Business Intelligence
by Hussen Mohamed
1. Features
1.1. Self-serve reporting
1.2. Fast implementation
1.3. In-memory analysis
1.4. Data warehouse
1.5. Data visualisation
1.6. OLAP
1.7. Report scheduling
1.8. Advanced security
1.9. Mobile Access
1.10. Office integration
2. Key stages of BI
2.1. Data Sourcing
2.2. Data Preprocessing/Integration, Data warehouses
2.3. Data Exploration
2.4. Data Presentation
2.5. Decision making
3. Data Mining
4. Association
5. Clustering
6. Summarization
7. DM types of data
8. Relational Database
9. Spatial Database
10. Text Multimedia Database
11. Data Stream
12. Heterogeneous
13. Techniques
14. Machine Learning and artificial intelligence
15. Data cleaning and preparation
16. Tracking patterns
17. Association
18. Classification
19. Outlier detection
20. Clustering
21. Regression
22. Prediction
23. Sequential patterns
24. Decision trees
25. Visualization
26. Neural networks
27. Data warehouse
28. Long-term memory processing
29. Paradigms
30. Verification
31. Discovery
32. Description
33. Prediction
34. Classification
35. Regression
36. Neural Networks
37. Bayesian networks
38. Decision trees
39. Support vector machines
40. Instance Based
41. Classifier Accuracy Measures
42. Holdout Method
43. Random Subsampling
44. K-fold Cross-Validation
45. Bootstrap Methods
46. Methods
47. Classification by Back Propagation
48. Association Rule mining
49. Discriminant Analysis Method
50. Algotithms
51. Simple Linear regression
52. Lasso regression
53. logistic regression
54. Multivariate regression algorithm
55. Multiple regression algorithm
56. Tools and appliications
57. Xplenty
58. Rapid Miner
59. Orange
60. Weka
61. KNIME
62. Sisense
63. SSDT (SQL Server Data Tools)
64. Apache Mahout
65. Oracle Data Mining
66. Rattle
67. DataMelt
68. IBM Cognos
69. IBM SPSS Modeler
70. SAS Data Mining
71. Teradata
72. Board
73. Dundas BI
74. Applications
74.1. Market Analysis
74.2. Production Control
74.3. Customer Retention
74.4. Science Exploration
74.5. Fraud Detection
74.6. Sports
74.7. Astrology
74.8. Internet Web Surf-Aid
75. Sequence discovery
76. Characteristics
76.1. Prediction of likely outcomes
76.2. Focus on large datasets and database
76.3. Automatic pattern predictions based on behavior analysis
76.4. Calculation – To calculate a feature from other features, any SQL expression can be calculated.
77. Future trends
77.1. Online
77.2. Anywhere, anytime
77.3. Real-time
77.4. Centralized, formalized
77.5. RFID
77.6. More samantic capabilities
78. Analytical tools
78.1. relationships
78.1.1. Attribute
78.1.2. Hierarchy
78.1.3. DataStore
78.1.4. Exit
78.2. patterns
78.2.1. Information Consumer Pattern
78.2.2. Analysis Pattern