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David Sweenor, Senior Director, Portfolio Marketing, Alteryx

Describe your career to date

First dabbling with machine learning (ML) during college, I co-oped for a small research company who specialized in artificial neural networks. My big project was to analyze biometric data which led to a couple of scientific papers on predicting mortality using neural networks.  

 

Post-college, I worked for IBM Microelectronics as a yield characterization engineer. This meant that I had to apply analytics and data science to try and understand why semiconductor yields were not high enough. If you’re not familiar with semiconductors, a wafer can go through 1200 different process steps and take from between three to six months to build. I had data of every type – electrical, measurement, optical, text, spatial, logistics, test… you name it. It was a great way to learn data science. After that, I moved from complaining about data systems… straight to the source. I joined the data warehousing team to try and fix those systems myself. Five years later, I ended up working in IBM’s business analytics center of competency. 

 

After spending over a decade at IBM, I turned to the dark side of marketing. I’ve worked for many household-name data and analytics companies and, in my current role at Alteryx, I am responsible for GTM strategy for the analytics, data science and machine learning as part of the portfolio marketing team. 

 

Additionally, I have published six books on analytics, with the most recent being a TinyTechGuide titled Artificial Intelligence: An Executive Guide to Make AI Work for Your Business. 

What stage has your organization reached on its data maturity journey?

Being the analytics automation company, Alteryx is quite sophisticated with data and analytics. Out of a 5-point scale, we’re probably a high 3 or close to a 4. The average maturity score across all companies is a 2.2 so that’s a great score. 

 

Tell us about the data and analytics resources you are responsible for

Being a portfolio marketing leader, I have about ten talented individuals working under me. These experts are distributed throughout the world and it is our responsibility to tell the Alteryx story – analytics for all – in a way that resonates globally. We regularly work with customers to help them automate analytics and to understand that analytics should not only be accessible to all employees, which should also encompass all systems and inform all decisions. The power of analytics is transformative – but many companies just need a little activation energy to get started. 

What challenges do you see for data in the year ahead that will have an impact on your organization and on the industry as a whole? 

With economic headwinds, geopolitical instability and constricted supply chains, this year promises to be full of surprises. It is more important than ever for organizations to double down on analytics automation. If you look at some of the research from previous downturns, the companies who invest in analytics and upskilling their employees at the beginning of a crisis are the same ones that become market leaders in their category in the months after. If you deprioritize your investments in data, analytics and people…you’re likely to struggle. 

 

Have you set out a vision for data? If so, what is it aiming for and does it embrace the whole organization or just the data function?

Our vision is that analytics is for all. No matter your skill level, analytics is for you. Alteryx powers analytics for all by providing the leading platform to automate analytics across all systems and decisions. Alteryx delivers easy end-to-end automation of data engineering, analytics, reporting, automated machine learning, geospatial analytics and automated insight generation, enabling enterprises everywhere to democratize data analytics across their organizations for a broad range of use cases. More than 8,400 customers globally rely on Alteryx to deliver intelligent decisions at scale.

 

Have you been able to fix the data foundations of your organization, particularly with regard to data quality?

Absolutely, without a solid foundation of easily accessible and quality data, analytics cannot really happen. Alteryx recently acquired a company which meant we had to work very diligently to merge and combine data from the acquisition. This included ensuring we had common data definitions, systems and processes. You can imagine the amount of data marketers use – but I’m happy to say, the team completed this in record time. 

David Sweenor
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