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Michael O'Connell, Chief analytics officer, TIBCO Software

Path to power

 

I was intrigued by maths and music from an early age. I recall being able to divide any four-digit number into any other number before starting school and having to leave the dinner table to uncontrollably shake to Kinks songs on the radio. I did undergraduate and Master’s Mathematics and Statistics in Sydney, Australia, and a PhD in Statistics at NC State in the US. Upon graduation, I worked in R&D for a medical device company as part of a knowledge-based systems (KBS) and statistics innovation team. We created new products with DNA-amplification diagnostics, transdermal drug delivery and bacterial identification and susceptibility testing product platforms, using expert system rules and machine learning models. I became interested in business, started some companies in the early days of the internet, and landed at TIBCO through some analytics acquisitions. 
I started an industry analytics practice and then a data science and innovation team at TIBCO. My work includes making our products smarter and easier to use with AI technologies and helping our customers and community to accelerate their analytics journey with software applications across many business sectors.

 

What has been the highlight of your career in the industry to date?

 

I’m most excited with our recent work, developing innovative analytic applications featuring models from historical data that we apply to new data and event streams, using batch and real-time scoring engines to optimise business operations. Bringing such continuous learning systems into hybrid cloud environments has been particularly satisfying, using our own connected intelligence cloud analytics and data science products, along with AWS, GCP and Azure data management, compute and data science functionality. Our analytic apps, like anomaly detection and customer engagement, feature innovation in data access, feature engineering, visual analytics, data science, event processing and case management. The innovation work has been really fun. Over the years, it’s been satisfying to develop product and technology applications using TIBCO data science and analytics software with our customers and partners, and how these drive practical business value across many vertical sectors. I’ve worked on applications in life sciences discovery, clinical and healthcare applications, financial services, the energy sector, telecommunications, retail and consumer goods, manufacturing, transportation, travel and logistics.  It’s been really fun to learn so much about these businesses and to help address some of their challenges. I feel especially fortunate to have created such extreme value with product and technology innovations, and analytics apps, in the life sciences, energy and high-tech manufacturing sectors.

 

If you could give your younger self some advice about how to progress in this industry, what would it be?

 

Do even more coding than I did and go beyond maths and stats. The time I was working with CGI bin scripts and webapps on my SPARCstation - do more of that. Integrate more data systems, do more feature engineering and ETL. Exercise more APIs. Do more of everything related to the analytics lifecycle - data access, prep, dataviz, apps, deployments. Be even hungrier to learn it all. Be more humble and grateful. Smell the roses. Do more music, learn more piano. Do more cardio, be kinder to my body. 
Think bigger in setting business and technology goals. Buy more stocks in companies that I used along the way - why didn’t I load up on Apple stock when I used Apple stuff so much and so early on?The work we did in hybrid cloud environments and augmented analytics with our products, eg, with AI recommendation systems, auto-ML and cloud applications was way beyond what I expected at the start of the year. We built several TIBCO connected intelligence cloud starter apps for our customers and community, using machine learning models-as-a-service, embedded in low code business process flows. We addressed broad functional areas, including risk management, anomaly detection, condition-based maintenance and customer engagement. We presented some of this work at the AWS Re:Invent conference. This was amazing - 5,000-plus people saw our work at the TIBCO booth, in our presentations and demo sessions, while 50,000-plus people attended the conference. Spotfire X was released with our AI recommendations engine in November. Awesome.

 

What do you expect 2019 to be like for the industry?

 

As we move into 2019, continued interest in AI/ML and cloud compute will drive more investment in analytic apps and systems of insight from interconnecting data through visual and predictive analytics. In parallel, democratising data science and analytics into the hands of business users and BI systems will continue to grow. Gartner is calling this augmented analytics - the third wave of BI and analytics and the “future of analytics”. 2019 will be more hybrid cloud, more analytic apps. AWS is a juggernaut and GCP and Azure are on the up. Real-time AI and model management will play an increasingly important role in the hybrid cloud environment.

 

Talent and skills are always a challenge to find - how are you tackling this in your organisation?

 

We have internal and external recruiters and open positions. We do hackathons and hands-on workshops. We keep an eye on our customers and partners - we don’t poach, but when someone is hungry, switched-on, and wants to work more with our technology, then we are there. We look after our employees. We have the coolest analytics portfolio on the planet and we have a lot of fun partying with our software and industry data from many sectors.

 

What aspect of data, analytics or their use are you most optimistic about and why?

 

I’m optimistic about augmented analytics, auto-ML and recommender systems making analytics more prevalent and democratising data science across broad sets of users. Along with this increased analytics awareness, I’m optimistic about analytics for social good. Analytics helping people, communities and the social fabric. Our work with the non-profit Tipping Point in easing the burden on low-income drivers has been satisfying in this regard. This data science work has directly resulted in new reforms by the San Francisco Municipal Transportation Agency (SFMTA) which has “allowed low-income families with outstanding debt to forgo late fees (on parking fines) and pay the remaining citation fees through a reduced low-fee payment plan, or use a community service programme.”Data and analytics technology/service provider
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