What is he best known for?
The fields of study he is best known for:
- Database
- Programming language
- Algorithm
Inderpal Singh Mumick focuses on Data warehouse, Materialized view, Database, Set and Theoretical computer science.
His studies deal with areas such as Dimensional modeling and Data cube as well as Data warehouse.
His Materialized view study is concerned with Information retrieval in general.
The various areas that Inderpal Singh Mumick examines in his Database study include Property, High availability and State.
The Set study combines topics in areas such as Datalog, SQL, Semantics and Negation.
The concepts of his Theoretical computer science study are interwoven with issues in Graph, Functional dependency, Predicate, Query optimization and Algorithm.
His most cited work include:
- Maintaining views incrementally (632 citations)
- Maintenance of materialized views: problems, techniques, and applications (617 citations)
- Selection of views to materialize in a data warehouse (261 citations)
What are the main themes of his work throughout his whole career to date?
Inderpal Singh Mumick mainly focuses on Materialized view, Database, Information retrieval, Data warehouse and Theoretical computer science.
His research in Materialized view intersects with topics in Consistency, SQL, World Wide Web and Data model.
In general Database, his work in Table, Data integration, Deductive database and Data access is often linked to Tuple linking many areas of study.
In his study, which falls under the umbrella issue of Data warehouse, Data mining and Control is strongly linked to Set.
His work in Theoretical computer science addresses issues such as Query optimization, which are connected to fields such as Query language.
His work in Online analytical processing covers topics such as Data cube which are related to areas like Greedy algorithm.
He most often published in these fields:
- Materialized view (30.00%)
- Database (25.00%)
- Information retrieval (16.00%)
What were the highlights of his more recent work (between 1998-2006)?
- Materialized view (30.00%)
- Data warehouse (16.00%)
- Information retrieval (16.00%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Materialized view, Data warehouse, Information retrieval, Database and Online analytical processing.
When carried out as part of a general Materialized view research project, his work on View maintenance is frequently linked to work in Base, therefore connecting diverse disciplines of study.
His study on Data warehouse also encompasses disciplines like
- Mathematical optimization which is related to area like Incremental maintenance,
- Aggregate which intersects with area such as Transaction data.
His Information retrieval research integrates issues from Property, Optimization problem and SQL.
In the subject of general Database, his work in Table, Data integration and Access method is often linked to Cost analysis, thereby combining diverse domains of study.
Inderpal Singh Mumick works mostly in the field of Online analytical processing, limiting it down to concerns involving Data cube and, occasionally, Greedy algorithm, Set and Computational science.
Between 1998 and 2006, his most popular works were:
- Maintenance of materialized views: problems, techniques, and applications (617 citations)
- Selection of views to materialize in a data warehouse (261 citations)
- Selection of Views to Materialize Under a Maintenance Cost Constraint (173 citations)
In his most recent research, the most cited papers focused on:
- Database
- Programming language
- Algorithm
Inderpal Singh Mumick mainly investigates Materialized view, Data warehouse, Data cube, Online analytical processing and Information retrieval.
The various areas that Inderpal Singh Mumick examines in his Materialized view study include Deferred maintenance, Overhead, Database transaction, Invariant and Database maintenance.
His study looks at the relationship between Data warehouse and topics such as Aggregate, which overlap with Scheme, Transaction data and Incremental maintenance.
His Data cube study incorporates themes from Set and Greedy algorithm.
His work carried out in the field of Greedy algorithm brings together such families of science as Graph theory, Theoretical computer science, Heuristics and Dimensional modeling.
His work on Incremental view maintenance and View maintenance as part of general Information retrieval study is frequently linked to Tuple and Function, bridging the gap between disciplines.
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