1. Advanced Databases Introduction
dr. Toon Calders
prof. dr. Jan Paredaens

2. Outline Motivation for the course Other DH courses
Practical organization
Course topics
Project
Overview of changes

3. Motivation for the Course
Database = a piece of software to handle data:
store,
maintain, and
query
Most ideal system situation-dependent
data type: simple / semi-structured / complex / …
types of queries: simple lookup / analytical / …
type of usage: multi-user / single-user / distributed / … …

4. Motivation for the Course
Relational databases are tuned towards:
simple data
simple, ad-hoc queries
multiple users
Other models are more suitable for other types of data
Object-Oriented,
Deductive,
Semi-Structured Databases,
Data warehouses

5. Motivation for the Course
Study different data models
Advantages, disadvantages
Conceptual level
what are the important notions?
What’s underneath?
In a scientific way
exact, not just claims

6. Motivation for the Course
Student knows:
different database models
Understands:
why they are introduced
conceptual notions
Is able to:
quickly master vendor-specific products

7. Outline Motivation for the course Other DH courses
Practical organization
Course topics
Project
Overview of changes

8. Other DH Courses Relational database systems Other database models
(2ID05) Databases and Data Modelling
(2ID35) Database Technology
transations, indexing, query optimization, distributed DB
Other database models
(2ID45) Advanced Databases
(2II15) Data Mining
(2ID25) Information Retrieval
(2ID99) Capita Selecta DH

9. Outline Motivation for the course Other DH courses
Practical organization
Course topics
Project
Overview of changes

10. Practical Organization
In principle …
Wed 8:45  10:30 Practical session M 1.46
no new material
opportunity to practice, ask questions
together solve exercises
Fri 10:45  12:30 Lectures HG 6.09
XML : Paredaens (6 lectures)
other parts: Calders

11. Practical Organization
Important information
Subscribe to 2ID45 on studyweb !
messages to the whole class group
lecture postponed, room changes, …

12. Practical Organization
Course material
Book:
Silberschatz, Korth, Sudarshan. Database system concepts 5th edition. McGraw-Hill International
Lots of additional material on course webpage
papers
slides
solutions to exercises …

13. Practical Organization
Grades:
70% written exam
30% group project
No project = no grade
Grade for the project can be transfered to August, similar for grade for the exam
Grades expire in August

14. Outline Motivation for the course Other DH courses
Practical organization
Course Topics
Project
Overview of changes

15. Course Topics Limitations of the relational model Deductive databases
Object-Oriented Databases
Data Warehousing & OLAP
Semi-Structured data

16. Limitations of the relational model
Not every query can be expressed
Transitive closure cannot be expressed in Relational Algebra
Give all cities reachable from Antwerp by plane
Give all smallest components of a part
Give all decendants of person X
Not even if you’re very smart …
proof
Extension to other relational query languages

17. Deductive Databases Motivation is two-fold:
add deductive capabilities to databases; the database contains:
facts (intensional relations)
rules to generate derived facts (extensional relations)
Database is knowledge base
Extend the querying
datalog allows for recursion

18. Deductive Databases Datalog as engine of deductive databases
similarities with Prolog
has facts and rules
rules define -possibly recursive- views
Semantics not always clear
safety
negation
recursion

19. Deductive Databases g(a,b). g(b,c). g(a,d). reach(X,X) :- g(X,Y).
reach(X,Y) :- g(X,Y).
reach(X,Z) :- reach(X,Y), reach(Y,Z).
node(X) :- g(X,Y).
node(Y) :- g(X,Y).
unreach(X,Y) :- node(X), node(Y), not reach(X,Y).

20. Deductive Databases In this topic we study:
How to handle negation and recursion in the same program
How to efficiently evaluate Datalog queries

21. OO Databases
Many applications require the storage and manipulation of complex data
design databases
geometric databases …
Object-Oriented programming languages manipulate complex objects
classes, methods, inheritance, polymorphism

22. OO Databases Very simple example:
Class book
set of authors
title
set of keywords
Extremely simple to model in OO language
Hard in relational database!

23. OO Databases
In many applications persistency of the data is nevertheless required
protection against system failure
consistency of the data
Mapping: object in OO language  tuples of atomic values in relational database is often problematic

24. OO Databases Either we ignore the multivalued dependencies
This table is in 3NF, BCNF
Title
Author
Keyword
Database System Concepts
Silberschatz
Database
Korth
Sudarshan
Storage

25. OO Databases Or we go to 4NF Title Author Database System Concepts
Silberschatz
Korth
Sudarshan
Title
Keyword
Database System Concepts
Database
Storage

26. OO Databases Basically OODB = persistent OO programming language
Very important concept
rather uninteresting scientifically
This topic will mainly be self-study
Reading bookchapter + Q & A session

