The Life of Metric: An MVP approach to data

hdahme

The revolution was televised. Static webpages became a thing of the past, and as the content became more dynamic, so too did the technology behind it. Less noticeably though, there was a shift in the mindset of developers; waterfall development fell out of favour, and agile development awakened to its golden day.

This mental shift has yet to happen in the realm of data analytics and science though. At both a macro and micro level, we have yet to accept that limited visibility doesn’t necessarily imply being lost. Models don’t need to be perfect, and business strategies don’t need to be definite and long-term. Many of the lessons that we’ve learned from agile software development can be applied to data analysis, not to mention businesses as a whole.

In this session, we’re going to talk about those strategies, as well as how to actually build a data pipeline in an agile fashion, with lessons pulled from the trenches of Pantheon amongst others. We’ll discuss:

  • How to determine what to measure

  • Infrastructure impacts

  • Content considerations

  • Human considerations when measuring

  • Why incomplete and agile will always outperform a complete monolith

Register NOW

Session Track

Business

Experience Level

Intermediate

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