Leveraging your diagram from your Week One Individual Assignment, develop a 1-page business case for implementing CRM within your current organization, an organization you are familiar with, or an org

Running head: DATA WAREHOUSE REPOSITORY

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Data Warehouse Repository

CRM in Data warehouse

Obtaining and keeping business trust is an initial goal of a data warehouse that needs favorable communication between the business users and the data warehouse team as well as the ability to offer reachable, high-quality data. Data control and the quality are continuous processes in provision of increased business trust in a data warehouse.

Data warehouse data components include:

• The consumption areas – is retrieved by professional clients and include a data warehouse, numerous data marts, or an arrangement of the two.

• The exception data – this is the range is where proceedings which fail data quality checks and business rules are held

• Production are including:

1. Production databases are where data is rinsed out, lineage is introduced, business rules are applied, and the versioned information is introduced.

2. Data in databases contain a mirror copy of a subset of source system data.

• Archived databases – the records holding old data removed from data areas to improve performance.

• Logging databases – the essential records for recording the day-to-day activity within the data warehouse and typically include logging activity from data integration processes and, optionally, consumption data area access.

• Metadata – it describes the data itself, both in business terms and technical terms. It includes definitions, rules, and origins of all data in the data warehouse. Also, process metadata helps define configurations and implement security within the data warehouse.

These data zones are the motivation of the remainder of this section, which is organized by data warehouse maturity level—starting with basic configurations seen in departmental data marts and moving to more advanced settings seen.

Exterior data feeds can include LOB systems, such as customer relationship management (CRM) systems. It is critical for CRM systems to put away data that is gathered from different data sources, so a data warehouse adequately architected in this respect signifies a model source of data for CRM. Data warehouses offer for data feeds that comprehend an essential, comprehensive as well as consistent perspective of customers, making CRM systems more effective and efficient. In addition, data warehouses show a regularly purified and consistent source of customer data that is accessible enterprise-wide. Maximum source data comes from transactional line of business CRM systems. These CRM systems’ data models are highly standardized in support of Online Transaction Processing (OLTP). Other sources, mostly file-based, are typically in a demoralized format and have various sources (e.g., external vendors and partners, exports from internal systems). Moreover, these files are made and preserved by business as well as technical users within applications such as Microsoft Excel and Access. The production area is where source data is rationalized and combined. The subject areas within the production area are generally modeled in a normalized format, but less so than the source LOB systems. This data is then transformed, demoralized, and aggregated when it flows to the consumption area. Dimensional data models are an example of a demoralized structure optimized for data consumption.

References

Best Practices for Data Warehousing with SQL Server 2008
http://msdn.microsoft.com/en-us/library/cc719165(v=SQL.100).aspx