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VU Business Intelligence I (052411)
First lecture: 13.03.2019 (attendance mandatory), 12:00-13:00, Last lecture: 26.06.2019.
Wed. wkly. from 09:45 - 13:00
Place: PC2, Währinger Straße 29 1.OG
Contents
The course is structured in five sections:
Methodology and modeling techniques in business intelligence
Data models in business intelligence and data quality
Analysis of cross sectional data (data mining)
Analysis of process data (process mining)
Business intelligence tools (OLAP, Visualization, Text mining, Data Quality Management)
Dates
13.03. |
Preliminary talk, 12:00-13:00 |
20.03. |
|
27.03. |
|
03.04. |
|
10.04. |
Modelling techniques of Business Intelligence |
17.04. |
Easter break |
24.04. |
Easter break |
01.05. |
Staatsfeiertag |
08.05. |
|
15.05. |
|
22.05. |
|
29.05. |
|
05.06. |
|
12.06. |
|
19.06. |
|
26.06. |
Final exam: 9:45 - 10:45 |
Handouts
Exercises
[border]
||27.03.|| Data Provisioning I ||
||03.04.|| Data Provisioning II ||
||10.04.|| Modelling techniques of Business Intelligence 1 ||
||c4cG Osterferien ||
||08.05.|| Modelling techniques of Business Intelligence 2 ||
||15.05.|| Presentation Exercise I and II ||
||22.05.|| Analysis methods for cross-sectional data (Data Mining 1) ||
||29.05.|| Analysis methods for cross-sectional data (Data Mining 2) ||
||05.06.||Analysis methods for cross-sectional data (Data Mining 3) ---Presentation Exercise III--- ||
||12.06.|| Analysis methods for process data (Process Mining 1) ||
||19.06.|| Analysis methods for process data (Process Mining 2) ||
||26.06.|| Social Network Analysis. Presentation Exercise IV ||
|| Conclusion and special techniques, Presentation Exercise !!III!! & V ||
Overall, 5 exercises will be provided. Single submission, i.e., no teamwork.
=== Handouts
* [file:BI1_Einleitung.pdf|Introduction]
* [file:UseCases.pdf|Use Cases]
* [file:BI1_Modelle.pdf|Modeling]
* [file:SupplementsModeling.pdf|Supplements Modeling]
* [file:MatrixFactorisation.pdf|Supplement Matrix factorization]
* [file:MarkovChains.pdf|Supplement Markov chains]
* [file:MarkovChain_Example.pdf|Markov chains - example]
* [file:2018_Cross-sectional Analysis 1.pdf|Cross-sectional Analysis 1]
* [file:2018_Cross-sectional Analysis 2.pdf|Cross-sectional Analysis 2]
* Examples Cross-sectional Analysis
** [file:2018_RegressionDemoExample.pdf|Regression Demo]
** [file:2018_ToyotaCorolla.pdf|Regression Car Prices]
** [file:2018_NaiveBayesDemo1.pdf|Naive Bayes Demo]
** [file:2018_TreeClassification1.pdf|Tree Classification Demo]
** [file:2018_LogisticRegressionDemo.pdf|Logistic Regression Demo]
** [file:2018_Nearest_neighbour_demo.pdf|kNN Demo]
** [file:2018_SupportVectorMachines.pdf|Support Vector machines Demo ]
** [file:2018_Boosting1.pdf|Boosting Demo ]
* [file:2018_Cross-sectional Analysis 3.pdf|Cross-sectional Analysis 3]
** [file:2018_DemonstrationCluster.pdf|Cluster analysis Demo]
* [file:2018_TimeSeriesClassification.pdf|Temporal Data Mining]
** [file:208_Timewarping1.pdf|Time Warping Demo]
** [file:2018_ResonseFeatures1.pdf|Response Feature Analysis Demo]
* [file:2018_TextMining1.pdf|Introduction Text Mining]
* [file:BusinessIntelligence_Data_SS18.pdf|Data Provisioning]
* [file:BusinessIntelligence_ProcessDiscovery_SS18.pdf|Process Discovery]
* Conformance checking: [http://www.processmining.org/_media/presentations/2006_beta-conference_conformancechecking.pdf|Slides] by A. Rozinat
* [file:BusinessIntelligence_2018_SocialNetworkAnalysis.pdf|Social Network Analysis]
//* [file:UseCase1.pdf|Use Case 1]
//* [file:UseCase2.pdf|Use Case 2]
//* [file:UseCase3.pdf|Use Case 3]
//* [file:BusinessIntelligence_Data_SS18.pdf|Data Provisioning]
//* [file:BI1_Modelle.pdf|Modeling in BI]
//* [file:Cross-sectional Analysis 1.pdf|Cross-sectional Analysis 1]
//* [file:Cross-sectional Analysis 2.pdf|Cross-sectional Analysis 2]
//* [file:Cross-sectional Analysis 3.pdf|Cross-sectional Analysis 3]
//** [file:RegressionExample.pdf|DemoExample Regression]
//** [file:NaiveBayesDemo1.pdf|DemoExample Naive Bayes]
//** [file:LogisticRegressionDemo.pdf|DemoExample Logistic Regression]
//** [file:TreeClassification1.pdf|DemoExample Tree classification]
//** [file:SupportVectorMachines.pdf|Example SVM]
//** [file:Boosting1.pdf|Example Boosting]
//* [file:TimeSeriesClassification.pdf|Temporal Data Mining]
//** [file:Timewarping1.pdf|Dynamic Time Warping]
//*** [file:Logistic_stacked1.csv|Data Time warping]
//** [file:ResonseFeatures1.pdf|Response Feature Analysis]
//* [file:TextMining.pdf|Text Mining]
//* [file:BusinessIntelligence_ProcessDiscovery_SoSe17.pdf|Process Mining]
//* [file:BusinessIntelligence_OrgMining_Conformance.pdf|Org Mining, Conformance Checking]
//* [file:BusinessIntelligence_SoSe17_SocialNetworkAnalysis.pdf|Social Network Analysis]
//* [file:NeuralNetsDeepLearning.pdf|Neural Nets and Deep Learning]
//** [file:NeuralNetDemo.pdf|Neural nets example]
//* [file:ImputationMethods.pdf|Missing values and Statistical Matching]
=== Exercises
* [file:Exercise 1.pdf|Exercise 1]
* [file:BUSI_Exercise2.pdf|Exercise 2]
** [file:DermatologischePatientendaten.xls|patient data]
** [file:script.sql|SQL script]
** [file:Intro_SQLXML.pdf|Intro SQLXML]
* [file:2018_Exercises_3_5.pdf|Exercises 3&5]
** [file:2018_WholesaleData.csv|Exercises3_5: Wholesale data]
** [file:2018_CreditDefault.xlsx|Exercises3_5: Credit default data]
** [file:2018_Timeseries.xlsx|Exercises3_5: Timeseries]
* [file:Exercise4_BUSI.pdf|Exercise 4]
//** [file:Timeseries.xlsx|Exercise5-Timeseries]
//** [file:DWH.7z|Exercise5-DWH]
//** [file:DataProcessing.7z|Exercise5-DataProcessing]
Old Exams
Grading
>= 50% overall
Literature
Abbildung 1: Book Cover
Letzte Änderung: 24.06.2019, 09:47 | 703 Worte
