ΟΙΚΟΝΟΜΟΤΕΧΝΙΚΗ SEMINARS SA
Who should attend :
The seminar is ideal for IT professionals and software engineers who work on any issues related to data management. The seminar covers a broad set of topics to provide
insights about how data systems work and how they are designed. In this way, it allows one to make better choices regarding which systems to chose depending on the
target data, queries and hardware. In addition, it gives insights to software engineers about best practices and modern system design approaches.
What are the learning outcomes?
• To become familiar with the history and evolution of data systems design over the past 4-5 decades.
• To understand the basic tradeoffs in designing and implementing modern data systems and access methods through a step-by-step hands-on experience.
• To be able to argue about the design a new data system given a data-driven scenario and build a functional prototype.
• To be able to understand which data system is a good fit given the needs of an application.
1. Introduction to Data Systems
Basic Properties and Features, Query Languages, Declarative Interfaces, Modularity
2. Modern Hardware and its Side-effects
Deep Memory Hierarchies, The Memory Wall, Multi-core, SIMD
3. Introduction to Data System Design
Data Layouts, Column/Row/Hybrid Layouts, Tradeoffs for Read/Memory/Update performance, Query plans and Optimization, Engineering Optimizations
4. Big Data Systems and System Fusion
Key-value stores, Graph stores, NoSQL, NewSQL and Hybrid Designs
5. Open Challenges and Next Wave of Innovation
Adaptivity, Massive Scale Monitoring, Hardware/software Co-design
is a professor of Computer Science at Harvard University where he leads DASlab, the Data Systems Laboratory@Harvard SEAS. Stratos works on data system architectures with emphasis on how we can make it easy to design efficient data systems as applications and hardware keep evolving and on how we can make it easy to use these systems even for non-experts. For his doctoral work on Database Cracking, Stratos won the 2011 ACM SIGMOD Jim Gray Doctoral Dissertation award for best thesis world-wide in data management. In 2011 he also won the ERCIM Cor Baayen award and was named “most promising young European researcher in computer science and applied mathematics” by the European Research Consortium for Informatics and Mathematics . He is also a recipient of an IBM zEnterpise System Recognition Award, a VLDB Challenges and Visions best paper award and an NSF Career award by the US National Science Foundation. In 2015 he was awarded the IEEE TCDE Early Career Award from the IEEE Technical Committee on Data Engineering for his work on adaptive data systems.
Επικοινωνία / Δηλώσεις Συμμετοχής:
Tηλ.: 210 52 27 094, 210 52 84 325,