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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 ...
The data are stored in a standard relational database and can be accessed by any SQL reporting tool (the tool does not have to be an OLAP tool). ROLAP tools are better at handling non-aggregable facts (e.g., textual descriptions). MOLAP tools tend to suffer from slow performance when querying these elements.
Business intelligence software is a type of application software designed to retrieve, analyze, transform and report data for business intelligence (BI). The applications generally read data that has been previously stored, often - though not necessarily - in a data warehouse or data mart .
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
These data become critical to segment markets or define target audiences, e.g. purchases of software license renewals by telecom companies could help identify which technologist is in charge of software installations vs. software procurement, etc. Customers in Business-to-Business environments often tend to be loyal since they need after-sales ...
Analytics is the "extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions." It is a subset of business intelligence, which is a set of technologies and processes that uses data to understand and analyze business performance to drive decision-making .
Guided analytics applications lie in the intersection between business intelligence and predictive analytics. A great number of business analysts rely on business intelligence tools to flexibly extract specific information from data. [1] It is often required to automatically run an analysis on the raw data before information can be extracted. [2]
Network intelligence (NI) is a technology that builds on the concepts and capabilities of deep packet inspection (DPI), packet capture and business intelligence (BI). It examines, in real time, IP data packets that cross communications networks by identifying the protocols used and extracting packet content and metadata for rapid analysis of data relationships and communications patterns.
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