Data Orchestration For Hybrid Cloud Analytics

Episode • Oct 22, 2019 • 42m

Summary

The scale and complexity of the systems that we build to satisfy business requirements is increasing as the available tools become more sophisticated. In order to bridge the gap between legacy infrastructure and evolving use cases it is necessary to create a unifying set of components. In this episode Dipti Borkar explains how the emerging category of data orchestration tools fills this need, some of the existing projects that fit in this space, and some of the ways that they can work together to simplify projects such as cloud migration and hybrid cloud environments. It is always useful to get a broad view of new trends in the industry and this was a helpful perspective on the need to provide mechanisms to decouple physical storage from computing capacity.

Announcements

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Your host is Tobias Macey and today I’m interviewing Dipti Borkark about data orchestration and how it helps in migrating data workloads to the cloud

Interview

Introduction
How did you get involved in the area of data management?
Can you start by describing what you mean by the term "Data Orchestration"?
- How does it compare to the concept of "Data Virtualization"?
- What are some of the tools and platforms that fit under that umbrella?
What are some of the motivations for organizations to use the cloud for their data oriented workloads?
- What are they giving up by using cloud resources in place of on-premises compute?
For businesses that have invested heavily in their own datacenters, what are some ways that they can begin to replicate some of the benefits of cloud environments?
What are some of the common patterns for cloud migration projects and what challenges do they present?
- Do you have advice on useful metrics to track for determining project completion or success criteria?
How do businesses approach employee education for designing and implementing effective systems for achieving their migration goals?
Can you talk through some of the ways that different data orchestration tools can be composed together for a cloud migration effort?
- What are some of the common pain points that organizations encounter when working on hybrid implementations?
What are some of the missing pieces in the data orchestration landscape?
- Are there any efforts that you are aware of that are aiming to fill those gaps?
Where is the data orchestration market heading, and what are some industry trends that are driving it?
- What projects are you most interested in or excited by?
For someone who wants to learn more about data orchestration and the benefits the technologies can provide, what are some resources that you would recommend?

Contact Info

LinkedIn
@dborkar on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
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Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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