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Episode 30:

The DataStack Journey with Rachel Bradley-Haas and Alex Dovenmuehle of Big Time Data

March 24, 2021

On this week’s episode of The Data Stack Show, Eric and Kostas are joined by the co-founders of Big Time Data, Rachel Bradley-Haas and Alex Dovenmuehle, formerly of Mattermost and prior to that, Heroku. At Big Time Data, they work together to provide companies with the ability to derive value and insights from decentralized datasets, improve business processes through data enrichment and automation, and build a scalable foundation to enable a data-driven culture.

Notes:

Highlights from this week’s episode include:

  • Rachel and Alex’s background and their goal to make data approachable for companies everywhere (3:09)
  • The data stack journey: making decisions when you’re small that allow you to grow with your data and your organization (12:28)
  • The problems faced when a data stack isn’t nurtured early on (15:59)
  • Changes in data stack technology (21:32)
  • How Alex and Rachel’s roles at Big Time Data differ and interact with each other (39:00)
  • Client use cases (43:34)
  • Comparing the stacks of seed stage startups, mid-sized companies and giant enterprises (48:54)

The Data Stack Show is a weekly podcast powered by RudderStack. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

About the Podcast

Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

To keep up to date with our future episodes, subscribe to our podcast on Apple, Spotify, Google, or the player of your choice.

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