Some of the benefits of SQL Server 2008 in Data warehousing

SQL Server 2008 provides a comprehensive and scalable data warehouse platform that enables strong analysis with a single analysis store to meet the needs of tens of thousands of users in terabytes of data. The following are some of the benefits of data warehousing in SQL Server 2008.

Data compression

The amount of data in the data warehouse continues to grow as the number of operating systems increases rapidly. Data compression embedded in SQL Server 2008 enables companies to store data more efficiently while improving performance because of reduced I/O requirements.

Backup compression

Keeping your disk-based backups online is expensive and time-consuming. With SQL Server 2008 backup compression, the storage required to maintain an online backup is reduced, and the backup speed is significantly faster because the required disk I/O is reduced.

Partitioned table parallelism

Segmentation enables companies to manage large, growing tables of data more efficiently, simply by dividing them into manageable chunks of data. SQL Server 2008 is built on the edge of partitioning in SQL Server 2005, which improves operational performance for large partitioned tables.

Star join query optimizer

SQL Server 2008 provides improved query performance for common Data Warehouse scenarios. The star join query optimizer reduces query response time by identifying the Data Warehouse connection mode.

Resource Monitor

With the introduction of the Resource Monitor, SQL Server 2008 enables companies to provide consistent and predictable responses to end users. The resource Monitor enables companies to define resource limits and priorities for different workloads, which enables concurrent workloads to provide stable performance.

Grouping settings

Grouping settings (GROUPING SETS) is an extension of the group by conditional statement, which allows users to define multiple groupings in the same query. Group settings generate a separate result set that is equivalent to union all for rows of different groupings, making it easier and faster to aggregate queries and reports.

Capturing change data

With the capture change data, the changes are captured and placed in the change table. It captures the full content of the change, maintains the consistency of the crosstab, and even works on the cross schema changes. This allows the company to integrate the latest information into the Data warehouse.

Mergesql statement

With the merge SQL statement, developers can more efficiently handle the scenarios of the data warehouse, such as checking for the existence of a row of data and then performing inserts or updates.

Scalable Integration Services

The two key benefits of extensibility for integrated services are:

· SQL Server Integration Services (SQL Server integration Services,ssis) pipeline improvements

Data integration packages are now more effective at scaling up, using effective resources, and managing the largest enterprise-class workloads. This new design increases the scalability of the runtime to multiple processors.

· SSIS Persistent Lookup

Performing a lookup is the most common extraction, transformation, and load (ETL) operation. This is particularly common in data warehouses where the actual records must use lookups to convert the business keys to their corresponding replacements. SSIS enhances the performance of lookups to support large tables.