1. Modern Data Management
From traditional data management to modern
data management
Many technological changes
Networks
Parallelism (Cluster computing & Multicore)
Storage systems
Processor technology
New applications
Web apps
Streaming data apps
Business analysis
Non-business apps

2. New applications Very large amounts of data Very volatile data
Data as streams
Data is not always structured in the database sense
Uncertain data …

3. Challenges! Distribution
Data management infrastructure
Distribution
Query optimization (case of a sensor network)–parallel processing
Intelligent indexing
Stream processing
Data quality
Semantics of Data
Intelligent interaction and information discovery
Tools for data analysis
Integrating symbolic computation, mining and analysis
Data visualization and application development …

4. Presentations
Agile data management challenges in enterprise big data landscapes (by Eric Simon)
Unification of the management of both enterprise data and big data
Governance at scale of an enterprise big data landscape through a unified view
Development of an environment for the creation of analytics by the masses
Querying and Exploring Big Scientific Data (by Thomas Heinis)
Brain simulation data : challenges for data management systems
Neurosciences - Simulation of human brain : new approach (indexing and navigation)
Benchmarking SQL-On-MapReduce systems (by Mohand-Saïd Hacid)
SQL MapReduce Systems for large data sets
A new architecture (BSP (Bulk Synchronous Processing)- based)