460-4098/02 – Business Intelligence and Data Warehouses II (BI II)
Gurantor department | Department of Computer Science | Credits | 3 |
Subject guarantor | doc. Ing. Radim Bača, Ph.D. | Subject version guarantor | doc. Ing. Radim Bača, Ph.D. |
Study level | undergraduate or graduate | Requirement | Optional |
Year | 2 | Semester | winter |
| | Study language | English |
Year of introduction | 2015/2016 | Year of cancellation | 2022/2023 |
Intended for the faculties | FEI | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The student is able to orient in the domain of Business Intelligence and Data Warehousing (DWH), in particular in practical knowledge of DWH data modelling methodology, Data Integration into DWH, analytics and presentation of data. Moreover, a student is able to design, create and make use of reporting and presentation layers in a DWH - data marts for analytics and reporting over data, including their graphical presentation using BI tools and web portals. As a supplement to the base content, the student is introduced to new developing trends in the domain of BI and DWH, including areas such as Big Data and analytics over massive quantity of data in real time.
Teaching methods
Lectures
Tutorials
Summary
The subject is a follow up to the Business intelligence and Data Warehouse I subject aimed to extend the knowledge in the domain of analytics over data using querying and specialized BI tools. The content of lectures is a more detailed clarification of DWH principles, specifics of data modelling, design of reporting layers, data integration including transformations and aggregations for presentation of business information hidden within data in a graphical form and layout, or data extracts for further processing. Another part of the subject is the methodology and principles of a solution design of reporting and analytics project. During practical sessions a student is given a chance to apply the knowledge in practical examples of reports and analytical cubes using market-leading BI tools.
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
Other requirements
Knowledge of topics of the topic Business Intelligence and data warehouses.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1.-2. Analytics over data - forms of analytics over DataWarehouse (DWH), advanced analytical methods, data mining.
3.-4. Reporting - types of reportingu, dashboards, ad-hoc reporting, presentation and semantic layers, OLAP cubes, parametrization, reporting outputs.
5.-6. OLAP - Dimensions and facts, Hierarchies in dimensional tables, Measures and metrics.
7.-8. Reporting tools
9.-10. Project Management in BI and DWH projects - project roles (Business Analyst, Developer, Tester), development and implementation phases, testing, types of environments, documenting.
11.-12. Process Management - Business definition/request, analysis, functional design, technical specifications, development and testing, deployment to production and handover, daily operation.
13. Latest trends in DWH and BI - Agile BI, Big Data
Computer practices:
1. Summary of business intelligence.
2. Creation of data structures for reporting.
3. Reports Definition
4. Reports Definition - view creation in DWH.
5. Metrics definition
6. Report design - tables - OLAP cubes
7. Report design - tables - drilldown, detailed views
8. Report design - Charts
9. SAP BO / Tableau
10. QlikView
11. IBM Cognos
12. R - Data Mining
13. Final test
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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