Scope

DaWaK conference is a high-quality forum for researchers, practitioners and developers in the field of Big Data Analytics, in a broad sense. The objective is to explore, disseminate and exchange knowledge in this field through scientific and industry talks. The conference covers all aspects of DAWAK research and practice, including data lakes, database design (data warehouse design, ER modelling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, text and data mining techniques, and deep learning.

Topics of Interest

The conference will bring together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide. Main topics include:

Theoretical models for data storage
Integration of databases and neural networks
Conceptual model foundations for big data
Parallel and scalable data processing
Distributed and parallel system architectures
Query processing and optimization
Semantics for big data
Data fabric and data lake architectures
Data Pre-processing and data cleaning
Polystore and multistore architectures
SQL alternatives: NoSQL, NewSQL, JSON
Cloud infrastructure; containers, virtualization
Metadata for big data frameworks
Big data storage and indexing
Mobile applications
Large-scale AI/ML for Multimodal dataa
Data Science workflows
Analytics on Large Graphs
Large-scale unstructured, semi-structured data
Data streams: networking and sensor data
Trustworthy AI on Data Lakes, Data Grid and Data Fabric
Deep learning on large data sets