow their business. My current vehicle for that is AnalyticalMarketer.io, but I am thinking to put more focus on it in my day job as well.

5) If you had a list of “best-kept-secrets” (websites, books, coaches) that have helped you, which would you recommend?

I have been very lucky, since Google has so many internal resources and courses to learn. So that’s where I usually go, when I want to learn something completely new. Externally (even though technically he also works at Google 😉 ) kaushik.net is probably my number one source for new analytical content.

As for “best-kept-secrets” I would say don’t be shy to google something! I guess for 95% of the technical challenges you are facing everyday somebody else had the same problem or something similar. Searching for your problem online will at least give you starting points to try out.

6) What is the number one piece of advice you give to aspiring data analysts?

Focus on analysis and insights rather than reporting. A mistake I see a lot of analysts make is to only focus on the reporting side of the job. So e.g. building dashboards or “data dumping” onto slides without any deeper analysis. But that’s where the real value of an analyst sits. Not only providing the data by rather drawing actionable insights and recommending next steps based on that data.

I think this will become more important in the future as on the one hand more and more data will be available and on the other hand a lot of the more technical aspects of the job will become automated (e.g. pulling the data). As such in order to provide value as analyst you will also have to know the business side quite well and provide actionable insights by combining the data and business world.

So in order to stand out be sure to be awesome not only at drawing actionable insights from data but also at visualizing and communicating recommendations to other stakeholders.

7) Where can readers find you online?

AnalyticalMarketer.io for all my content and consulting services, @the_mmw on Twitter.

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