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Data Journey: This Missing Piece
We live in a complex, chaotic world as data professionals:
- The Modern Data Stack is too complex.
- New cloud data toolchains are fragmented.
- Data architecture patterns are diverse and complicated.
- Data itself, of course, is diverse, numerous, and forever changing.
- And the step-by-step process of ingesting, storing, transforming, predicting, visualizing, and governing data is spread among various people in your organization.
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.’
Specifically, Chris covered the following:
- What is a Data Journey?
- The pain and problems caused by not having the artifact in your organization
- How a Data Journey provides a layer of run time expectations that ensure problems are caught before your customers find embarrassing errors.
- How a Data Journey goes across all your tools and down into the technology stack to actively identify the problem source.
- How DataOps Observability allows you to quickly create, monitor, and alert on all the myriad of Data Journies in your organization.