The “Llamazing Data” podcast first aired on the June 4th, 2020. Brief episodes in edutainment style are aired every fortnight and are aimed at bringing knowledge about how professionals from various fields are facing similar data-based problems.
Every second Thursday a new story is presented, and the guests of the show are sharing their stories and experience in making data-driven decisions. A traditional 1-minute-long-quiz is always there closer to the end of the episode – to challenge our speakers in their expertise. No hard feelings 🙂
Tune in to hear some great stories and make sure to subscribe to not miss a thing!
- Season 2 – Internet of Things (IoT)
- Season 1 – Artificial Intelligence (AI)
- Episode 12 – Talented Mr. Machine: Data-Driven Optimizations And Machine Learning Implementation
- Episode 11 – No Gibberish For This Table: Simultaneous Interpretation And AI-Based Translators
- Episode 10 – Talk Ex-Machina To Me: Natural Language Processing (NLP) And AI In Speech Recognition
- Episode 09 – Kseniya’s Reading Room: Alan Turing – Computing Machinery And Intelligence (1950)
- Episode 08 – All Of Those Things: Data Usage And AI In Product Management
- Episode 07 – Once Upon A Time: AI In Storytelling And Data-Driven Reader Experience
- Episode 06 – Academia Has Entered The Building: Data Science And AI-Based Products
- Episode 05 – Catching The Curl: Data And AI In Traditionally Manual Business
- Episode 04 – We Mean Business: Data-Driven Enterprise Analytics And Consulting
- Episode 03 – Fourth Estate On AI-Wheels: Data Usage And Digitalization In Journalism
- Episode 02 – Live, And Learn, And Automate: Data-Driven Education And Supplement Learning
- Episode 01 – Cinderella’s Best Shoes: Hyper-Personalization In Data-Driven Product Design
Season 2 – Internet of Things (IoT)
Episode 01 – In the Beholder’s Eyes: Data Visualization in IoT

In the premiere episode in the renewed season of “Llamazing Data” podcast we’re talking with Manuel Lima, Design and Visual Culture leading specialist, about how data can be interpreted, how IoT-based products are benefiting from data and where is the limit (if there is one?) of the useful data’s capabilities.