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In many big data projects, there is no large data analysis happening, but the challenge is the extract, transform, load part of data pre-processing. [ 225 ] Big data is a buzzword and a "vague term", [ 226 ] [ 227 ] but at the same time an "obsession" [ 227 ] with entrepreneurs, consultants, scientists, and the media.
A presentation program is commonly used to generate the presentation content, some of which also allow presentations to be developed collaboratively, e.g. using the Internet by geographically disparate collaborators. Presentation viewers can be used to combine content from different sources into one presentation.
Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
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.
A cloud-based architecture for enabling big data analytics. Data flows from various sources, such as personal computers, laptops, and smart phones, through cloud services for processing and analysis, finally leading to various big data applications. Cloud computing can offer access to large amounts of computational power and storage. [30]
Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
Research and development, projects Smart cities, more responsive government Smart city, e-democracy, open data, intelligent environment: Digital scent technology: Diffusion Smell-O-Vision, iSmell: DNA digital data storage: Experiments Mass data storage Electronic nose: Research, limited commercialization [20] [21]
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]