3 research outputs found
Classification Methodology for Architectures in Information Systems: A Statistical Converging Technique
Architectures are critical to the Information System (IS) domain because they represent funda- mental structures and interactions of systems. Since analysing architecture similarities is chal- lenging and time-consuming even in one domain, IS architecture classifications are paramount to understanding architectural complexity. However, classification approaches used in existing research commonly rely on manual interventions, and thus architectural classification reliability is hampered. We propose a novel methodology based on component modelling and applica- tion of a statistical converging technique, which ensures reliable IS architectural classification and minimises subjective interventions. We demonstrate the methodology by classifying data warehouse architectures
Data processing in high-performance computing systems
The paper integrates the results of a large group of authors working in different areas that are important
in the scope of big data, including but not limited to: overview of the basic solutions for the development of data centers; storage and processing; decomposition of a problem into sub-problems of lower complexity (such as applying divide and conquer algorithms); models and methods allowing broad parallelism to be realized; alternative techniques for potential acceleration; programming languages; and practical applications
BIG DATA ΠΈ Π°Π½Π°Π»ΠΈΠ· Π²ΡΡΠΎΠΊΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ : ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ
Π ΡΠ±ΠΎΡΠ½ΠΈΠΊΠ΅ ΠΎΠΏΡΠ±Π»ΠΈΠΊΠΎΠ²Π°Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Π½Π°ΡΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΎΠΊ Π² ΠΎΠ±Π»Π°ΡΡΠΈ BIG DATA and Advanced Analytics Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ IT-ΡΠ΅ΡΠ΅Π½ΠΈΠΉ ΠΈ Π±ΠΈΠ·Π½Π΅Ρ-ΡΠ΅ΡΠ΅Π½ΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½Ρ, ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΠΈ