What is SQL Server Consolidation
Reducing the Number of Physical Sql Servers and also Sql Server Instances.
What are Business Drivers for Sql Server Consolidations.
1. Reduction of Total Cost of Ownership. (Maintaining Personal / Patch Management / Data centre Costs/ Energy Consumption (GreenIT)).
2. Best practices like database maintaince, back up,high availbility,DR strategies etc.
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Features of SQL SERVER 2005 for Consolidation
1. Large Scale Performance (Scale UP)
2. non-uniform memory access (NUMA) architecture
3. Work Load Governerance.
4. Multiple applications connecting through two different IP Address.
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Microsoft Consolidation Options
1. Hardware Partioning
High Throughput Applications
Complete Isolation
Reboot after resizing
2. Resource Management
Medium-High Throughput Applications
Manage Resource Usuage
Same Operating system level
3. Virtualization
Medium-Low throughput
Isolating legac applications
Complex management
Limed scale-up
ALL OF US DO NOT HAVE EQUAL TALENT. YET,ALL OF US HAVE AN EQUAL OPPORTUNITY TO DEVELOP OUR TALENTS. ~ Ratan Tata
Tuesday, June 30, 2009
Tuesday, June 16, 2009
Sunday, June 14, 2009
Data Quality Process
Profiling (Identifying data quality issues).
Generalized Cleansing (tests to meet business rules).
Parsing and standardization (restructing data into a common format).
Matching (finding unique identifiers and performint de-duplication).
Enrichment (phone and email validation)
Monitoring (checking conformance to data quality requirements).
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The construction of data warehouses involves data cleaning, data integration, and data transformation.
OLAP operations such as roll-up, drill-down, slicing, and dicing.
A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision making process
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Generalized Cleansing (tests to meet business rules).
Parsing and standardization (restructing data into a common format).
Matching (finding unique identifiers and performint de-duplication).
Enrichment (phone and email validation)
Monitoring (checking conformance to data quality requirements).
----------------------------------------------------------------------------------------
The construction of data warehouses involves data cleaning, data integration, and data transformation.
OLAP operations such as roll-up, drill-down, slicing, and dicing.
A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision making process
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