DataKitchen Demo: The Data Journey That Leads to Quality and Observability At Scale

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Data leaders live daily with complexity and chaos and are crushed by potential tasks.

  • The ‘Modern’ Data Stack is full of shiny new boxes of technology.
  • New cloud data toolchains are fragmented.
  • Data architecture patterns are diverse and complicated.
  • Data itself, of course, is diverse, numerous, and forever changing.
  • The step-by-step process of ingesting, storing, transforming, predicting, visualizing, and governing data is spread among various people in your organization.
  • And your customers are asking for all sorts of new work.
  • Is there any question about why your day-to-day job is chaotic and stressful? Or that you live in a state of hope and dread that, somewhere in the journey data takes from source to value, suddenly, everything will break, and you will be the last to notice?

Something is missing from our data systems. We cannot judge the expectations vs. reality in our production data systems. What is the variance between what is happening now and what should be happening? Is it on time? Late? Is it trustworthy? What is happening now? Will my customers find a problem? That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It starts with your data and leads to quality, trusted, on-time insight delivery to your customers. Data Observability and Data Quality Validation Testing are the core components that comprise the myriad of Data Journies in Your Organization.