Generalizing Streaming Pipeline Design for Big Data

2020 ◽  
pp. 149-160
Author(s):  
Krushnaa Rengarajan ◽  
Vijay Krishna Menon
Keyword(s):  
Big Data ◽  
Pipeline Design

scholarly journals MLOps approach in the cloud-native data pipeline design

2021 ◽  
Author(s):  
István Pölöskei
Keyword(s):  
Big Data ◽  
Data Modeling ◽  
Technology Gap ◽  
Know How ◽  
Modeling Process ◽  
Data Pipeline ◽  
Pipeline Design

The data modeling process is challenging and involves hypotheses and trials. In the industry, a workflow has been constructed around data modeling. The offered modernized workflow expects to use of the cloud’s full abilities as cloud-native services. For a flourishing big data project, the organization should have analytics and information-technological know-how. MLOps approach concentrates on the modeling, eliminating the personnel and technology gap in the deployment. In this article, the paradigm will be verified with a case-study in the context of composing a data pipeline in the cloud-native ecosystem. Based on the analysis, the considered strategy is the recommended way for data pipeline design.

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

When the Sample Is the Population: Big Data

PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  
Big Data

A critical incident for big data

2014 ◽  
Author(s):  
Daniel Maurath
Keyword(s):  
Big Data ◽  
Critical Incident

Little sensors, big data

2015 ◽  
Author(s):  
Kirsten Weir
Keyword(s):  
Big Data
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