Top 144 Kimball Design Tips by the Number of References in Google Search

Rank # Design Tip Refs
1 ) 51 Latest Thinking on Time Dimension Tables 1310
2 ) 5 Surrogate Keys for the Time Dimension 1140
3 ) 122 Call to Action for ETL Tool Providers 616
4 ) 115 Kimball Lifecycle in a Nutshell 519
5 ) 46 Another Look at Degenerate Dimensions 443
6 ) 48 De-clutter with Junk Dimensions 321
7 ) 137 Creating and Managing Shrunken Dimensions 286
8 ) 8 Perfectly Partioning History with Type 2 SCD 262
9 ) 25 Dimensional Models for Parent-Child Applications 240
10 ) 111 Is Agile Enterprise Data Warehousing an Oxymoron? 226
11 ) 41 Drill Down into a Detailed Bus Matrix 166
12 ) 50 Factless Fact Tables 163
13 ) 1 Guidelines for an Expressive Clickstream Data Mart 152
14 ) 34 You Don't Need an EDW 151
15 ) 91 Marketing the DW/BI System 145
16 ) 59 Surprising Value of Data Profiling 144
17 ) 106 Can the Data Warehouse Benefit from SOA? 137
18 ) 107 Using the SQL MERGE Statement for Slowly Changing Dimensions 134
19 ) 21 Declaring the Grain 124
20 ) 56 Dimensional Modeling for Microsoft Analysis Services 121
21 ) 2 Multiple Time Stamps 111
22 ) 99 Staging Areas and ETL Tools 110
23 ) 90 Slowly Changing Entities 103
24 ) 89 The Real Time Triage 101
25 ) 13 When Fact Tables can be used as Dimensions 96
26 ) 20 Sparse Facts and Facts with Short Lifetimes 96
27 ) 57 Early Arriving Facts 93
28 ) 9 Processing Slowly Changing Dimensions during Initial Load 90
29 ) 17 Populating Hierarchy Helper Tables 88
30 ) 43 Dealing With Nulls in a Dimensional Model 85
31 ) 81 Fact Table Surrogate Keys 83
32 ) 37 Modeling a Pipeline with Accumulating Snapshots 78
33 ) 15 Combining SCD Techniques 75
34 ) 85 Smart Date Keys to Partition Fact Tables 69
35 ) 136 Adding a Mini-Dimension to a Bridge Table 68
36 ) 73 Relating to Agile Methodologies 67
37 ) 49 Off the Bench about the Bottoms Up Misnomer 65
38 ) 3 Focus on Business Process, not Business Departments 63
39 ) 42 Combining Periodic and Accumulating Snapshots 62
40 ) 39 Bus Architecture Foundation for Analytic Applications 60
41 ) 28 Avoiding Catastrophic Failure of the Data Warehouse 58
42 ) 139 Much Ado About Nothing 56
43 ) 58 BI Portal 55
44 ) 92 Dimension Manager and Fact Provider 55
45 ) 95 Patterns to Avoid when Modeling Header/Line Item Transactions 54
46 ) 35 Modeling Time Spans 52
47 ) 121 Columnar Databases: Game Changers for DW/BI Deployment? 52
48 ) 124 Alternatives for Multi-valued Dimensions 51
49 ) 33 Using CRM Measures as Behavior Tags 48
50 ) 16 Hot Swappable Dimensions 45
51 ) 135 Conformed Dimensions as the Foundation for Agile Data Warehousing 45
52 ) 97 Modeling Data as Both a Fact and Dimension Attribute 44
53 ) 19 Replicating Dimensions Correctly 41
54 ) 113 Creating, Using, and Maintaining Junk Dimensions 41
55 ) 127 Creating and Managing Mini-Dimensions 41
56 ) 134 Data Warehouse Testing Recommendations 40
57 ) 87 Combining SCD Techniques Having It Both Ways 39
58 ) 128 Selecting Default Values for Nulls 38
59 ) 7 Getting your Data Warehouse back on Track 36
60 ) 22 Variable Depth Customer Dimensions 36
61 ) 30 Put your Fact Tables on a Diet 36
62 ) 53 Dimension Embellishments 36
63 ) 110 Business Requirements Gathering Dos and Don’ts 36
64 ) 133 Factless Fact Tables for Simplification 36
65 ) 12 Accurate Counting with a Dimensional Supplement 35
66 ) 119 Updating the Date Dimension 35
67 ) 6 Showing the Correlation between Dimensions 33
68 ) 84 Readers’ Suggestions on Fact Table Surrogate Keys 33
69 ) 141 Expanding Boundaries of the Data Warehouse 33
