In traditional data architecture, data was always centralised in a data warehouse or a data lake and governed by a centralised team.
However, with the rise of distributed systems, microservices, and agile methodologies, this approach has proven to be inadequate for managing data at scale. Data Mesh proposes a different approach, where data is treated as a product and owned by the teams that produce it.
In other words, it's a way of thinking about data management that focuses on decentralisation and autonomy. But how can companies use this to their advantage?
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos spoke to Paolo Platter, Co-Founder and CTO at Agile Lab, about:
- Successful data mesh strategies
- Benefits vs monolithic data lakes
- Customer success stories
Agile Lab works with an array of clients across the globe, creating business vertical solutions to address specific challenges and needs in their field of activity. To hear about their success stories and the ways in which they exceed their clients' expectations, skip to 19:40.
Agile Lab creates value for its clients in data-intensive environments through customizable solutions to establish performance driven processes, sustainable architectures, and automated platforms driven by data governance best practices.
Since 2014 we have implemented 100+ successful Elite Data Engineering initiatives and used that experience to create Witboost: a technology agnostic, modular platform, that empowers modern enterprises to discover, elevate and productize their data both in traditional environments and on fully compliant Data mesh architectures.
Comments ( 3 )