Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering dat...
230: The Cynical Data Guy: Data Tech Debt, Data Mesh, and Dashboard Directives
Highlights from this week’s conversation include:The Return of the Cynical Data Guy (0:14)Risks of SQL Complexity (2:16)Technical Debt in Data (4:34)Data Mesh Critique (6:38)Governance vs. Decentralization (9:55)Never Let a Stakeholder Tell You They Need a Dashboard (12:05)Dashboard vs. Table (13:34)Organizational Dynamics in Data Requests (16:35)AI and Prompt Writing (19:43)Search Techniques and User Behavior (21:20)Discussion on Code Optimization Tools (23:19)Final Thoughts and Takeaways (24:47)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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229: The Future of AI: Superhuman Intelligence, Autonomous Coding, and the Path to AGI with Misha Laskin of ReflectionAI
Highlights from this week’s conversation include:Misha's Background and Journey in AI (1:13)Childhood Interest in Physics (4:43)Future of AI and Human Interaction (7:09)AI's Transformative Nature (10:12)Superhuman Intelligence in AI (12:44)Clarifying AGI and Superhuman Intelligence (15:48)Understanding AGI (18:12)Counterintuitive Intelligence (22:06)Reflection's Mission (25:00)Focus on Autonomous Coding (29:18)Future of Automation (34:00)Geofencing in Coding (38:01)Challenges of Autonomous Coding (40:46)Evaluations in AI Projects (43:27)Example of Evaluation Metrics (46:52)Starting with AI Tools and Final Takeaways (50:35)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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The PRQL: From Theoretical Physics to AI: Misha Laskin on AGI, Superhuman Intelligence, and Autonomous Coding
The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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228: The Machine Learning Reality Check: When AI Makes Sense for Marketing Attribution with Lew Dawson of Momentum Consulting
Highlights from this week’s conversation include:Previewing Today’s Topic (0:14Machine Learning Discussion (1:44)Conditions for Machine Learning Worthiness (6:59)Simplicity in Modeling (8:43)Predictive Analytics vs. Machine Learning (10:42)Optimization and Investment Problems (13:03)Practical vs. Theoretical Saturation (15:16)Building Relationships with Marketing Teams (19:52)Reporting Metrics and Attribution Models (22:49)Tracking Common Metrics (25:40)Understanding Profit Generation (27:46)ROI Calculation Challenges (29:49)AI in Customer Data Analysis (31:23)Execution Challenges in Marketing Automation (35:23)API Limitations in Marketing Tools (36:50)Optimizing Ads with AI (37:50)Challenges of Real-Time Data Integration (40:01)Final thoughts and takeaways (41:13)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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227: The Art & Science of Marketing Attribution: From UTMs to Machine Learning with Lew Dawson of Momentum Consulting
Highlights from this week’s conversation include:Welcome Back, Lew (0:14)Recap of Previous Discussion (1:03)Benefits of Hashing Information (2:33) Using Hashes for Data Context (4:24)Hashing and Query Parameters (7:24)Static Values for Hashing (11:10)Identity Resolution in Data Attribution (14:36)Methodologies for User Tracking (16:37)Combining Data Sources for Attribution (21:13)Understanding Data Gaps (25:25)Defining Objectives and KPIs (27:50)Identity Resolution Challenges (28:46)User and Session Stitching (32:01)Trusting Ad Platforms (35:23)Defining Attribution (38:09)The Credit Dilemma (40:18)First Touch Attribution Explained (41:47)Linear Attribution Model (43:21)B2C and B2B Attribution Scenarios (45:22)Timeframes in Attribution (47:29)Understanding Lookback Windows (49:34)Google Analytics Changes (51:20)Attribution After Conversion (53:26)Online vs. Offline Attribution (55:49)Discipline in Tracking (58:52)Challenges in Coordination (1:00:12)QR Codes and Data Integration (1:01:55)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
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