70 ) 126 Disruptive ETL Changes 32
71 ) 140 Is it a Dimension, a Fact, or Both? 32
72 ) 4 Fast Changing Complex Customer Dimensions 31
73 ) 102 Server Configuration Considerations 31
74 ) 123 Using the Dimensional Model to Validate Business Requirements 31
75 ) 100 Keep Your Keys Simple 30
76 ) 129 Are IT Procedures Beneficial to DW/BI Projects? 30
77 ) 61 Handling all the Dates 29
78 ) 88 Dashboards Done Right 28
79 ) 11 Accurate Counts within a Dimension 27
80 ) 78 Late Arriving Dimension Rows 27
81 ) 24 Multinational Dimensional Data Warehouse Considerations 26
82 ) 14 Arbitrary Balance Reporting with Transaction Facts 24
83 ) 26 Audit Dimensions to Track Lineage and Confidence 24
84 ) 27 Being Off-line as Little as Possible 24
85 ) 29 Graceful Modifications to Existing Fact and Dimension Tables 24
86 ) 103 Staffing the Dimensional Modeling Team 24
87 ) 105 Snowflakes, Outriggers, and Bridges 24
88 ) 130 Accumulating Snapshots for Complex Workflows 24
89 ) 18 Taking the Publishing Metaphor Seriously 23
90 ) 32 Doing the Work at Extract Time 23
91 ) 75 Creating the Metadata Strategy 23
92 ) 45 Techniques for Modeling Intellectual Capital 22
93 ) 104 Upgrading your BI Architecture 22
94 ) 76 Advantages of a 64-bit Server 21
95 ) 86 Reference Dimensions for Infrequently-Accessed Degenerates 21
96 ) 93 Transactions Create Time Spans 20
97 ) 96 Think Like A Software Development Manager 20
98 ) 79 Dangerously Large Dimension Tables 19
99 ) 82 Pivoting the Fact Table with a Fact Dimension 17
100 ) 114 Avoiding Alternate Organization Hierarchies 17
101 ) 109 Dos and Don’ts on the Kimball Forum 15
102 ) 31 Designing a Real Time Partition 9
103 ) 60 Big Shifts in Business Intelligence 9
104 ) 63 Building a Change Data Capture System 9
105 ) 65 Document the ETL System 9
106 ) 112 Creating Historical Dimension Rows 9
107 ) 10 Is your Data Correct 8
108 ) 36 To Be or Not To Be Centralized 8
109 ) 38 Analytic Application—What's That? 8
110 ) 40 Structure of an Analytic Application 8
111 ) 44 Reliance on the BI Tool’s Metadata 8
112 ) 47 Business Initiatives versus Business Processes 8
113 ) 52 Improving Operating Procedures 8
114 ) 62 Alternate Hierarchies 8
115 ) 69 Identifying Business Processes 8
116 ) 70 Architecting Data for MS SQL Server 2005 8
117 ) 101 Slowly Changing Vocabulary 8
118 ) 108 When is the Dimensional Model Design Done? 8
119 ) 125 Balancing Requirements and Realities 8
120 ) 138 Use a Design Charter to Keep Dimensional Design Activities on Track 8
121 ) 23 Rolling Prediction of the Future 7
122 ) 54 Delivering Historical and Current Perspectives 7
123 ) 68 Simple Drill-Across in SQL 7
124 ) 80 Dimension Row Change Reason Attributes 7
125 ) 83 Resist Abstract Generic Dimensions 7
126 ) 94 Building Custom Tools for the DW/BI System 7
127 ) 98 Focus on Data Stewardship 7
128 ) 116 Add Uncertainty to Your Fact Table 7
129 ) 118 Managing Backlogs Dimensionally 7
130 ) 120 Design Review Dos and Don’ts 7
131 ) 131 Easier Approaches For Harder Problems 7
132 ) 55 Exploring Text Facts 6
133 ) 64 Avoid Isolating the DW and BI Teams 6
134 ) 67 Maintaining Back Pointers to Operational Sources 6
135 ) 72 Business Process Decoder Ring 6
136 ) 74 Compliance-Enabled Data Warehouses 6
137 ) 77 Warning: Summary Data may be Hazardous 6
138 ) 132 Kimball Forum Update 6
139 ) 66 Implementation Analysis Paralysis 5
140 ) 71 Naming Conventions 5
141 ) 117 Dealing with Data Quality: Don’t Just Sit There, Do Something! 5
142 ) 142 Building Bridges 5
143 ) 143 Enjoy the Sunset 5
144 ) 144 History Lesson on Ralph Kimball and Xerox PARC 4