252-0834-00L  Information Systems for Engineers

SemesterAutumn Semester 2021
LecturersG. Fourny
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
252-0834-00 VInformation Systems for Engineers
Online lecture: This lecture will primarily take place online. Reserved rooms will remain blocked on campus for students to follow the course from there.
2 hrs
Fri14:15-16:00HG E 5 »
G. Fourny
252-0834-00 UInformation Systems for Engineers
Groups are selected in myStudies.
1 hrs
Fri16:00-17:00ON LI NE »
16:00-17:00ON LI NE »
16:00-17:00ON LI NE »
16:15-17:00CAB G 52 »
16:15-17:00CAB G 56 »
16:15-17:00CAB G 57 »
16:15-17:00CAB G 59 »
G. Fourny

Catalogue data

AbstractThis course provides the basics of relational databases from the perspective of the user.

We will discover why tables are so incredibly powerful to express relations, learn the SQL query language, and how to make the most of it. The course also covers support for data cubes (analytics).
ObjectiveThis lesson is complementary with Big Data for Engineers as they cover different time periods of database history and practices -- you can take them in any order, even though it might be more enjoyable to take this lecture first.

After visiting this course, you will be capable to:

1. Explain, in the big picture, how a relational database works and what it can do in your own words.

2. Explain the relational data model (tables, rows, attributes, primary keys, foreign keys), formally and informally, including the relational algebra operators (select, project, rename, all kinds of joins, division, cartesian product, union, intersection, etc).

3. Perform non-trivial reading SQL queries on existing relational databases, as well as insert new data, update and delete existing data.

4. Design new schemas to store data in accordance to the real world's constraints, such as relationship cardinality

5. Explain what bad design is and why it matters.

6. Adapt and improve an existing schema to make it more robust against anomalies, thanks to a very good theoretical knowledge of what is called "normal forms".

7. Understand how indices work (hash indices, B-trees), how they are implemented, and how to use them to make queries faster.

8. Access an existing relational database from a host language such as Java, using bridges such as JDBC.

9. Explain what data independence is all about and didn't age a bit since the 1970s.

10. Explain, in the big picture, how a relational database is physically implemented.

11. Know and deal with the natural syntax for relational data, CSV.

12. Explain the data cube model including slicing and dicing.

13. Store data cubes in a relational database.

14. Map cube queries to SQL.

15. Slice and dice cubes in a UI.

And of course, you will think that tables are the most wonderful object in the world.
ContentUsing a relational database
=================
1. Introduction
2. The relational model
3. Data definition with SQL
4. The relational algebra
5. Queries with SQL

Taking a relational database to the next level
=================
6. Database design theory
7. Databases and host languages
8. Databases and host languages
9. Indices and optimization
10. Database architecture and storage

Analytics on top of a relational database
=================
12. Data cubes

Outlook
=================
13. Outlook
Literature- Lecture material (slides).

- Book: "Database Systems: The Complete Book", H. Garcia-Molina, J.D. Ullman, J. Widom
(It is not required to buy the book, as the library has it)
Prerequisites / NoticeFor non-CS/DS students only, BSc and MSc
Elementary knowledge of set theory and logics
Knowledge as well as basic experience with a programming language such as Pascal, C, C++, Java, Haskell, Python

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
In examination block forBachelor's Degree Programme in Computational Science and Engineering 2016; Version 27.03.2018 (Examination Block G2)
Bachelor's Programme in Computational Science and Engineering 2012; Version 13.12.2016 (Examination Block G2)
ECTS credits4 credits
ExaminersG. Fourny
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 150 minutes
Additional information on mode of examinationWorking on the exercises is rewarded in the sense of ETH's continuous performance assessment with up to 0.25 bonus points. In principle, it is expected that students solve all exercises. In order to control this, the assignments will be collected in 3 weeks of the semester, announced in advance. Those who successfully solve ast least 2 of these 3 weeks of assignments get 0.25 extra points at the exam.
The examination may be computer-based.
Written aidsGeneral dictionaries are allowed.
Online examinationThe examination may take place on the computer.
Distance examinationIt is not possible to take a distance examination.
If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkInformation
RecordingAll lectures are recorded and made available on YouTube
LiteratureDatabases, The Complete Book
Only public learning materials are listed.

Groups

252-0834-00 UInformation Systems for Engineers
GroupsG-01
Fri16:15-17:00CAB G 52 »
G-02
Fri16:15-17:00CAB G 56 »
G-03
Fri16:15-17:00CAB G 57 »
G-04
Fri16:15-17:00CAB G 59 »
G-05
Fri16:00-17:00ON LI NE »
G-06
Fri16:00-17:00ON LI NE »
G-07
Fri16:00-17:00ON LI NE »

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Computational Biology and Bioinformatics MasterTheoryWInformation
DAS in Data ScienceBig Data SystemsWInformation
Electrical Engineering and Information Technology BachelorEngineering ElectivesWInformation
Computer Science (General Courses)Computer Science for Non-Computer ScientistsZInformation
Integrated Building Systems MasterSpecialised CoursesWInformation
Mechanical Engineering MasterEnergy, Flows and ProcessesWInformation
Mechanical Engineering MasterMechanics, Materials, StructuresWInformation
Mechanical Engineering MasterRobotics, Systems and ControlWInformation
Mechanical Engineering MasterMicro & NanosystemsWInformation
Mechanical Engineering MasterBioengineeringWInformation
Mechanical Engineering MasterDesign, Computation, Product Development & ManufacturingWInformation
Physics MasterGeneral ElectivesWInformation
Computational Science and Engineering BachelorElectivesWInformation