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Front Page 		1
Contents 		2
1 Introduction and Scope of this document 		5
2 Document Plan 		5
2.1 Reference publication: Kimball’s Data Warehousing Lifecycle 		6
2.2 Enhancements to Reference Publication 		7
3 Relevance of the new tendencies for our scope 		8
3.1 Cloud Computing for Analytics 		8
3.1.1 Cloud data warehouses 		9
3.1.2 Cloud data integration 		10
3.1.3 Cloud Application Integration 		12
3.2 Big Data 		13
3.2.1 Hadoop for ETL workloads 		15
3.2.2 Hadoop for Analytics, or Data Lakes 		16
3.2.3 Hadoop as a service 		17
3.3 Self-service tools and agility 		18
4 Technical Architecture 		19
4.1 Technical Architecture Overview 		19
4.2 DW/BI system architecture model 		20
4.3 Best Practices 		22
4.3.1 Technical Architecture at Planning Stage 		22
4.3.2 Technical Architecture at Design Stage 		23
4.3.3 Technical Architecture at Development Stage 		24
4.3.4 Technical Architecture at Deployment Stage 		24
4.4 Enhancements to the reference publication 		25
4.4.1 Technical Architecture in our own experience 		25
4.4.2 Cloud Deployments 		31
4.4.3 Big Data 		31
4.4.4 Self-service and agility 		32
5 Dimensional data modeling 		33
5.1 Dimension Data Modeling Overview 		33
5.2 Brief Summary 		34
5.3 Best Practices 		35
5.3.1 Dimension Data Modeling - Project definition stage 		35
5.3.2 Dimension Data Modeling - Requirements Interview 		35
5.3.3 Dimension Data Modeling – Logical 		35
5.3.4 Dimension Data Modeling – Physical 		38
5.3.5 Dimension Data Modeling – ETL Considerations 		38
5.3.6 Dimension Data Modeling – Deployment Considerations 		42
5.4 Enhancements to the reference publication 		44
5.4.1 Dimension Modeling in our own experience 		44
5.4.2 Cloud Deployments 		47
5.4.3 Big Data 		48
5.4.4 NoSQL 		49
5.4.5 Self-Service and Agility 		50
6 Data Quality 		51
6.1 Brief Summary 		51
6.2 Best Practices 		53
6.2.1 Data quality at project definition stage 		53
6.2.2 Data Quality at Requirements Definition Stage 		54
6.2.3 Data Quality at Design Stage 		54
6.2.4 Data Quality at Development Stage 		55
6.2.5 Data Quality at Deployment Stage 		56
6.3 Enhancements to the reference publication 		57
6.3.1 Our own experience 		57
6.3.2 Cloud Deployments 		59
6.3.3 Big Data 		60
6.3.4 Self-Service Tools 		66
7 Non-functional aspects 		69
7.1 Brief Summary 		69
7.2 Best Practices 		69
7.2.1 Performance at Requirements and planning stage 		69
7.2.2 Performance at Design and Technical architecture stage 		70
7.2.3 Performance at Dimensional DW Model design stage 		72
7.2.4 Performance at Implementation, physical design stage 		73
7.2.5 Performance at Deployment and support stage 		74
7.2.6 Security at Requirements and planning stage 		74
7.2.7 Security at Design and Technical architecture stage 		75
7.2.8 Security at Implementation, physical design stage 		75
7.2.9 Security at Deployment and support stage 		76
7.3 Enhancements to the reference publication 		77
7.3.1 Performance optimization based on our own experience 		77
7.3.2 Security best practices based on our own experience 		81
7.3.3 Cloud deployments 		83
7.3.4 Big data 		86
8 Conclusion 		90
9 Glossary 		91
10 References 		94
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