We are invites all participants worldwide to attend the
24th International Conference on Big Data & Data Analytics on December 11-12, 2025 in Amsterdam, Netherlands cordially invites you to Oral presentations, poster presentations and exhibitors sharing their knowledge. The main theme of the conference is "
AI-Powered Analytics: Shaping Tomorrow’s Digital Ecosystems ". The conference aims to extend its reach in the field of big data and AI, and lectures by experts and presentations by young researchers will keep the conference inspired and keep you enthusiastic. We feel that our expert organizing committee is our major asset. But your presence at the venue adds another feather to the crown of
Data Analysis-2025.
Data analysis, which extracts hidden and predictive information from large databases, is a powerful new AI technology with great potential to help companies focus on the most important information in their data warehouses. Data Analysis-2025 consists of the following 20 tracks and sessions designed to provide a comprehensive session that addresses current issues in big data and data analytics. Data analytics tools predict future trends and behaviours and enable businesses to make proactive, knowledge-driven decisions. The automated future analysis provided by AI technology goes beyond the analysis of past events provided by the retrospective tools typical of decision support systems. Big data and data analytics tools can answer business problems that traditionally take too long to solve.
The keywords related to this conference are:
Data Analysis-2025 | Big Data & Data Analytics | Data Analysis conferences-2025 | Big Data conferences | Data Analysis conferences | ICBDDA-2025 | Data Analysis 2025 | Conference Series | Upcoming Big Data Conferences | Amsterdam | Netherlands | 2025
Join global thought leaders, researchers, industry experts, and data pioneers at the 24th International Conference on Big Data & Data Analytics, happening on December 11–12, 2025, in the vibrant city of Amsterdam, Netherlands. With the theme “AI-Powered Analytics: Shaping Tomorrow’s Digital Ecosystems”, this prestigious event brings together the brightest minds shaping the future of intelligent data.
Key Reasons to Attend:
1. Cutting-Edge Scientific Sessions
Explore 20+ thought-provoking sessions covering AI-driven analytics, predictive modelling, data governance, IoT data integration, block chain analytics, real-time stream processing, and more.
2. World-Class Speakers
Hear from globally renowned data scientists, AI experts, academicians, and industry leaders who are revolutionizing how we understand and apply data.
3. Hands-On Learning
Gain practical skills in big data tools, cloud-based analytics, machine learning, and data visualization through interactive workshops and technical demonstrations.
4. Networking Opportunities
Connect with a diverse community of data professionals, entrepreneurs, researchers, policymakers, and students from across the globe. Forge collaborations and grow your professional network.
5. Industry-Academia Exchange
Bridge the gap between academic innovation and industry implementation. Discover how data analytics is transforming finance, healthcare, retail, transportation, and smart cities.
6. Paper Presentations & Poster Sessions
Showcase your research, receive peer feedback, and contribute to the global body of knowledge in big data science and AI-powered decision-making.
7. Publication & Recognition
Selected papers will be published in indexed journals and conference proceedings, giving your work visibility and recognition among global peers.
8. Explore Amsterdam
Beyond sessions, explore the scenic canals, rich history, and vibrant culture of Amsterdam — one of Europe’s most innovative and beautiful cities.
Who Should Attend?
-
Data Scientists & Engineers
-
AI/ML Practitioners
-
Business Intelligence Experts
-
Academicians & Researchers
-
IT & Cloud Architects
-
Government & NGO Analysts
-
Startups & Innovators
-
Graduate Students in Data & AI Fields
Explore scalable deep learning frameworks that power real-time data analytics across industries. This session highlights innovations in neural network optimization, transfer learning, and large-scale training for image, video, and language datasets. Discover how AI-driven models process massive datasets with cloud-native infrastructures and distributed computing. Ideal for data scientists and ML engineers working on deep learning pipelines, edge AI, and NLP applications in big data environments. Keywords: deep learning, scalable AI, big data models, distributed neural networks.
