Today

958: Without Trusted Context, Agents are Stupid (featuring Salesforce’s Rahul Auradkar)

In this #sponsored Feature Friday episode, Salesforce’s Rahul Auradkar speaks to Jon Krohn about the company’s unified data engine and how its acquisition of Informatica provides the missing context layer for AI models and agents. Hear how Salesforce’s Data 360 helps customers to ... Show More

23m 59s

Jan 13

957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva

AI agents, data lakes, and managing data sprawl: Ashwin Rajeeva, cofounder and CTO of Acceldata, speaks to Jon Krohn about how the agentic data management startup raised over $100 million in venture capital to expand its business in automating data quality assurance as well as ca ... Show More

59m 36s

Jan 9

956: From Agent Demo to Enterprise Product (with Ease!) feat. Salesforce’s Tyler Carlson

#Sponsored SVP, Head of Product for Salesforce’s AppExchange & Ecosystem, Tyler Carlson, talks to Jon Krohn about taking AI agents from prototype to enterprise-grade production with the Agentforce 360 Platform. Though we may now have plenty of tools to build demos for AI agents, ... Show More

26m 28s

Aug 2021

Data Discovery From Dashboards To Databases With Castor

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Every organization needs to be able to use data to answer questions about their business. The trouble is that the data is usually spread across a wide and shifting array of systems, from databases to dashboards. The othe ... Show More

52m 47s

Mar 2022

Bayesian Machine Learning with Ravin Kumar (Ep. 191)

<p>This is one episode where passion for math, statistics and computers are merged. I have a very interesting conversation with Ravin, data scientist at Google where he uses data to inform decisions.</p> <p>He has previously worked at Sweetgreen, designing systems that would b ... Show More

31m 12s

Mar 2020

What exactly is "data science" these days? (Practical AI #80)

Matt Brems from General Assembly joins us to explain what "data science" actually means these days and how that has changed over time. He also gives us some insight into how people are going about data science education, how AI fits into the data science workflow, and how to diff ... Show More

48m 40s

Aug 2022

Collecting And Retaining Contextual Metadata For Powerful And Effective Data Discovery

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Data is useless if it isn’t being used, and you can’t use it if you don’t know where it is. Data catalogs were the first solution to this problem, but they are only helpful if you know what you are look ... Show More

53m 24s

Apr 2024

Establish A Single Source Of Truth For Your Data Consumers With A Semantic Layer

<h2>Summary</h2> <p>Maintaining a single source of truth for your data is the biggest challenge in data engineering. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. In order to enable this use case, while mainta ... Show More

56m 23s

Mar 2024

When And How To Conduct An AI Program

<h2>Summary</h2> <p>Artificial intelligence technologies promise to revolutionize business and produce new sources of value. In order to make those promises a reality there is a substantial amount of strategy and investment required. Colleen Tartow has worked across all stages ... Show More

46m 25s

Jan 2022

Academics and Data Science Innovation with Dr. David Bader, Distinguished Professor and Director, Institute for Data Science, New Jersey Institute of Technology

<p>The data science field is expanding because so many businesses and other institutions require skilled workers who can manage data as well as provide insights. Companies and students are clamoring for more academic programs. There is great need, but academic institutions are st ... Show More

39m 32s

Apr 2021

You are the product [RB] (Ep. 147)

In this episode I am with George Hosu from <a href='https://cerebralab.com'>Cerebralab</a> and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not. Our Sponsors <p>Thi ... Show More

45m 4s

Mar 2024

Adding Anomaly Detection And Observability To Your dbt Projects Is Elementary

<h2>Summary</h2> <p>Working with data is a complicated process, with numerous chances for something to go wrong. Identifying and accounting for those errors is a critical piece of building trust in the organization that your data is accurate and up to date. While there are num ... Show More

50m 44s

263: Communicating Data