scholarly journals Towards Identifying Data Analytics Use Cases in Product Planning

Procedia CIRP ◽  
2021 ◽  
Vol 104 ◽  
pp. 1179-1184
Author(s):  
Maurice Meyer ◽  
Melina Panzner ◽  
Christian Koldewey ◽  
Roman Dumitrescu
Keyword(s):  
Data Analytics ◽  
Use Cases ◽  
Product Planning

scholarly journals Use cases and challenges in telecom big data analytics

2016 ◽  
Vol 5 ◽  
Author(s):  
Chung-Min Chen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Driving Forces ◽  
Big Data Analytics ◽  
Use Cases ◽  
Telecommunication Industry ◽  
New Research

This paper examines the driving forces of big data analytics in the telecom domain and the benefits it offers. We provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.

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 Informatics driven quality improvement in the modern histology lab

JAMIA Open ◽  
2020 ◽  
Author(s):  
Robert P Seifert ◽  
Vektra Casler ◽  
Nada Al Qaysi ◽  
Shaileshbhai Revabhai Gothi ◽  
Leah Williams ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Information Systems ◽  
Data Visualization ◽  
Data Analytics ◽  
Use Cases ◽  
Anatomic Pathology ◽  
Data Tracking ◽  
Visualization Techniques ◽  
Laboratory Information Systems ◽  
And Task

Abstract Laboratory Information Systems (LIS) and data visualization techniques have untapped potential in anatomic pathology laboratories. Pre-built functionalities of LIS do not address all the needs of a modern histology laboratory. For instance, “Go live” is not the end of LIS customization, but just the beginning. After closely evaluating various histology lab workflows, we implemented several custom data analytics dashboards and additional LIS functionalities to monitor and address weaknesses. Herein, we present our experience in LIS and data-tracking solutions that improved trainee education, slide logistics, staffing/instrumentation lobbying, and task tracking. The latter was addressed through the creation of a novel “status board” akin to those seen in inpatient wards. These use-cases can benefit other histology laboratories.

scholarly journals Framework for Data Analytics in Data-Driven Product Planning

2020 ◽  
Vol 52 ◽  
pp. 350-355
Author(s):  
Melina Massmann ◽  
Maurice Meyer ◽  
Maximilian Frank ◽  
Sebastian von Enzberg ◽  
Arno Kühn ◽  
...  
Keyword(s):  
Data Analytics ◽  
Data Driven ◽  
Product Planning

scholarly journals Smart Data Analytics for Machine Learning Approach in 5G Network

2021 ◽  
pp. 1-4
Author(s):  
Camilla Schaefer ◽  
Ana Makatsaria
Keyword(s):  
Machine Learning ◽  
Data Analytics ◽  
Large Range ◽  
Transmission Capacity ◽  
Use Cases ◽  
Learning Approach ◽  
5G Network ◽  
Machine Learning Approach ◽  
Smart Data ◽  
Smart Vehicle

Psychological radio innovation can possibly ameliorate the shortage of remote assets on the grounds that unlicensed clients can utilize remote assets just on the off chance that they no affect the tasks of authorized clients. Later, psychological radio CLOUD (CogCLOUD) will be built from numerous versatile SUs associated with one another in a circulated way, which can be sent for different applications, including smart vehicle frameworks. Notwithstanding, in CogCLOUD, channel exchanging is intrinsically important at whatever point an essential client with a permit shows up on the channel. Permitting optional clients to pick an accessible channel among a large range hence empowers dependable correspondence in this unique circumstance, yet correspondence qualities, for example, bottleneck transmission capacity, RTT would change with channel switch. Because of the change, TCP needs refresh the blockage window to utilize the accessible assets. TCP CRAHN was proposed for CogCLOUD. TCP CRAHN is first assessed in quite a while the bottleneck transmission capacity then RTT changes. Considering the outcomes, TCP CoBA is proposed to additionally increase the throughput of the above use cases. TCP CoBA refreshes the cwnd dependent on accessible cradle space in transfer hub upon channel switch, just as other correspondence attributes. Through recreations, we show that contrasted and TCP CRAHN, TCP CoBA increase the throughput by up to 200%.

scholarly journals A Research on the Importance of Big Data Analytics in Health Care and Government Sectors

2019 ◽  
Vol 9 (1) ◽  
pp. 5471-5473
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Data Use ◽  
Big Data Analytics ◽  
Use Cases ◽  
State Of Affairs ◽  
Important Purpose ◽  
Insight Into

This paper provides associate insight into but, we are able to uncover further worth from the information produced by health care and govt. associate oversized quantity of varied info is produced by these sectors. However, whereas not correct info analytics ways, this info became of no use. Big Data Analytics victimization Hadoop plays an honest responsibility in enjoying important purpose analysis of the big volume of knowledge and prepared to guess the pressing state of affairs things prior to that happens. It explains the Big Data use-cases in health care and govt. sectors.

Data Analytics in der Produktion*/A maturity model for the classification of real-world applications of data analytics in manufacturing environment

2018 ◽  
Vol 108 (07-08) ◽  
pp. 543-548
Author(s):  
T. Pschybilla ◽  
D. Baumann ◽  
S. Manz ◽  
W. Wenger ◽  
Keyword(s):  
Decision Making ◽  
Real World ◽  
Data Analytics ◽  
Use Cases ◽  
Maturity Model ◽  
Manufacturing Environment ◽  
Smart Services ◽  
Real World Applications

Mit der fortschreitenden Digitalisierung in der Produktion werden konstant ansteigende Datenmengen generiert. Eine besondere Rolle kommt dabei dem Gebiet der Data Analytics zu, welches die Gewinnung von Wissen aus Daten und damit die Entscheidungsfindung unterstützen kann. Im Beitrag wird ein Reifegradmodell zur Einordnung von Anwendungsfällen der Data Analytics in der Produktion vorgestellt und an einem Beispiel der Smart Services der Trumpf GmbH + Co. KG angewendet.   With the progressing digitization in manufacturing, continuously increasing amounts of data are being generated. The field of data analytics plays an important role in this context by advancing the acquisition of knowledge from data and thus decision-making. This paper presents a maturity model for the classification of data analytics use cases in manufacturing. The model is applied to an example of Smart Services at Trumpf GmbH + Co. KG.

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