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