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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 ...
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Data thinking is a product design framework that combines data science with the design process. It integrates principles from computational thinking, statistical thinking, and domain-specific knowledge to steer the creation of data-driven solutions.
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.
Only a few companies are considered to be at a "mature" stage of big data and analytics. [7] These include internet-based companies (such as LinkedIn , Facebook , and Amazon ) and other non-Internet-based companies, including financial institutions (fraud analysis, real-time customer messaging and behavioral modeling) and retail organizations ...
Data analysts typically spend the majority of their time in the process of data wrangling compared to the actual analysis of the data. The process of data wrangling may include further munging , data visualization , data aggregation, training a statistical model , as well as many other potential uses.