This session focuses on federated learning systems that train models across distributed edge devices without compromising user data. It covers secure data exchange, edge analytics, and real-time AI for smart devices and IoT. Understand how privacy-preserving AI enables compliance with GDPR and HIPAA. Explore tools for collaborative model training at the network edge. Keywords: federated learning, edge AI, decentralized analytics, data privacy, GDPR, IoT analytics.
Learn about high-velocity data stream processing with Apache Kafka, Flink, and Spark Streaming. This session dives into architectures for real-time analytics, predictive modelling, and dynamic event detection in industries like finance, logistics, and cybersecurity. Discover how AI models make instant decisions from live data pipelines. Keywords: real-time analytics, data streaming, predictive intelligence, event processing, Apache Kafka.
Explore the development of transparent, fair, and auditable AI models in big data ecosystems. Topics include bias detection, algorithm interpretability, and model explain ability using SHAP, LIME, and XAI frameworks. Learn how enterprises ensure ethical AI deployment in critical domains like healthcare, finance, and public policy. Keywords: explainable AI, XAI, algorithmic bias, responsible AI, AI ethics.
This session addresses how big data analytics supports environmental sustainability, carbon footprint tracking, and climate forecasting. Learn how satellite data, remote sensing, and AI-driven climate models contribute to disaster prediction and ESG strategies. Ideal for researchers in environmental science and smart city development. Keywords: climate analytics, sustainability, ESG data, remote sensing, environmental big data.
Dive into the intersection of quantum computing and big data analytics. Explore how quantum algorithms accelerate complex problem-solving in data clustering, pattern recognition, and optimization. Learn about quantum machine learning and its transformative potential in finance, drug discovery, and supply chain. Keywords: quantum computing, QML, big data optimization, quantum analytics, future of AI.
Understand how data mesh and data fabric frameworks decentralize and streamline data access across global enterprises. This session covers best practices, metadata management, governance, and self-service analytics at scale. Discover how businesses evolve from monolithic data lakes to intelligent ecosystems. Keywords: data mesh, data fabric, enterprise data architecture, self-service analytics.
Explore the role of generative AI (e.g., GANs, diffusion models) in creating synthetic datasets for training robust AI systems. Learn how synthetic data improves model accuracy, privacy, and bias mitigation, especially in regulated sectors. Gain hands-on insights into tools for generating high-fidelity artificial datasets. Keywords: generative AI, synthetic data, model training, GANs, AI data generation.
Discover how organizations manage data quality, lineage, security, and compliance through AI-powered governance platforms. This session covers tools and strategies for ensuring accountability and aligning with global data protection regulations. Focus on risk management in high-volume data environments. Keywords: data governance, compliance, AI regulation, data ethics, privacy laws.
Dive into big data applications in genomics, medical imaging, and patient analytics. Explore how AI enables early disease detection, personalized therapies, and hospital resource optimization. Real-world use cases include cancer prognosis, wearable health devices, and drug discovery pipelines. Keywords: AI in healthcare, precision medicine, medical big data, genomic analytics, health tech.
Explore how cities harness big data from sensors, traffic systems, and urban IoT networks to make data-informed decisions. Learn about AI applications in public safety, waste management, energy optimization, and citizen services. See case studies on building smart, resilient urban ecosystems. Keywords: smart cities, urban analytics, IoT in cities, smart governance, AI urban planning.
Discover how NLP models like BERT, GPT, and LLaMA are transforming text analysis in business intelligence, customer feedback, and document processing. Learn best practices in deploying large language models for unstructured data at scale. Keywords: NLP, language models, unstructured data, BERT, enterprise text analytics.
Uncover how big data and AI detect financial fraud, optimize portfolios, and automate trading strategies. Focus on risk modelling, anomaly detection, and real-time transaction analysis in banks, fintech, and insurance. Keywords: financial analytics, AI in fintech, fraud detection, big data finance, risk analytics.
