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teaching:infoh419 [2022/09/19 15:29] ezimanyi [Groups of the current year] |
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| * Analytical queries involve aggregations (min, max, avg, ...) over large subgroups of the data; | * Analytical queries involve aggregations (min, max, avg, ...) over large subgroups of the data; | ||
| * When analyzing data it is convenient to see it as multi-dimensional. | * When analyzing data it is convenient to see it as multi-dimensional. | ||
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| For these reasons, data to be analyzed is typically collected into a data warehouse with Online Analytical Processing support. Online here refers to the fact that the answers to the queries should not take too long to be computed. Collecting the data is often referred to as Extract-Transform-Load (ELT). The data in the data warehouse needs to be organized in a way to enable the analytical queries to be executed efficiently. For the relational model star and snowflake schemes are popular designs. Next to OLAP on top of a relational database (ROLAP), also native OLAP solutions based on multidimensional structures (MOLAP) exist. In order to further improve query answering efficiency, some query results can already be materialized in the database, and new indexing techniques have been developped. | For these reasons, data to be analyzed is typically collected into a data warehouse with Online Analytical Processing support. Online here refers to the fact that the answers to the queries should not take too long to be computed. Collecting the data is often referred to as Extract-Transform-Load (ELT). The data in the data warehouse needs to be organized in a way to enable the analytical queries to be executed efficiently. For the relational model star and snowflake schemes are popular designs. Next to OLAP on top of a relational database (ROLAP), also native OLAP solutions based on multidimensional structures (MOLAP) exist. In order to further improve query answering efficiency, some query results can already be materialized in the database, and new indexing techniques have been developped. | ||
| - | In the course, the main concepts of multidimensional databases will be covered and illustrated using the SQL Server tools. Complimentary to the course, IBM and Teradata will give invited lectures. | + | In the course, the main concepts of multidimensional databases will be covered and illustrated using the SQL Server tools. |
| ===== Books ===== | ===== Books ===== | ||
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| ===== Software ===== | ===== Software ===== | ||
| - | All software used in the course is available in the computer labs. Students who wish a personal copy of the software on their own computers, can get free copies of the software. Succinct instructions to acquire the software have been included below; in case additional help is required you can contact the sysadmin of the department: Robin Choquet <alesuiss@ulb.ac.be> | + | All software used in the course is available in the computer labs. Students who wish a personal copy of the software on their own computers, can get free copies of the software. Succinct instructions to acquire the software have been included below; in case additional help is required you can contact the sysadmin of the department: Robin Choquet <Robin.Choquet@ulb.be> |
| * MS SQL Server Tools: can be downloaded for free from http://www.academicshop.be/msdnaa/ Register on this page with your ULB email address, and 'order' the free msdnaa. After verification you receive login credentials to download quite a few software packages for free. Select the SQL Server 2014 Enterprise edition. | * MS SQL Server Tools: can be downloaded for free from http://www.academicshop.be/msdnaa/ Register on this page with your ULB email address, and 'order' the free msdnaa. After verification you receive login credentials to download quite a few software packages for free. Select the SQL Server 2014 Enterprise edition. | ||
| - | * Indyco Builder can be downloaded from http://www.indyco.com/ . License keys for all students will be added soon. | ||
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| ===== Groups of the current year ===== | ===== Groups of the current year ===== | ||
| - | * Spark SQL: Luis Alfredo Leon, Satria Bagus Wicaksono, Jezuela Gega, Isabella Forero | + | * Spark SQL: Luis Alfredo Leon, Satria Bagus Wicaksono, Jezuela Gega, Isabella Forero |
| + | * MySQL: Ali AbuSaleh, Liliia Aliakberova, Muhammad Rizwan Khalid, Mariana Mayorga Llano | ||
| + | * PostgreSQL: Mir Wise Khan, Rishika Gupta, Ahmad, Chidiebere Ogbuchi | ||
| + | * Oracle: Sayyor Yusupov, Nikola Ivanović, Bogdana Živković, Jose Antonio Lorencio Abril | ||
| + | * MariaDB: Prashant Gupta, Abd Alrhman Abu Sbeit, Maren, TBD. | ||
| ===== Examinations from Previous Years ===== | ===== Examinations from Previous Years ===== | ||