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Demo Data from EDBT 2026 / reviewers in the wild / expert

Rima Mutreja

dblp:322/1441 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 77% Query processing and optimization · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Database system architecture and tuning
workload characterization		 0.612022
Intelligent Automated Workload Analysis for Database Replatforming · SIGMOD Conference 2022

Methods — techniques the papers use, named apart from their topics

workload analysis · 0.6
YearPublicationVenuePosition
2023 How Global Retailer ADEO Migrated to Google BigQuery with Database Virtualization
abstract
We describe how multi-national retailer ADEO successfully employed database virtualization to migrate all workloads of a complex Enterprise Data Warehouse (EDW) from a legacy Teradata system to Google BigQuery. We demonstrate the generality of the technology and the approach.
Ehab Abdelhamid, Amirhossein Aleyasen, Michael Duller, Eric Foratier, Vincent Fruleux, Mirella Katch, Gourab Mitra, Rima Mutreja, Jozsef Patvarczki, Matthew Pope, Nikos Tsikoudis, F. Michael Waas
 IEEE Big Data8
2022 Intelligent Automated Workload Analysis for Database Replatforming
abstract
Performing a detailed workload analysis is a crucial step in determining the feasibility, timeline and cost of a major data warehouse replatforming project, i.e., migration from one platform to another. A large company's data warehouse applications may include millions of queries, some of which will use features that are unsupported or have different semantics in the new warehouse, or may have poor performance there.
Amirhossein Aleyasen, Mark Morcos, Lyublena Antova, Marc Sugiyama, Dmitri Korablev, Jozsef Patvarczki, Rima Mutreja, Michael Duller, F. Michael Waas, Marianne Winslett
 SIGMOD Conference7