Summary of the Episode

Modern Data Stacks (MDS) with their cost-effectiveness and flexibility are the new big thing in the data management landscape. InvoTalks sat down with Natalia Shuliak from Double Cloud-a platform that allows users to build sub-second analytical data & pipelines in less than 5 minutes. In this episode, listen to how you can adopt and use Modern Data Stacks (MDS) to make data-driven decisions to stand out in the market.


Show Notes

  • Modern Data Stack is not a buzzword anymore, in fact, it is a technology stack that is attracting a lot of attention in the data world. Mainly because of the pressing need for data management and large swathes of data predicted to be produced in the coming years. As per Natalia by 2025, 180 zettabytes of data will be produced. For its proper management, Modern Data Stack architecture is a “must”.
  • Natalia also says that most of the companies have questions like Why use modern data stack?  Characteristics of modern data stack? Key fundamentals of the modern data stack. It is all just so simple; a Modern Data Stack (MDS) is a set of specific tools that are used to organize, store and transform data. The only thing that is different is the flexibility and cost-effectiveness it provides in comparison to the old data management style or ETL. Where a company has to procure all the system- first extraction of data, transportation. Second loading and third analysis. But Modern Data Stack Tools are robust enough that each component can be swapped out independently and can excel at the function they are built for.
  • Natalia says, companies have all of this data with a choice to use and extract value or can abandon it and get eaten by the competition. On the basis of useful data insights the ever-changing market trends plus evolving and transforming customer needs can be judged and efficiently dealt with. Double Cloud being a flexible platform allows users to build sub-second analytical data & pipelines in less than 5 minutes on open-source technologies like ClickHouse and Apache Kafka.

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