Data Warehousing Key Terms
Making sense of data warehousing terminologyWhile large IT departments and companies have traditionally been the ones to take advantage of data warehousing, it's not out of the question for small and medium businesses. The high cost of the necessary software and hardware, coupled with the maintenance required, kept most small businesses out of the playing field.
If you're looking at the possibility of data warehousing options for your business for the first time, familiarize yourself with the data warehousing key terms first. If you're not IT savvy, you can get confused quickly. This guide addresses basic terms, such as data warehouse, data mart, queries, SOA, structured and unstructured data and meta data.
Data martA data mart is a repository of data (that may or may not come from a data warehouse) gathered from operational data and other sources that's designed to answer the specific demands of a single audience in terms of analysis, content, presentation and ease of use. A data mart is sometimes described as a scaled-down data warehouse for a single department or function.
QueriesQueries are concise memos with specific parameters for requesting information from a data warehouse. For example, you can write queries to retrieve quarterly sales values or comparisons of weekly, monthly, quarterly and annual sales values.
write your own queries from Penn Computing at the University of Pennsylvania Information Systems & Computing department.
SOASOA stands for service-oriented architecture. It's an enterprise-scale, conceptual IT architecture used to design applications and business processes where every computing unit of work equals one service. For example, a service can be determining inventory levels, ordering product or segmenting customers. SOA integrates your business as linked services and their outcomes.
Structured data vs. unstructured dataStructured data refers to data within fixed fields inside a record or file. The format of structured data remains the same; only the values change. Examples include spreadsheets, budgets, purchase orders, statistics, inventories and sales. In contrast, unstructured data comes in the form of free-form text such as emails or other word processing documents. Unstructured data also includes Bitmap objects such as image, video and audio files.
Meta dataSimply and concisely put, the term meta data means data about other data. With regard to a data warehouse, meta data describe the warehouse's contents, data location, correlation to other data, sources and its relation to the company.
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