Compare data lake, Lake House, and warehouse architectures optimized for AI workloads. Discuss technologies like Delta Lake, Snowflake, and Apache Iceberg. Focus on performance, cost, and integration with ML tools. Keywords: data lake house, Delta Lake, AI storage, data warehouse, cloud storage solutions.
This track focuses on using machine learning to detect cyber threats, analyse network anomalies, and predict attacks. Explore automated defence systems, anomaly detection, and AI SOC tools. Keywords: AI cybersecurity, threat detection, cyber analytics, machine learning security, predictive defence.
Learn how to integrate and visualize data from diverse sources—text, images, IoT, video, and sensors. Explore dashboards, VR, and AR analytics tools for decision-makers. Keywords: multimodal analytics, data visualization, data fusion, dashboards, interactive analytics.
Explore infrastructure automation for data science workflows using containerization, Kubernetes, and server less computing. Learn how to scale analytics efficiently in hybrid cloud environments. Keywords: big data infrastructure, Kubernetes, containerized analytics, server less data pipelines.
Understand how AI predicts customer behaviour, optimizes pricing, and personalizes shopping experiences using big data. Focus on recommendation systems, sentiment analysis, and customer journey mapping. Keywords: AI in retail, customer analytics, personalization, behavioural big data, sentiment AI.
Explore how data analytics is reshaping online education, adaptive learning platforms, and student performance tracking. Topics include AI tutors, learning path optimization, and educational data mining. Keywords: learning analytics, EdTech, AI in education, student data, adaptive learning.
This session features cross-sector AI success stories—healthcare, agriculture, logistics, manufacturing, and government. Explore frameworks, ROI strategies, and ethical deployment of AI at scale. Keywords: enterprise AI, cross-industry innovation, AI integration, AI ROI, transformation strategy.
Participation Options:
Data Analysis 2025 Conference provides the participants with different modes or ways to participate such as Delegate or Speaker under ACADEMIC / STUDENT / BUSINESS Category. Mode of participation is Online through Power Point Presentation/ Video Presentation on Cisco Webinars.
-
Keynote speaker: 45-50 minutes
-
Speaker (oral presentation): 25-30 minutes (only one person can present)
-
Speaker (workshop): 45-50 minutes (more than 1 can present)
-
Speaker (special session): 45-50 minutes (more than 1 can present)
-
Speaker (symposium): more than 45 minutes (more than 1 can present)
-
Delegate (only registration): will have access to all the sessions with all the benefits of registration
-
Poster presenter: can present a poster and enjoy the benefits of delegate
-
Remote attendance: can participate via video presentation or e-poster presentation
-
Exhibitor: can exhibit his/her company’s products by booking exhibitor booths of different sizes
-
Media partner
-
Sponsor
-
Collaborator
Benefits of Joining Conference:
-
Get your abstract published with DOI
-
Get Certified for your participation
-
Reduced Costs Affordability
-
Knock Down Geographical Barriers
-
Convenience from comfort of your own home or from work
-
They’re Archived: Ability to view events in the recording
-
Great resource for learning new career skills
-
Learn from the Pros
-
Global exposure to your research
-
Make new connections
-
Significant time saving
-
Wider Reach
-
Position yourself as the expert
-
Get your abstracts published with unique DOI in International Journals
-
Get up to 50% discounts for publishing your entire article in our open access International Journals
-
Get Handbooks and conference kits
-
Get an access to the network with eminent personalities from worldwide
1. Global Market Growth Trend (2020–2025)
The global Big Data & Data Analytics market is projected to reach USD 624.2 billion by the end of 2025, up from USD 168 billion in 2020. This surge is fueled by exponential growth in AI adoption, cloud computing, and IoT integration across industries like healthcare, finance, manufacturing, and smart cities.
