SmartDataLake SIGNED
Sustainable Data Lakes for Extreme-Scale Analytics
Total Cost €
0EC-Contrib. €
0Partnership
0Views
0SmartDataLake project word cloud
Explore the words cloud of the SmartDataLake project. It provides you a very rough idea of what is the project "SmartDataLake" about.
Project "SmartDataLake" data sheet
The following table provides information about the project.
| Coordinator |
ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS
Organization address contact info |
| Coordinator Country | Greece [EL] |
| Total cost | 3˙945˙450 € |
| EC max contribution | 3˙945˙450 € (100%) |
| Programme |
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)) |
| Code Call | H2020-ICT-2018-2 |
| Funding Scheme | RIA |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-01-01 to 2021-12-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS | EL (MAROUSSI) | coordinator | 853˙125.00 |
| 2 | ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE | CH (LAUSANNE) | participant | 760˙000.00 |
| 3 | TECHNISCHE UNIVERSITEIT EINDHOVEN | NL (EINDHOVEN) | participant | 569˙637.00 |
| 4 | UNIVERSITAT KONSTANZ | DE (KONSTANZ) | participant | 425˙000.00 |
| 5 | RAW LABS SA | CH (LAUSANNE) | participant | 411˙750.00 |
| 6 | SYNYO GmbH | AT (WIEN) | participant | 322˙500.00 |
| 7 | SPAZIODATI SRL | IT (TRENTO) | participant | 302˙500.00 |
| 8 | SPRING TECHNO GMBH & CO KG | DE (BREMEN) | participant | 300˙937.00 |
Map
Project 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.
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The information about "SMARTDATALAKE" are provided by the European Opendata Portal: CORDIS opendata.