International Conference on Data Visualization and Mining using Big Data - (ICDVMBDA-26)


8th - 9th December, 2026 | Nice, France

Multi-format (In-person/Virtual)

Registration Options

Explore conference registration categories designed for every mode of participation.

Important Dates

Pre-registration Deadline

8th November, 2026

Paper Submission Deadline

13th November, 2026

Last Date Of Registration

23rd November, 2026

Date Of Conference

8th - 9th December, 2026

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Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 4 SDG 4 — Quality Education
SDG 8 SDG 8 — Decent Work and Economic Growth
SDG 9 SDG 9 — Industry, Innovation and Infrastructure
SDG 10 SDG 10 — Reduced Inequalities
SDG 11 SDG 11 — Sustainable Cities and Communities
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All Session Tracks

Track 01
Advancements in Data Visualization Techniques

This track focuses on the latest methodologies and tools for effective data visualization in the context of big data. Participants will explore innovative visual representations that enhance comprehension and decision-making.

Track 02
Machine Learning Applications in Big Data Analytics

This session will delve into the integration of machine learning algorithms within big data analytics frameworks. Attendees will examine case studies that demonstrate the impact of these technologies on predictive modeling and data interpretation.

Track 03
AI-Driven Visualization Strategies

This track will investigate the role of artificial intelligence in enhancing data visualization processes. Discussions will center on how AI can automate and optimize visual analytics to uncover insights from complex datasets.

Track 04
Data Mining Techniques for Large Scale Datasets

This session will cover advanced data mining techniques tailored for large-scale big data environments. Participants will learn about novel approaches to extract meaningful patterns and trends from extensive datasets.

Track 05
Visual Analytics for Intelligent Systems

This track will explore the intersection of visual analytics and intelligent systems in big data applications. The focus will be on how visual tools can enhance the interpretability and usability of intelligent systems.

Track 06
Dashboard Design and User Experience

This session will address best practices in dashboard design for effective data visualization. Participants will discuss user experience considerations that enhance the accessibility and functionality of data dashboards.

Track 07
Data Integration Techniques for Enhanced Analytics

This track will examine methodologies for integrating disparate data sources to improve analytical outcomes. The focus will be on strategies that facilitate seamless data integration in big data environments.

Track 08
Visual Intelligence and Data Storytelling

This session will highlight the importance of visual intelligence in crafting compelling data narratives. Attendees will learn how effective storytelling techniques can transform complex data into actionable insights.

Track 09
Innovative Strategies for System Optimization

This track will focus on innovative strategies aimed at optimizing systems through big data analytics. Participants will explore case studies that illustrate the successful application of these strategies in various engineering domains.

Track 10
Predictive Analytics in Engineering Applications

This session will discuss the role of predictive analytics in engineering, particularly in the context of big data. Attendees will explore methodologies that enhance forecasting accuracy and operational efficiency.

Track 11
Challenges and Solutions in Big Data Visualization

This track will address the challenges faced in visualizing big data and propose potential solutions. Participants will engage in discussions on overcoming obstacles related to data complexity and visualization scalability.