Datacast Episode 74: The Next Generation of Business Intelligence with Cindi Howson

Datacast Episode 74: The Next Generation of Business Intelligence with Cindi Howson

Cindi Howson, the Chief Data Strategy Officer at ThoughtSpot, is an analytics and Business Intelligence expert with more than 20 years of experience and a flair for bridging business needs with technology.

Cindi was previously the Vice President in data and analytics at Gartner, where she was the lead author of the Analytics and BI Magic Quadrant. Additionally, she led the data and analytics maturity model, as well as research initiatives in data and AI for good, NLP/BI Search, and augmented analytics.

Prior to this, she was the founder of BI Scorecard, a contributor to Information Week, and the author of several books, including (1) Successful Business Intelligence: Unlock the Value of BI & Big Data and (2) SAP BusinessObjects BI 4.0: The Complete Reference. She has an MBA from Rice University and a BA from the University of Maryland.

Datacast Episode 73: Datasets for Software 2.0 with Taivo Pungas

Datacast Episode 73: Datasets for Software 2.0 with Taivo Pungas

Taivo Pungas is a tech entrepreneur working on a stealth-mode startup. Previously, he built the AI team at Veriff from scratch to 20+ people and contributed to various ML/data roles at Starship and other Estonian startups. On the side, he advises startups and writes a blog at taivo.ai.

What I Learned From Attending Tecton apply(meetup) 2021

What I Learned From Attending Tecton apply(meetup) 2021

Last month, I attended apply(), Tecton’s follow-up virtual event of their ML data engineering conference series. I’ve previously written a recap of their inaugural event, a whirlwind tour of wide-ranging topics such as feature stores, ML platforms, and research on data engineering. In this shorter post, I would like to share content from the main talks and lightning talks presented at the community meetup. Topics include ML systems research, ML observability, streaming architecture, and more.

Datacast Episode 72: Folding Data with Gleb Mezhanskiy

Datacast Episode 72: Folding Data with Gleb Mezhanskiy

Gleb Mezhanskiy is the CEO & Co-founder of Datafold -  a data observability platform that helps companies unlock growth through more effective and reliable use of their analytical data. As a founding member of Data teams at Autodesk and Lyft and the Head of Product at Phantom Auto, Gleb has built some of the world's largest and most sophisticated data platforms and has developed tooling to improve productivity and data quality in organizations with hundreds of data users.

Datacast Episode 71: Trusted AI with Saishruthi Swaminathan

Datacast Episode 71: Trusted AI with Saishruthi Swaminathan

Saishruthi Swaminathan is an Advisory Data Scientist at IBM's AI Strategy and Innovation division. Previously, she was a technical lead and data scientist in the IBM Center for Open-Source Data and AI Technologies team, whose main focus is to democratize data and AI through open source technologies. She has a Master’s in Electrical Engineering that specializes in Data Science and a Bachelor's degree in Electronics and Instrumentation. Her passion is to dive deep into the ocean of data, extract insights, and use AI for social good.

Previously, she worked as a Software Developer on a mission to spread the knowledge and experience she acquired in her learning process. She also leads an initiative to bring education to rural children and organizes meetups that focus on women's empowerment.

Datacast Episode 70: Machine Learning Testing with Mohamed Elgendy

Datacast Episode 70: Machine Learning Testing with Mohamed Elgendy

Mohamed Elgendy is a seasoned AI expert, who has previously built and managed AI organizations at Amazon, Rakuten, Twilio, and Synapse. In particular, he founded and managed Amazon's computer vision think tank. He is the author of the "Deep Learning for Vision Systems" book published by Manning in November 2020. Mohamed regularly speaks at many AI conferences like Amazon's DevCon, O'Reilly's AI, and Google's I/O.

What I Learned From Attending MLOps World 2021

What I Learned From Attending MLOps World 2021

Two months ago, I attended the second edition of MLOps: Production and Engineering World, which is a multi-day virtual conference organized by the Toronto Machine Learning Society that explores the best practices, methodologies, and principles of effective MLOps. In this post, I would like to share content from the talks that I found most useful during this conference, broken down into Operational and Technical talks.

Datacast Episode 69: DataPrepOps, Active Learning, and Team Management with Jennifer Prendki

Datacast Episode 69: DataPrepOps, Active Learning, and Team Management with Jennifer Prendki

Dr. Jennifer Prendki is the founder and CEO of Alectio, the first startup fully focused on DataPrepOps. She and her team are on a fundamental mission to help ML teams build models with less data. Before Alectio, Jennifer was the Vice President of ML at Figure Eight. She also built an entire ML function from scratch at Atlassian and led multiple Data Science projects on the Search team at Walmart Labs. She is recognized as one of the top industry experts on Active Learning and ML lifecycle management. She is an accomplished speaker who enjoys addressing both technical and non-technical audiences.