Data Becker Einladungs-Druckerei.rarl !EXCLUSIVE!
DOWNLOAD ===> https://bytlly.com/2t2yxE
Students can explain the general architecture of an application system that is based on a database. They describe the syntax and semantics of the Entity Relationship conceptual modeling languages, and they can enumerate basic decision problems and know which features of a domain model can be captured with ER and which features cannot be represented. Furthermore, students can summarize the features of the relational data model, and can describe how ER models can be systematically transformed into the relational data model. Student are able to discuss dependency theory using the operators of relational algebra, and they know how to use relational algebra as a query language. In addition, they can sketch the main modules of the architecture of a database system from an implementation point of view. Storage and index structures as well as query answering and optimization techniques can be explained. The role of transactions can be described in terms of ACID conditions and common recovery mechanisms can be characterized. The students can recall why recursion is important for query languages and describe how Datalog can be used and implemented.They demonstrate how Datalog can be used for information integration. For solving ER decision problems the students can explain description logics with their syntax and semantics, they describe description logic decision problems and explain how these problems can be mapped onto each other. They can sketch the idea of ontology-based data access and can name the main complexity measure in database theory. Last but not least, the students can describe the main features of XML and can explain XPath and XQuery as query languages.
Students can apply ER for describing domains for which they receive a textual description, and students can transform relational schemata with a given set of functional dependencies into third normal form or even Boyce-Codd normal form. They can also apply relational algebra, SQL, or Datalog to specify queries. Using specific datasets, they can explain how index structures work (e.g., B-trees) and how index structures change while data is added or deleted. They can rewrite queries for better performance of query evaluation. Students can analyse which query language expressivity is required for which application problem. Description logics can be applied for domain modeling, and students can transform ER diagrams into description logics in order to check for consistency and implicit subsumption relations. They solve data integration problems using Datalog and LAV or GAV rules. Students can apply XPath and Xquery to retrieve certain patterns in XML data.
Alle zur Durchführung der Projekte sinnvollen Quellen (Skripte, Fachbücher, Manuals, Datenblätter, Internetseiten). / All sources that are useful for completion of the projects (lecture notes, textbooks, manuals, data sheets, internet pages). 2b1af7f3a8