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Agile Lab
Agile Lab
6 episodes
10 hours ago
Keep up with Big data and cutting-edge technologies. In this podcast we're going to talk about data from different perspectives: Architectures, Data science, Data engineering and much more.
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Management
Business
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All content for Agile Lab is the property of Agile Lab and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Keep up with Big data and cutting-edge technologies. In this podcast we're going to talk about data from different perspectives: Architectures, Data science, Data engineering and much more.
Show more...
Management
Business
Episodes (6/6)
Agile Lab
How Data Mesh enables organizational changes

In this episode, Andrea Faré, Change Choreographer at Leapfrog and Alberto Firpo, Agile Lab CEO and Co-Founder, focus on how companies can leverage Data Mesh to start a radical organizational change and how a Data Mesh Blueprint could help this transformation.

LISTEN THE PODCAST and learn:

  • What has changed for Enterprise Organizations in the last years, from the organizational and data point of view?
  • How a Data Mesh Blueprint could support the chance?
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4 years ago
30 minutes 33 seconds

Agile Lab
Semantic knowledge in the Data Mesh

In this episode, with Juan Sequeda, Principal Scientist at data.world, and Paolo Platter, CTO & Co-founder of Agile Lab, we discuss synergies between the emerging paradigms of Knowledge Graphs and Data Mesh, looking at how they can work together and the main differences in terms of ownership, accountability and data observability.

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4 years ago
52 minutes 10 seconds

Agile Lab
Organizational changes in the Data Mesh Journey | Part 1

In the second episode, Henrik Göthberg, CEO and Founder at Dairdux Alliance and Organizational Management Expert, and Alberto Firpo, Agile Lab CEO, focus on the main pain-points that organizations have to deal with when starting the journey towards Data Mesh.

LISTEN THE PODCAST to discover:

  • Which are the internal and external pain points
  • How you can work with data integration
  • Why a company should choose Data Mesh
  • If distributed data are unavoidable
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4 years ago
30 minutes 14 seconds

Agile Lab
Organizational changes in the Data Mesh Journey | Part 2

In this episode, Henrik Göthberg, CEO and Founder at Dairdux Alliance and Organizational Management Expert, and Alberto Firpo, Agile Lab CEO, focus on Change Management, discussing in depth which are the main challenges for both the IT and Business side.

LISTEN THE PODCAST and discover:

  • What is the identikit of a company that could start a Data Mesh journey?
  • What role does central IT need to play?
  • How can a company boost adoption?
Show more...
4 years ago
47 minutes 3 seconds

Agile Lab
InnoTechCast - Agile Lab for Ambrosetti

Alberto Firpo, Co-Founder & CEO of Agile Lab, is the protagonist of the episode of "InnoTechCast - Leaders' View on Innovation" to talk about Machine Learning and Big Data applied to insurance.


In this podcast Alberto Firpo explains how the data collected by the "black-box" installed on cars, thanks to Machine Learning models and real-time systems, provide useful information to insurance companies.


In particular, through Agile Lab's Wasp platform, the data collected in real time allow insurance companies to activate services for customers, in real time, and formulate policies on the basis of "driving behaviour", the driving behaviour of the driver detected through innovative methods.

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4 years ago
23 minutes 22 seconds

Agile Lab
Data Mesh - Overview and real use cases

In this first episode,  Paolo Platter, Agile Lab CTO, talks about some major aspects of the Data Mesh journey.

LISTEN THE PODCAST and find the answer to some key questions:

  • What is Data Mesh?
  • What problems can it solve?
  • How to take the first steps?
  • Data Lake vs Data Mesh
Show more...
4 years ago
43 minutes 21 seconds

Agile Lab
Keep up with Big data and cutting-edge technologies. In this podcast we're going to talk about data from different perspectives: Architectures, Data science, Data engineering and much more.