27. Data Warehousing & OLAP
Warehouse
Extract
Transform
Load
Refresh
OLAP Engine
Monitor
&
Integrator
Metadata
Data Sources
Front-End Tools
Serve
Data Marts
Operational
DBs
other
sources
Data Storage
OLAP
Server
Analysis
Query/Reporting
Data Mining
ROLAP
BI applications includes:
Query and Reporting
Online Analytical Processing (OLAP)
Statistical Analysis
Decision Support Systems
Forecasting
Data Mining
Other
Meta data is the data defining warehouse objects. It has the following kinds
Description of the structure of the warehouse
schema, view, dimensions, hierarchies, derived data defn, data mart locations and contents
Operational meta-data
data lineage (history of migrated data and transformation path), currency of data (active, archived, or purged), monitoring information (warehouse usage statistics, error reports, audit trails)
The algorithms used for summarization
The mapping from operational environment to the data warehouse
Data related to system performance
warehouse schema, view and derived data definitions
Business data
business terms and definitions, ownership of data, charging policies

28. Data Warehousing & OLAP
Transaction processing
Operational setting
Up-to-date = critical
Simple data
Simple queries; only « touch » a small part of the database
Flight reservations
ticket sales
do not sell a seat twice
reservation, date, name
Give flight details of X
List flights to Y

29. Data Warehousing & OLAP
Decision support
Off-line setting
« Historical » data
Summarized data
Integrate different databases
Statistical queries
Flight company
Evaluate ROI flights
Flights of last year
# passengers per carrier for destination X
Passengers, fuel costs, maintenance info
Average % of seats sold/month/destination

30. Data Warehousing & OLAP
In this topic we will study:
Conceptual models for decision support
Database explosion problem
Efficient implementation strategies
indexing, view materialization

31. XML Why is XML important? XML is like HTML but
simple open non-proprietary widely accepted data exchange format
XML is like HTML but
no fixed set of tags
X = “extensible”
no fixed semantics (c.q. representation) of tags
representation determined by separate ‘stylesheet’
semantics determined by application
no fixed structure
user-defined schemas
simple: human readable, machine readable
open / non-proprietary: does not belong to Microsoft / IBM etc., documentation is freely available, means also that a lot of (often free) software is already available
widely accepted: W3C standard

32. XML <PersonList Type="Student" Date="2004-12-12">
<Title Value="Student List"/>
<Contents>
<Person>
<Name>Jan Vijs</Name>
<Id>11</Id>
<Address>
<Number>123</Number>
<Street>Turnstreet</Street>
</Address>
</Person>
<Id>66</Id>
<Street>Hole Rd</Street>
</Contents>
</PersonList>

33. XML
In this topic:
XML
XQuery, XSLT
LiXQuery
Taught by prof Paredaens

34. Outline Motivation for the course Other DH courses
Practical organization
Course Topics
Project
Overview of changes

35. Project Pick one of the 4 topics: Formulate your own project
deductive databases / rule-based systems
object-oriented databases
data warehouses
semi-structured databases
Formulate your own project
illustrating the different course concepts
showing you mastered the technology

36. Project Make a project proposal ( WEEK 10 ) Status report ( WEEK 15 )
examples of last year will be given
fulfilling certain constraints
listing technologies to be used
Status report ( WEEK 15 )
Final report ( WEEK 20 )
Project presentations ( WEEKS 21 & 22 )

37. Outline Motivation for the course Other DH courses
Practical organization
Course Topics
Project
Overview of changes

38. Overview of Changes First some facts and figures regarding Spring 2008
Heterogeneous group
Outside NL, HBO, BSc TU/e
CSE
BIS

39. Overview of Changes Some suggestions I decided to act upon:
1. Start with the difficult material:
expressiveness of RA
Gaifman locality
2. Too much time is being spent on XML
(5+5)  (6+3) & topic (XSLT) has been added
3. Disproportional weight given to XML in exam
project no longer exclusively XML

40. Overview of Changes Some suggestions I decided to act upon:
4. Some materials and instruction just too hard
extra exercices will be added; more modular
5. The course was split up in lots of individual subjects, with no apparent relation to one another
tried to handle that in the course motivation

41. Overview of Changes Some suggestions that were ignored:
A google for 'advanced databases' returns quite some courses from other universities that look interesting to me. Perhaps the lecturers could take a look at those.
When (re-)constructing the course last year other universities’ ADB courses were surveyed. Many of the interesting topics are already handled in other courses (Data Mining, Information retrieval, Database technology)

42. Overview of Changes Some suggestions that were ignored:
Don't discuss prerequisite knowledge too much, it is prerequisite.
 Heterogeneous group.
Balance the course subjects more, TC was discussed very specific while the other 3 subjects where treated in global.
 Time spent on TC is justified by its difficulty and its importance for database theory + motivates OODB & Deductive DB

43. Overview of Changes Take-away message
(some?) lecturers do act on questionnaires
filling out the questionnaires is useful

44. Overview of Changes Take-away message
(some?) lecturers do act on questionnaires
filling out the questionnaires is useful

45. Summary Relational model has limitations
simple queries
simple data
OODBs allow complex data types
Deductive databases, datalog complex queries
Somewhere in-between: datawarehouses and OLAP
special requirements, special datastructures
Semi-structured data can be stored in XML
Project complements theoretical lectures
Instructions for clarification

46. !! See you on Friday !!