Customer Relationships and Data Warehousing

This Technology is an Information Infrastructure with Detailed Data

Sep 30, 2009

Large organizations routinely collect vast amounts of personal data about their customers, through the transactions they conduct.

Large organizations routinely collect vast amounts of personal data about their customers, through the transactions they conduct with these organizations.

From an operational perspective, corporate data may be located in several different places throughout the organization – mainframe applications, distributed systems, and information-gathering devices. The latter may include: point-of-sale (POS) registers, automatic teller machines (ATMs), as well as order entry, billing, financial, accounting, inventory, customer service, or logistics applications. To be useful, regardless of its source, this data must be collected and transformed into a consistent form, if the data warehouse is to fulfill its primary goal as a core technology in a CRM solution.

This process is called ‘data transformation’ and it is the foundation for creating a warehouse with high-quality, reliable data. Data transformation includes a number of processes for handling and manipulating data, which are:

Two Types of Data Warehouses

There are two fundamental schools of thought for designing a data warehouse. One approach is a distributed, centralized design where data is stored in independent data marts, each having the data relevant to that aspect of the business. A better alternative, and more complete solution for the enterprise, is to source the data into a single centralized data source that allows users throughout the organization to make decisions from the same consistent data.

In some organizations, these two designs are combined to benefit from the best features of each one, by using a single data store of clean, accurate detailed data for the enterprise. This data is combined with data from smaller, dependent data storage facilities, known as ’data marts.’

Data marts containing subsets of data from the enterprise warehouse, selected and organized for a particular set of usage requirements, can be implemented as either logical implementations or separate physical implementations. Data replication and propagation processes synchronize data between the enterprise data warehouse and the data marts.

Performing Customer-related Functions

Organizations in most private sectors, financial institutions, healthcare providers, travel agencies, retailers, automotive manufacturers, communication companies, among others, as well as organizations in the public sector, collect customer data to perform a number of customer-related functions, including:

However, getting positive, measurable business results from these activities does not come from simply gathering information and storing it. The data gathered needs to be used in a manner which will achieve the objectives of the corporate CRM strategy, which will result from the knowledge and understanding of customers, who they are and what they really want, and then applying this knowledge to establish customer relationship strategies and processes.

The copyright of the article Customer Relationships and Data Warehousing in Business Project Management is owned by Duane Sharp. Permission to republish Customer Relationships and Data Warehousing in print or online must be granted by the author in writing.