TMW Case Study #004 | Building a better data foundation by HP
Release Date: 11/19/2024
TMW Case Study #004 | Building a better data foundation by HP
Making Sense of Martech
From third-party to first-party: Building a better data foundation
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info_outlineFrom third-party to first-party: Building a better data foundation
What do you think of when I say “tech start-up?” Those words probably conjure up thoughts of a small team working out of the founder’s garage somewhere in Palo Alto, Sunnyvale, or Cupertino. The reason that image springs to mind is because that is how a bunch of the biggest and most influential tech companies started out over the years. But who started this trend?
Well, it’s not a plucky start-up anymore, but the answer is Hewlett Packard. Way back in 1939, Bill Hewlett and David Packard founded HP in a one-car garage at 367 Addison Avenue, Palo Alto, which is now adorned with a plaque reading: The Birthplace of Silicon Valley. A lot has changed since then: Far from their fledgling days when they produced audio oscillators (which Disney used to test the sound equipment for the movie ‘Fantasia’!), HP is now a multinational IT mainstay.
The original HP split into two companies in 2015: Hewlett Packard Enterprise for enterprise products and services, and HP Inc for its personal computer and printer business. The split between its B2B and B2C customers was reflected in its data architecture. Like many legacy businesses, HP found itself in a situation where it had separate platforms and data stores for commercial and consumer data managed by a plethora of different stakeholders, leading to a severely siloed data landscape.
Over the last few years, HP has overcome these challenges by bringing together its fractured data landscape into a modern, composable data architecture befitting its history as the origin of the Silicon Valley mythology. To understand how HP went about this transformation, The Martech Weekly sat down with Kumar Ram, Global Head of Marketing Data Sciences, and Luis Alonzo, Head of Customer Data Strategy and Engineering.
Kumar and Luis’s responses have been edited for clarity and congruency.