460-4070/02 – Business Intelligence and Data Warehouses I (BI I)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantordoc. Ing. Michal Krátký, Ph.D.Subject version guarantordoc. Ing. Michal Krátký, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Year1Semestersummer
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRA28 doc. Ing. Michal Krátký, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 2+2
Combined Graded credit 14+0

Subject aims expressed by acquired skills and competences

A student is able to orient in the domain of Business Intelligence and Data Warehousing (DWH), in particular practical knowledge of DWH data modeling methodology, ETL processes and data integration to data warehouses. Moreover, the student knows the methodology and he/she is able to create a reporting layer - data marts for analytics and reporting over data. The student is capable to describe the core basis of necessary data processing and operations with data in DWH database.

Teaching methods

Lectures
Tutorials

Summary

The course is a follow-up to the Database and Information Systems 2 course with focus on applying the knowledge to the domain of Business Intelligence and Data Warehouse. The content of lectures is based on getting familiar with principles of Data Warehousing, data modelling specifics, design of respective layers of a data warehouse, data integration using SQL scripts and ETL tools, data transformations within respective layers of a data warehouse including final aggregations of data in order to be presented as business information in a graphical form and layout, or in a form of data extracts for further processing, where the second part of the course carries on in the next term. Another part of the course is the methodology for the solution design of a DWH and data integration projects. During practical sessions students will make use of the methodology in a practical example of data warehouse design and development in an SQL database environment within scope of their final work.

Compulsory literature:

1. L. T. Moss, Shaku Atre: Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. 576p, Addison-Wesley Professional, 2003.

Recommended literature:

1. R. Kimball, M. Ross: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. 600p, Wiley, 2013. 2. R. Kimball, J. Caserta: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. 528p, Wiley, 2004. 3. C. Batini, M. Scannapieco: Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications). Springer, 2010.

Way of continuous check of knowledge in the course of semester

Partial tasks in topics of lectures are checked on practices.

E-learning

Další požadavky na studenta

Knowledge of the following topics: SQL, procedural extensions of SQL, physical database design, distributed and NoSQL DBMS.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to BI and Data Warehousing 2. Data Warehouses (DWH) - Data modelling principles 3. Data Warehouses - multi-dimensional modelling, data layers - staging, main model, presentation layer (views, indexes). 4. Data Warehouses (DWH) - historization and SCD, using surrogate keys 5. Data marts 6. Operational Data Stores 7. Data Integration - ETL. 8. ETL Framework 9. Data Integration - ETL, transformation definitions - ETL development 10. ETL and Data Integration tools 11. Business Dictionaries and transformation rules 12. Data Quality 13. Analytics over DWH Computer practices: 1. Practicals plan, platform introduction, sample databases. 2. Data modeling of tables and views in DWH. 3. Creation of DWH layers 4. Data historization, data indexing, surrogate keys creation 5. Fine tuning - querying (query definition for aggregations), analytical functions 6. Simple data pumps 7. Definition of ETL framework 8. Mappings definition, data workflow definition 9. ETL mappings - coding 10. ETL tool - Informatica 11. ETL tool - IBM DataStage/MS SSIS 12. Data profiling, Data cleansing - business rules definition 13. Test

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Graded credit Graded credit 100  51
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner