Intelligent design patterns for cloud-based analytics and BI
Who is this presentation for?Enterprise architect, CIO, CTO, Data Engineering, Analytics experts
With data management increasingly moving to object storage and cloud data warehouses, organizations naturally expect the BI applications can also benefit from the scale of data and real-time analytics. The traditional BI architecture in this cloud-native environment surfaces not-so-obvious challenges :
While object storage scales for you to store large amounts of data, the analytics can only be done on subsets.
While the data can be ingested in real time, the analytics has to wait for data warehouse batch ETL cycles before it can be used.
It is time to invest in an agile and cloud-native architecture for BI, which does not rely on outdated analytic patterns of traditional BI.
In this talk we will discuss how the application of traditional BI to cloud-native data management and warehousing can result in a “frankenstack” that many users have tried to simplify in the first place by choosing cloud! We will review service-oriented design of the clouds (storage, compute, catalog, security, SQL service) and describe how BI should be a native service in this environment.
What you'll learn
Shant Hovsepian is a cofounder and CTO of Arcadia Data, where he is responsible for the company’s long-term innovation and technical direction. Previously, Shant was an early member of the engineering team at Teradata, which he joined through the acquisition of Aster Data. Shant interned at Google, where he worked on optimizing the AdWords database, and was a graduate student in computer science at UCLA. He is the coauthor of publications in the areas of modular database design and high-performance storage systems.
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