Francisco was born in Quito, Ecuador, and at age 13, came to the US to live with his father in Miami, Florida. He studied Marketing at Saint Thomas University, and his skills in math landed him a job as Teaching Assistant for Statistics & Calculus. After graduation, his professional career began at some nation’s leading ad agencies before he eventually transitioned into the ad tech space. In 2016, he ventured into the entrepreneurial world and founded Direcly, a Google Marketing Platform, Google Cloud, and Looker Sales/Consulting partner obsessed with using innovative technological solutions to solve business challenges. Against many odds and with no external funding since its inception, Direcly became a part of a selected group of Google Cloud and Google Marketing Platform partners. Francisco’s story was even featured in a Forbes Ecuador article!
Outside of the office, Francisco is an avid comic book reader/collector, a golfer, and fantasy adventure book reader. His favorite comic book is The Amazing Spider-Man #252, and his favorite book is The Hobbit. He says he isn’t the best golfer, but can ride the cart like a pro.
When were you introduced to the cloud, tech, or data field? What made you pursue this in your career?
I began my career in marketing/advertising, and I was quickly drawn to the tech/data space, seeing the critical role it played. I’ve always been fascinated by technology and how fast it evolves. My skills in math and tech ended up being a good combination.
I began learning some open source solutions like Hadoop, Spark, and MySQL for fun and started to apply them in roles I had throughout my career. After my time in the ad agency world, I transitioned into the ad tech industry, where I was introduced to how cloud solutions were powering ad tech solutions like demand side, data management, and supply side platforms.
I’m the type of person that can get easily bored doing the same thing day in and day out, so I pursued a career in data/tech because it’s always evolving. As a result, it forces you to evolve with it. I love the feeling of starting something from scratch and slowly mastering a skill.
What courses, studies, degrees, or certifications were instrumental to your progression and success in the field? In your opinion, what data skills or competencies should data practitioners be focusing on acquiring to be successful in 2022 and why?
My foundation in math, calculus, and statistics was instrumental for me. Learning at my own pace and getting to know the open source solutions was a plus. What I love about Google is that it provides you with an abundance of resources and information to get started, become proficient, and master skills. Coursera is a great place to get familiar with Google Cloud and prepare for certifications. Quests in Qwiklabs are probably one of my favorite ways of learning because you actually have to put in the work and experience first hand what it’s like to use Google Cloud solutions. Lastly, I would also say that just going to the Google Cloud internal documentation and spending some time reading and getting familiar with all the use cases can make a huge difference.
For those who want to acquire the right skills I would suggest starting with the fundamentals. Before jumping into Google Cloud, make sure you have a good understanding of Python, SQL, data, and some popular open sources. From there, start mastering Google Cloud by firstly learning the fundamentals and then putting things into practice with Labs. Obtain a professional certification — it can be quite challenging but it is rewarding once you’ve earned it. If possible, add more dimension to your data expertise by studying real life applications with an industry that you are passionate about.
I am fortunate to be a Google Cloud Certified Professional Data Engineer and hold certifications in Looker, Google Analytics, Tag Manager, Display and Video 360, Campaign Manager 360, Search Ads 360, and Google Ads. I am also currently working to obtain my Google Cloud Machine Learning Engineer Certification. Combining data applications with analytics and marketing has proven instrumental throughout my career. The ultimate skill is not knowledge or competency in a specific topic, but the ability to have a varied range of abilities and views in order to solve complicated challenges.
You’re no doubt a thought leader in the field. What drew you to Google Cloud? How have you given back to your community with your Google Cloud learnings?
Google Cloud solutions are highly distributed, allowing companies to use the same resources an organization like Google uses internally, but for their own business needs. With Google being a clear leader in the analytics/marketing space, the possibilities and applications are endless. As a Google Marketing Platform Partner and having worked with the various ad tech stacks Google has to offer, merging Google Cloud and GMP for disruptive outcomes and solutions is really exciting.
