Project description
A toolkit for sustainable data lakes
Data lakes store large amounts of structured, semi-structured and unstructured data, facilitating flexible, self-service analytics for fast and ad hoc decision-making. The EU-funded SmartDataLake project will empower extreme-scale analytics over sustainable Big Data lakes. It will provide an adaptive, scalable and flexible toolkit to manage data lakes. This toolkit will offer data virtualisation for abstracting and optimising queries over heterogeneous data, while enabling automated data placement in different storage tiers. It will also offer data synopses for approximate query answering and visual analytics. The data lake contents will be modeled and organised as a heterogeneous information network, including different types of entities and relations. SmartDataLake will assess the results in real-world use cases from the business intelligence domain.
Objective
Data lakes are raw data ecosystems, where large amounts of diverse data are retained and coexist. They facilitate self-service analytics for flexible, fast, ad hoc decision making. SmartDataLake enables extreme-scale analytics over sustainable big data lakes. It provides an adaptive, scalable and elastic data lake management system that offers: (a) data virtualization for abstracting and optimizing access and queries over heterogeneous data, (b) data synopses for approximate query answering and analytics to enable interactive response times, and (c) automated placement of data in different storage tiers based on data characteristics and access patterns to reduce costs. The data lake’s contents are modelled and organised as a heterogeneous information network, containing multiple types of entities and relations. Efficient and scalable algorithms are provided for: (a) similarity search and exploration for discovering relevant information, (b) entity resolution and ranking for identifying and selecting important and representative entities across sources, (c) link prediction and clustering for unveiling hidden associations and patterns among entities, and (d) change detection and incremental update of analysis results to enable faster analysis of new data. Finally, interactive and scalable visual analytics are provided to include and empower the data scientist in the knowledge extraction loop. This includes functionalities for: (a) visually exploring and tuning the space of features, models and parameters, and (b) enabling large-scale visualizations of spatial, temporal and network data. The results of the project are evaluated in real-world use cases from the business intelligence domain, including scenarios for portfolio recommendation, production planning and pricing, and investment decision making. SmartDataLake will foster innovation and enable European SMEs to capitalize on the value of their own data lakes.
Fields of science
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
151 25 Maroussi
Greece