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Innehåll tillhandahållet av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
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How to Leverage Data For Exponential Growth - Tarush Aggarwal

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Manage episode 297999651 series 2954151
Innehåll tillhandahållet av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

In this episode we are joined by an industry veteran who has worked for some of the biggest names in the enterprise Data world. Tarush Aggarwal shares his journey from his early days at Salesforce and then WeWork, right through to the present day.

He reveals how to set Data Science & Engineering up for success in both small and large organisations.

Episode Summary

  • How Salesforce leveraged data to grow their company fast
  • How Mark Benioff ensured his vision was executed effectively at Salesaforce.com
  • What it was like to join WeWork at the start of their data function
  • The differences between how WeWork and Salesforce.com leveraged data
  • How to structure a Data function - centralised V decentralised V hybrid model
  • How Spotify structured their data team to scale the business
  • Can a Fortune 500 business make the hybrid model work?
  • The fundamentals for a new start up - how to get building a data function right
  • Product company versus service delivery company - how does that affect the data function structure?
  • What’s next for data privacy?
  • The 5x Company - entry-level training program, what it is and who its for?
  • Data Mastermind groups - are they the way forward?

  continue reading

25 episoder

Artwork
iconDela
 
Manage episode 297999651 series 2954151
Innehåll tillhandahållet av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

In this episode we are joined by an industry veteran who has worked for some of the biggest names in the enterprise Data world. Tarush Aggarwal shares his journey from his early days at Salesforce and then WeWork, right through to the present day.

He reveals how to set Data Science & Engineering up for success in both small and large organisations.

Episode Summary

  • How Salesforce leveraged data to grow their company fast
  • How Mark Benioff ensured his vision was executed effectively at Salesaforce.com
  • What it was like to join WeWork at the start of their data function
  • The differences between how WeWork and Salesforce.com leveraged data
  • How to structure a Data function - centralised V decentralised V hybrid model
  • How Spotify structured their data team to scale the business
  • Can a Fortune 500 business make the hybrid model work?
  • The fundamentals for a new start up - how to get building a data function right
  • Product company versus service delivery company - how does that affect the data function structure?
  • What’s next for data privacy?
  • The 5x Company - entry-level training program, what it is and who its for?
  • Data Mastermind groups - are they the way forward?

  continue reading

25 episoder

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