I consider myself to be a very fortunate person, who came from a developing country, and was given amazing opportunities from both an educational and career standpoint. I have always wanted to give back in the form of teaching and creating opportunities, especially for Latinos / US Hispanics. Since 2018, I’ve partnered with Florida International University Honors College and Google to create industry relevant courses. I’ve had the privilege to co-create the curriculum and teach on quite a variety of topics. We introduced a class called Marketing for the 21st Century, which had a heavy emphasis on the Google Marketing Platform. Given its success, in 2020, we introduced Analytics for the 21st Century, where we incorporated key components of Google Cloud into the curriculum. Students were even fortunate enough to learn from Googlers like Rob Milks (Data Analytics Specialist) and Carlos Augusto (Customer Engineer).
What are 1-2 of your favorite projects you’ve done with Google Cloud’s data products?
My favorite project to date is the work we have done with Royal Caribbean International (RCI) and Roar Media. Back in 2018, we were able to transition RCI efforts from a fragmented ad tech stack into a consolidated one within the Google Marketing Platform. Moreover, we were able to centralize attribution across all the paid marketing channels. With the vast amount of data we were capturing (17+ markets), it was only logical to leverage Google Cloud solutions in the next step of our journey. We centralized all data sources in the warehouse and deployed business intelligence across business units.
The biggest challenge from the start was designing an architecture that would meet both business and technical requirements. We had to consider the best way to ingest data from several different sources, unify them, have the ability to transform data as needed, visualize it for decision makers, and set the foundations to apply machine learning. Having a deep expertise in marketing/analytics platforms combined with an understanding of data engineering helped me tremendously in leading the process, designing/implementing the ideal architecture, and being able to present end users with information that makes a difference in their daily jobs.
We utilized BigQuery as a centralized data warehouse to integrate all marketing sources (paid, organic, and research) though custom built pipelines. From there we created data driven dashboards within Looker, de-centralizing data and giving end users the ability to explore and answer key questions and make real time data driven business decisions. An evolution of this initiative has been able to go beyond marketing data and apply machine learning. We have created dashboards that look into covid trends, competitive pricing, SEO optimizations, and data feeds for dynamic ads. From the ML aspect, we have created predictive models on the revenue side, mixed marketing modeling, and applied machine learning to translate English language ads to over 17 languages leveraging historical data.
What are your favoriteGoogle Cloud data productswithin the data analytics, databases, and/or AI/ML categories? What use case(s) do you most focus on in your work? What stands out aboutGoogle Cloud’s offerings?
I am a big fan of BigQuery (BQ) and Looker. Traditional data warehouses are no match for the cloud – they’re not built to accommodate the exponential growth of today’s data and the sophisticated analytics required. BQ offers a fast, highly scalable, cost-effective and fully controlled cloud data warehouse for integrated machine learning analytics and the implementation of AI.
Looker on the other hand, is truly next generation BI. We all love Structured Query Language (SQL), but I think many of us have been in position of writing dense queries and forgetting how some aspects of the code work, experiencing the limited collaboration options, knowing that people write queries in different ways, and how difficult it can be to track changes in a query if you changed your mind on a measure. I love how Look ML solves all those challenges, and how it helps one reuse, control and separate SQL into building blocks. Not to mention, how easy it is to give end users with limited technical knowledge the ability to look at data on their terms.
What’s next for you?
I am really excited about everything we are doing at Direcly. We have come a long way, and I’m optimistic that we can go even further. Next for me is just to keep on working with a group of incredibly bright people who are obsessed with using innovative technological solutions to solve business challenges faced by other incredibly bright people.
From this story I would like to tell those that are pursuing a dream, that are looking to provide a better life for themselves and their loved ones, to do it, take risks, never stop learning, and put in the work. Things may or may not go your way, but keep persevering — you’ll be surprised with how it becomes more about the journey than the destination. And whether things don’t go as planned, or you have a lot of success, you will remember everything you’ve been through and how far you’ve come from where you started.
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