Season 9, Episode 6 - Steve Butler, North America Leader - Analytics, Insights, and Automation, Philips

·30 min·2 clips

Steve Butler says nobody is really paying people to do dashboards anymore.

1. Data Science Perspectives features Bill Franks talking with Steve Butler about a career in analytics, insights, and automation at Philips North America. 2. Bill Franks introduces Butler as the North American leader for analytics, insights, and automation at Philips, with prior roles at Slalom, Deloitte, Teradata, Asurion, and Anderson Consulting. 3. The episode asks how Butler moved into analytics, what has changed across data warehousing, big data, cloud, and AI, and what skills still matter. 4. Butler says his path into analytics was happenstance, starting after his MBA at Anderson Consulting, now Accenture, where he was trained as a programmer and consultant. 5. He describes a marketing analyst role at a wireless phone company that needed someone who could query databases, procure data, curate data, and build models and reports. 6. Butler says he used SQL access to data and ended up running the database marketing team at headquarters after beginning in an analyst pod. 7. Bill Franks notes that telcos such as AT&T were early adopters of analytics at scale because billing systems created customer databases. 8. Butler recalls an Oracle data warehouse, 7 a.m. query runs, and waiting for the batch window to close at night. 9. He says migrating to a more scalable platform made it possible to iterate through data many times in a day and improve analytics maturity. 10. Butler argues that infrastructure still matters in cloud analytics because great analytics depends on managing the platform well. 11. He says cloud systems increase speed, let teams spin infrastructure up and down, and make it easier to add GPUs when needed. 12. Butler supports agile frameworks in data and analytics because they help teams collaborate faster and keep pace with the infrastructure. 13. He says data curation still takes time because analysts must integrate data properly and avoid false positives. 14. Butler says consulting offers variety across sectors and functions, while data analytics skills travel well between consulting and corporate roles. 15. He says corporate roles let him invest in developing others, while consulting often feels like helicoptering in and out. 16. Butler says he now uses his experience at Philips to see how healthcare analytics differs from telecommunications and media. 17. In healthcare and life sciences, Butler says the mission is patient outcomes, and analytics must support safety, quality, and efficiency. 18. He points to image recognition for x-ray, MRI, and CT products, along with FDA review and peer review before AI can be applied. 19. Butler says he still enjoys solving problems, going to the office, and using whiteboards with peers to work through hard questions. 20. He predicts ontology, knowledge graphs, and sector-specific language models will be a major growth area for the next 3 to 5 years.

Listen to the show on

Apple Podcasts Spotify

Play clips from this episode More from Data Science Perspectives