Operation management architecture of power communication backbone transmission network based on big data

2021 ◽  
Author(s):  
Shujuan Zhang ◽  
Lixia Zhang ◽  
Huisheng Gao ◽  
Yang Li ◽  
Meili Wang
Keyword(s):  
Big Data ◽  
Operation Management ◽  
Transmission Network ◽  
Management Architecture

Big Data in Operation Management

2016 ◽  
pp. 1-29
Author(s):  
Arushi Jain ◽  
Vishal Bhatnagar
Keyword(s):  
Big Data ◽  
Data Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Operation Management ◽  
Use Cases ◽  
Revolutionary Change

The word big data analytics have been increased substantially these days, one of the most prominent reasons is to predict the behavior of the customer purchase. This analysis helps to understand what customer wants to purchase, where they want to go, what they want to eat etc. So that valuable insights can be converted into actions. The knowledge thus gained helps in understanding the needs of every customer individually so that it becomes easier to do the business with them. This is the revolutionary change to build a customer-centric business. To build a customer centric business an organization must be observant about what customer is doing, must keep a record about what customer is purchasing and lastly should discover the insights to maximum the profit for customer. In this chapter we discussed about various approaches to big data management and the use cases where these approaches can be applied successfully.

scholarly journals Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Siyang Qin ◽  
Jie Man ◽  
Xuzhao Wang ◽  
Can Li ◽  
Honghui Dong ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Rapid Development ◽  
Big Data Analytics ◽  
Travel Behaviour ◽  
Operation Management ◽  
Tourist Attractions ◽  
Data Support ◽  
Effective Manner ◽  
Tourist Flow

Considering the rapid development of the tourist leisure industry and the surge of tourist quantity, insufficient information regarding tourists has placed tremendous pressure on traffic in scenic areas. In this paper, the author uses the Big Data technology and Call Detail Record (CDR) data with the mobile phone real-time location information to monitor the tourist flow and analyse the travel behaviour of tourists in scenic areas. By collecting CDR data and implementing a modelling analysis of the data to simultaneously reflect the distribution of tourist hot spots in Beijing, tourist locations, tourist origins, tourist movements, resident information, and other data, the results provide big data support for alleviating traffic pressure at tourist attractions and tourist routes in the city and rationally allocating traffic resources. The analysis shows that the big data analysis method based on the CDR data of mobile phones can provide real-time information about tourist behaviours in a timely and effective manner. This information can be applied for the operation management of scenic areas and can provide real-time big data support for “smart tourism”.

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