2. AI-Powered Analytics Driving the Ecosystem
AI is no longer optional in analytics—it is foundational. From real-time decision-making to deep learning pattern detection, AI-powered analytics enable hyper-personalization, anomaly detection, and automation across datasets at scale. The 2025 trend sees businesses moving toward AI-as-a-Service (AIaaS) models for embedded intelligence.
3. Rising Demand for Real-Time, Edge-Based Data Processing
With 5G rollouts and edge computing, companies now demand near-zero latency in data processing. Industries like autonomous vehicles, telemedicine, and smart factories require real-time analytics without relying solely on centralized cloud models. This shift enhances performance, privacy, and security.
4. Growing Emphasis on Ethical AI & Data Governance
As regulations like GDPR, Digital Services Act, and AI Act evolve, ethical data usage is becoming central. Enterprises are investing in transparent, explainable AI systems that comply with governance models and uphold user privacy. This also increases trust and long-term sustainability.
5. Sector-Wise Impact of Big Data in 2025
|
Industry
|
|
2025 Market Value (USD Billion)
|
Use Cases
|
|
Healthcare
|
|
92.5
|
Predictive diagnostics, clinical AI
|
|
BFSI
|
|
78.2
|
Fraud detection, credit scoring
|
|
Retail & eCom
|
|
65.9
|
Customer analytics, demand forecasting
|
|
Manufacturing
|
|
53.6
|
Smart factories, predictive maintenance
|
|
Government
|
|
46.4
|
Smart cities, citizen data management
|
6. Regional Market Share & Growth (2025)
|
Region
|
|
Forecast (USD Bn)
|
CAGR (2020–2025)
|
|
North America
|
|
232.5
|
14.1%
|
|
Europe
|
|
148.7
|
13.4%
|
|
Asia-Pacific
|
|
129.3
|
16.2%
|
|
Latin America
|
|
53.6
|
12.3%
|
|
MEA
|
|
60.1
|
11.8%
|
Europe, especially cities like Amsterdam, is fast becoming a data innovation hub due to government support, skilled workforce, and secure digital infrastructure.
The 24th International Conference on Big Data & Data Analytics 2025 is not just a conference—it’s a strategic marketplace of innovation, aligning business leaders, scientists, and AI pioneers toward building tomorrow’s smart digital ecosystems. Don’t miss your chance to be part of the AI-driven data transformation shaping the global economy.
Data Analysis-2025 | Big Data & Data Analytics | Data Analysis conferences-2025 | Big Data conferences | Data Analysis conferences | ICBDDA-2025 | Data Analysis 2025 | Conference Series | Upcoming Big Data Conferences | Amsterdam | Netherlands | 2025
Visa Process for the Data Analysis 2025
Visa process Guildlines:
Here’s a step-by-step guide to help you navigate the Schengen visa process for attending the 24th International Conference on Big Data & Data Analytics on December 11-12, 2025 in Amsterdam, Netherlands:
1. Choose the Right Visa
-
You'll need a short-stay Schengen Type C visa for business purposes, since you're attending a professional conference in Netherlands.
2. Required Documents
-
Valid passport
-
Two recent facial photos
-
Conference invitation letter
-
Proof of registration/payment
-
Cover letter stating purpose, trip dates, funding, etc.
-
Proof of accommodation in Amsterdam
-
Round-trip flight itinerary
3. Application Timeline
-
Apply for your Schengen visa between 6-8 weeks before and at least 15 calendar days before departure, as processing takes about 15 calendar days
4. Appointment Booking
-
Netherlands now requires mandatory online appointment booking via the Netherlands Visa Application Centre (VFS Global) platform—you must complete your application through your Netherlands-Visas account, book your appointment online, and then visit VFS Global in your region on the scheduled date.
5. Biometrics & Interview
-
Attend the VFS centre for biometric data submission (fingerprints and photo), unless provided within the last 59 months, and be prepared for a brief interview, especially if this is your first trip for a conference.
6. After Submission
-
Track your visa application through the VFS tracking portal, and you’ll be notified once your passport and visa are ready for pickup.
