ALF: An Automated Low-code Flexible Framework for Data Workflows

The demand for data science innovation is growing across all sectors. There is no shortage of new big-data applications and tools for deploying data science projects. Data scientists typically create data workflows manually or by writing scripts to automate parts of the process. However, basic scripting is insufficient for large-scale projects and performance optimizations. This poses great technical challenges for data scientists. In this paper, we present the Automated Low-code Flexible (ALF) Framework, designed to remove technical barriers and streamline data workflows. ALF also provides a holistic view of workflow construction and end-to-end workflow management. Its design is supported by a case study, demonstrating ALF’s ability to integrate a diverse array of applications, alongside performance enhancement tools and workflow inspection capabilities.

Authors

Institutions

Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825914
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ALF: An Automated Low-code Flexible Framework for Data Workflows

Mea Wang, Usman Alim, Rishab Aiyer Ghosh, Wamika Jha
Scientific Computing and Data Management
article

ALF: An Automated Low-code Flexible Framework for Data Workflows

Mea Wang, Usman Alim, Rishab Aiyer Ghosh, Wamika Jha
article en

Abstract

The demand for data science innovation is growing across all sectors. There is no shortage of new big-data applications and tools for deploying data science projects. Data scientists typically create data workflows manually or by writing scripts to automate parts of the process. However, basic scripting is insufficient for large-scale projects and performance optimizations. This poses great technical challenges for data scientists. In this paper, we present the Automated Low-code Flexible (ALF) Framework, designed to remove technical barriers and streamline data workflows. ALF also provides a holistic view of workflow construction and end-to-end workflow management. Its design is supported by a case study, demonstrating ALF’s ability to integrate a diverse array of applications, alongside performance enhancement tools and workflow inspection capabilities.

University of Calgary (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 69%
Scientific Computing and Data Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ALF: An Automated Low-code Flexible Framework for Data Workflows — Mea Wang, Usman Alim, et al. · (2024) | TGRS Research Map | TGRS