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Customer data management should provide a cost-effective, user-friendly solution for marketing, research, sales, human resources and IT departments; enables companies to create and email online surveys, reports and newsletters; encompasses and simplifies customer relationship management (CRM) and customer feedback management (CFM)
Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers.
Data collection can be done by observing customer behavior through in-situ studies or by processing e.g. log files, by interviewing customers, potential customers, stakeholders, or a sample of the general population. The data can be quantitative in nature (counting sales, clicks, eye-tracking) or qualitative (surveys, questionnaires, interviews ...
Master data represents "data about the business entities that provide context for business transactions". [1] The most commonly found categories of master data are parties (individuals and organisations, and their roles, such as customers, suppliers, employees), products, financial structures (such as ledgers and cost centres) and locational concepts.
Customer data or consumer data refers to all personal, behavioural, and demographic data that is collected by marketing companies and departments from their customer base. [1] To some extent, data collection from customers intrudes into customer privacy , the exact limits to the type and amount of data collected need to be regulated.
Consider a database of sales, perhaps from a store chain, classified by date, store and product. The image of the schema to the right is a star schema version of the sample schema provided in the snowflake schema article. Fact_Sales is the fact table and there are three dimension tables Dim_Date, Dim_Store and Dim_Product.
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An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.
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