CS 157B: Database Management Systems II May 8 Class Meeting Department of Computer Science San Jose State University Spring 2013 Instructor: Ron Mak www.cs.sjsu.edu/~mak.

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Presentation transcript:

CS 157B: Database Management Systems II May 8 Class Meeting Department of Computer Science San Jose State University Spring 2013 Instructor: Ron Mak

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 2 Final Exams Next Week  Section 1 Thursday, May 16 12:15-2:30 PM MacQuarrie Hall, room 222  Section 2 Wednesday, May 15 5:15-7:30 PM MacQuarrie Hall, room 222  Test how well you understand the material. Similar to the midterms.  Bring your laptops!

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 3 Postmortem Reports  Short report on: What did you learn from the class? Was it useful? What did you do for your team projects and how well. What did your teammates do and how well.  A few paragraphs, can be just an message.  Due Monday, May 13. _

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 4 Semester Review  Conceptual, logical, and physical data models Primary and foreign keys First and second normal forms One-to-one, one-to-many, and many-to-many associations Entity-relationship (ER) diagrams  Referential integrity Cascade policy _

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 5 Semester Review  Hibernate Mapping Java classes to database tables using annotations Lazy and eager fetching Mapping inheritance hierarchies Hibernate Query Language (HQL)  Criteria API Query-by-Example (QBE) Restrictions Chaining criteria

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 6 Semester Review  Well-formed XML documents XML namespaces  Parsing XML documents with Java DOM, SAX, and StAX parsers  XPath Location paths, axes, expressions, and functions  XML Schema Simple and complex types, attributes Valid XML documents

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 7 Semester Review  Object-XML mapping Marshalling and unmarshalling data Java JAXB packages xjc compiler  XQuery FLOWR expressions User-defined XQuery functions  XSLT Transform XML documents for-each, if, choose, current node, sort, count() templates, apply-template

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 8 Semester Review  Web Services Description Language (WSDL) Service contract Service-Oriented Application Protocol (SOAP) messages  Web service provider Deploy to a URL using the “publisher” utility or Tomcat  Web service client Connect to an existing web service Download and process the WSDL service contract wsimport  NetBeans support for developing web service providers and clients

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 9 Semester Review  Data warehousing Purpose Extract, Transform, and Load (ETL) Data marts  Business Intelligence IBM Cognos  Dimensional modeling Star schema Fact table Dimension tables

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 10 Semester Review  Online Analytical Processing (OLAP) Select dimensions Drill up and drill down Slice and dice Pivot  Data mining Predictive analytics Search for patterns _

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 11 Semester Review  Data virtualization Composite Information Server and Composite Studio  Disparate data sources Database XML Web services Excel Flat files (CSV, etc.)  Virtual views Create using Studio Publish and access with client applications

Department of Computer Science Spring 2013: May 8 CS 157B: Database Management Systems II © R. Mak 12 Semester Review  Unstructured data  Content management systems Metadata  The bottom line: Not all data lives in databases. You must be able to handle disparate data sources if you want to be successful in today’s Big Data environment.