scholarly journals Controller szerepkör és szaktudás változása az Ipar 4.0 hatására

Economica ◽  
2020 ◽  
Vol 11 (3-4) ◽  
Author(s):  
Brigitta Kovács
Keyword(s):  
Big Data ◽  
Business Information

Publikációm célja, hogy bemutassa a controller szerepkör kialakulását és fejlődését az elmúlt 10 évben, különös tekintettel a jelenlegi változásokra, mely az Ipar 4.0 következménye. Az Ipar 4.0 az exponenciális információtechnikai fejlődéshez köthető, melynek révén korábban elképzelhetetlen mennyiségű adat gyűjtésére, tárolására és kiértékelésére lettünk képesek (Big Data). A beszámolást és az elemzéseket új üzleti információs (Business Information - BI) rendszerek segítik, melyekben interaktív dashboard alapú riportok felépítésére van lehetőség. Az előrejelzés készítésben is új lehetőségek nyíltak, ugyanis a nagyobb mértékben rendelkezésre álló adatok és a nagyobb számítástechnikai kapacitások révén ezeken futtatható előrejelző algoritmusok révén, sokkal gyakoribb és pontosabb tervek készíthetők. A változások természetesen hatással vannak mind a controllertől elvárt szaktudásra, mind a szervezeten belül betöltött szerepére, melyet részletesen bemutatok publikációmban. A cikk végén ismertetem empirikus kérdőíves kutatásom eredményeit a controllerektől elvárt IT tudásról és ennek összefüggéseit a vállalat controlling folyamatainak automatizáltságával.

Modern Health Management With Cognitive Computing and Big Data Analytics

2019 ◽  
pp. 206-224
Author(s):  
Mamata Rath
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Health Management ◽  
Big Data Analytics ◽  
Large Data ◽  
Data Sets ◽  
Cognitive Computing ◽  
Business Information ◽  
Data Querying ◽  
Data Elements

Big data analytics is an refined advancement for fusion of large data sets that include a collection of data elements to expose hidden prototype, undetected associations, showcase business logic, client inclinations, and other helpful business information. Big data analytics involves challenging techniques to mine and extract relevant data that includes the actions of penetrating a database, effectively mining the data, querying and inspecting data committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage impressive data that can influence the business. In this way, the primary goal of big data analytics is to help business relationship to have enhanced comprehension of data and, subsequently, settle on proficient and educated decisions.

Business Information Mapping for Big Data and Internet of Things

2015 ◽  
pp. 79-97
Author(s):  
Robert Stackowiak ◽  
Art Licht ◽  
Venu Mantha ◽  
Louis Nagode
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Business Information

Big Data Analytics and IoT in Smart City Applications

2022 ◽  
pp. 364-380
Author(s):  
Mamata Rath
Keyword(s):  
Big Data ◽  
Smart City ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Business Information ◽  
Data Querying ◽  
Data Elements

Big data analytics is a sophisticated approach for fusion of large data sets that include a collection of data elements to expose hidden prototype, undetected associations, showcase business logic, client inclinations, and other helpful business information. Big data analytics involves challenging techniques to mine and extract relevant data that includes the actions of penetrating a database, effectively mining the data, querying and inspecting data committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage impressive data that can influence the business.

Big Data Analytics and IoT in Smart City Applications

2021 ◽  
pp. 586-601
Author(s):  
Mamata Rath
Keyword(s):  
Big Data ◽  
Smart City ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Business Information ◽  
Data Querying ◽  
Data Elements

Big data analytics is a sophisticated approach for fusion of large data sets that include a collection of data elements to expose hidden prototype, undetected associations, showcase business logic, client inclinations, and other helpful business information. Big data analytics involves challenging techniques to mine and extract relevant data that includes the actions of penetrating a database, effectively mining the data, querying and inspecting data committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage impressive data that can influence the business.

scholarly journals Research on the Innovation of Cross-border E-commerce Customer Service Model Based on Big Data in the Post-epidemic Era

2021 ◽  
Vol 292 ◽  
pp. 03041
Author(s):  
Jiahui Liang
Keyword(s):  
Big Data ◽  
Customer Service ◽  
Positive Impact ◽  
Rapid Development ◽  
Service Model ◽  
Cross Border ◽  
Customer Information ◽  
Business Information ◽  
Data Application ◽  
Big Data Application

In the post-epidemic era, with the rapid development of cross-border e-commerce, massive amounts of customer information data are generated every day. This article explores useful business information data, innovates cross-border e-commerce customer service model, optimizes customer service details, meets customer needs, and creates greater profits for the company. This article defines big data, expounds the 5V characteristics of big data and commonly used analysis methods, analyzes the positive impact of big data on cross-border e-commerce customer service, and the problems of big data application in cross-border e-commerce customer service, and proposes targeted cross-border innovations Countermeasures for e-commerce customer service model.

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