About Data User Experience
            Maybe we have ignored this for too long
        
        
     
        
                        
    
        
    
        Quo vadis, Data Open source
            A case study and review based on the examples of Snowplow, dbt, Rudderstack, and Iceberg
        
        
     
        
                        
    
        
    
        After the Modern Data Stack: Welcome back, Data platforms
            And no, there is no one way to what is next, we have 1000+ of ways.
        
        
     
        
                        
    
        
    
        Use feature analytics for better products
            We are not building something for the fun here
        
        
     
        
                        
    
        
    
        What is beyond event data?
            When Data Events are iron, Activities are your steel-building parts.
        
        
     
        
                        
    
        
    
        The Go-To Metrics for Data Products: Start with These Few
            We are talking about data products, so of course we should speak about metrics
        
        
     
        
                        
    
        
    
        Leaving product analytics
            an analysis of the current state of product analytics and beyond
        
        
     
        
                        
    
        
    
        The extensive guide for Server-Side Tracking
            Take control where you create your event data
        
        
     
        
                        
    
        
    
        Ways to solve the data user identity & privacy crisis
            Why we should think beyond using user ids for everything
        
        
     
        
                        
    
        
    
        Here is your stack of salt for reading or watching data content
            You will need more than just a few grains
        
        
     
        
                        
    
        
    
        Tracking/Measurement/Collection/Creation - what was the question again?
            Trying to define something that needs definition but has a history that can't be changed easily.
        
        
     
        
                        
    
        
    
        Retention Analytics - the definitive guide
            There just one thing to learn in product analytics - unfortunately it takes a bit
        
        
     
        
                        
    
        
    
        Why product analytics is completely different than BI
            When explorers meet structured formats
        
        
     
        
                        
    
        
    
        More than 30 unique tracking events will cause you problems
            The easiest way to increase data adoption, productivity and decrease quality problems
        
        
     
        
                        
    
        
    
        The data’s trojan horse
            There is a way to talk to other business teams
        
        
     
        
                        
    
        
    
        Sometimes, you need to say: screw it
            Or: The return of the hipster data stack