The phrase "abstraction for data" is correct and usable in written English.
It can be used in contexts related to computer science, programming, or data management, where the concept of abstraction is applied to data structures or representations.
Example: "The abstraction for data allows developers to work with complex data types without needing to understand their underlying implementation."
Alternatives: "data abstraction" or "data representation".
Confluo's basic storage abstraction for data streams is a new data structure: Atomic MultiLog, a collection of lock-free concurrent logs that stores raw data, aggregate statistics and materialized views, and uses new techniques to efficiently update the entire collection as a single atomic operation.
Finally, the same observation as for Esterel holds, i.e., the delta-cycle changes only provide a single abstraction for data and cannot influence the control-flow of substeps.
Virtualization and abstraction for data centers (whether private, hybrid and public cloud) depends upon storage and memory products, as shown by the number of storage companies participating in the 2018 VMworld.
Three grounding principles, namely autonomy, adaptability and emergence, support the co-construction of successive abstraction levels for data interpretation.
Moreover, the Esterel variables only provide one simplified abstraction layer for data.
We developed a standard abstraction form for data extraction.
Domain model, logical system model, and implementation model are three layers for abstraction of data modeling in MDA.
This architecture has three layers for abstraction of data modeling because software solutions can be automatically derived from models by "technology independence".
We propose Chunks and Tasks, a parallel programming model built on abstractions for both data and work.
These ideas range from techniques for dealing with impedance mismatches between programming paradigms such as Language Integrated Querying (LINQ), to abstractions and primitives for data parallelism such as BigTable and Map/Reduce, to new, data-centric declarative languages for domains such as networking and system management.
In this paper, an approach of data abstraction for fixture design information representation is proposed, first to systemize and manage myriads of fixture related resources, e.g., past fixture design solutions, fixture units depository.
