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Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods .
Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. [2] In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. [3]
The difficulties associated with quantification of EDM benefits translate into challenges with the positioning of EDM as an organizational priority. Achieving organizational alignment on the importance of data management (as well as managing data as an ongoing area of focus) is the domain of governance. In recent years the establishment of an ...
Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. [1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text ...
Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems."
Business systems planning (BSP) is a method of analyzing, defining and designing the information architecture of organizations. It was introduced by IBM for internal use only in 1981, [ 1 ] although initial work on BSP began during the early 1970s.
Master data management (MDM) is a discipline in which business and information technology collaborate to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets.
A time series is the sequence of a variable's value over equally spaced periods, such as years or quarters in business applications. [11] To accomplish this, the data must be smoothed, or the random variance of the data must be removed in order to reveal trends in the data. There are multiple ways to accomplish this.