1BM110 Data Analytics for Business Intelligence (1BM110)
Summary
Summary 1BM110 Data Analytics for Business Intelligence Lecture notes
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Course
1BM110 Data Analytics for Business Intelligence (1BM110)
Institution
Technische Universiteit Eindhoven (TUE)
Notice! These notes are unstructured and have not been checked afterwards. Hence the low price.
No notes of lecture 6, since the transcript is written in de notes of de slides.
, 1BM110 Lecture notes
Lecture 1
Conventional decision support -> emphasis on deduction:
Premise: Every swan I have seen is white.
Conclusion: All swans are white.
BI-> emphasis on induction:
premise A:all men are mortal
premise B: Pete is a men
Conclusion: Pete is mortal.
BI: data-driven decision support
emphasis on induction
Data-> model -> decision
Business/data analytics: degree of intelligence
Descriptive analytics: use data to understand the past and current performance. What is
going on, what has happened using the data collected.
o Reporting, dashboards, summarization, visualization
o Segmentation: clustering
Predictive analytics: analyse the past performance in order to predict the future. What will
occur?
o Regression & classification
o Associate rule
o Text mining: unstructured data
Prescriptive analytics: what should occur?
o Optimization techniques
o Mathematical optimization models: heuristics
Maturity & ambition level matrix
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