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Unveiling the Hidden Challenges of Cloud Data Management

This article explores the multifaceted challenges of cloud data management, as outlined by Magdalena Balazinska from the University of Washington. It covers three primary problem areas: 1) Fast data management, addressing the need for real-world use-case translation into research problems. 2) Efficient multitenant data management for cloud providers, focusing on both OLTP and OLAP challenges. 3) Transformative approaches to cloud data management, redefining interfaces and strategies for shared data processing, cost analysis, and service-level agreements.

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Unveiling the Hidden Challenges of Cloud Data Management

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  1. The Hidden Face of • Cloud Data Management Magdalena Balazinska Computer Science & Engineering -- U of Washington http://www.cs.washington.edu/people/faculty/magda Magdalena Balazinska - University of Washington

  2. Three Types of Challenges Problem 1: Fast Pb 2: Efficient (multitenant) Data Management in the Cloud Pb 3: Transformative (for developers and users) Well defined research problems Pretty well defined research problems Poorly defined research problems Magdalena Balazinska - University of Washington

  3. Pb 1: Fast Cloud Data Management • Well-known challenges around all V’s • Volume, velocity, variety, etc. • But: Need to incentivize and recognize translation of real-world use-cases into research problems • Description of application • Dataset(s) to use for testing solutions • List of current solutions and their performance • It’s too costly when everyone does it over and over again Magdalena Balazinska - University of Washington

  4. Pb2: Efficient Cloud Data Management • Multitenancy problem for Cloud providers: • OLTP: Well defined problems (predict, pack, and migrate) • OLAP: Less well defined problems • And what about service developers • Build services on top of existing Cloud resources • These services may have tenants of their own • Challenges • Resource management in hierarchy of multitenant systems • Performance, elasticity, costs, SLAs Magdalena Balazinska - University of Washington

  5. Pb3: Transformative Cloud Data Mgmt • New interface to data management • How should Cloud SLAs look like? How to avoid surprises? • How to reason about Cloud costs and capabilities? • How to do all types of processing at the same time? • Graphs, text, streams, etc. • Interactive, batch, visual • New levels of sharing across users and tenants • How to manage sharing of data and computation? • Data itself may have a price and/or a license agreement • How to support data discovery? quality assessment? Magdalena Balazinska - University of Washington

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