The 23rd International Conference on Big Data & Data Analytics, held on July 25–26, 2024, in Amsterdam, Netherlands, was a resounding success, drawing an international gathering of over 400 participants from more than 30 countries. Organized under the central theme “Data-Driven Futures: Unlocking Insights through Innovation,” the conference served as a dynamic platform for knowledge exchange, industry-academic collaboration, and exploration of emerging technologies in big data and analytics. The event brought together leading researchers, data scientists, academicians, business intelligence experts, and technology innovators to discuss the transformative impact of big data in a rapidly evolving digital world. The inaugural session commenced with a welcome address by the organizing chair. The two-day conference featured more than 50 scientific and technical sessions covering a wide range of tracks, including AI-powered analytics, data mining and visualization, real-time data processing, cloud computing, cybersecurity, NLP and sentiment analysis, healthcare and biomedical data, industrial IoT, and smart city applications. Sessions were structured to reflect both theoretical advances and real-world case studies, creating a balanced exchange of ideas. In addition to oral presentations, 25 poster sessions were hosted, encouraging interaction between young researchers and senior scientists. Two pre-conference workshops were also conducted—one on data visualization using Tableau and Power BI, and the other on predictive modeling and machine learning using Python and Apache Spark. These workshops were met with great enthusiasm, especially from early-career professionals and students, as they offered practical exposure to high-demand tools and methodologies. A significant highlight of the conference was the panel discussions that focused on pressing issues in data science today. One panel explored the challenges of ethical AI and responsible data use, while another addressed real-time analytics in high-stakes industries like finance, healthcare, and emergency response. The third panel dealt with cross-border data sharing, open data policies, and the growing demand for harmonized data governance frameworks. These discussions offered actionable insights for policy-makers, tech leaders, and academic institutions looking to align with global data ethics standards. Alongside the academic program, the tech exhibition segment featured industry booths from major companies such as IBM, SAP, TIBCO, Oracle, and several data analytics startups. These booths showcased the latest innovations in analytics software, cloud services, and AI-driven platforms, giving attendees the opportunity to experience hands-on demonstrations and engage with product developers and data engineers. Several business partnerships and academic-industry collaborations were initiated during these sessions. The event was marked by a vibrant exchange of ideas, fostering connections between data scientists and decision-makers across diverse sectors. Many participants praised the conference’s interdisciplinary approach, with topics bridging not only technical domains but also policy, ethics, and human-centered design. Informal networking sessions, such as the welcome reception and conference dinner cruise through Amsterdam’s historic canals, further enriched the experience, offering cultural immersion and deeper peer engagement. Overall, the 23rd International Conference on Big Data & Data Analytics achieved its goal of pushing the boundaries of data science, fostering international dialogue, and promoting responsible innovation. It underscored the critical role of data in shaping future societies and industries, while also highlighting the importance of ethical considerations and collaborative problem-solving. The organizing committee extended heartfelt thanks to all keynote speakers, session chairs, participants, sponsors, and partners for making the event a memorable and impactful success. The next edition, the 24th International Conference, is scheduled for December 11–12, 2025, again in Amsterdam, and will focus on the theme “AI-Powered Analytics: Shaping Tomorrow’s Digital Ecosystems.”
For more details contact
Program manager | Data Analysis 2025
Data Analysis-2025 | Big Data & Data Analytics | Data Analysis conferences-2025 | Big Data conferences | Data Analysis conferences | ICBDDA-2025 | Data Analysis 2025 | Conference Series | Upcoming Big Data Conferences | Amsterdam | Netherlands | 2025
Chang Yen-Jung
Hongfei Li
Bertrand Hassani
Eleni Rozaki
Ron Erickson
Bennett B. Borden
Andrew A. Goldenberg
Nikolaos Freris
Sophia Tsoka
Åukasz Augustyniak
Ergi Sener
Thomas Sterling
