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Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [25] Big data requires a set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. [26]
2 stars: data is available in a structured format, such as Microsoft Excel file format (.xls). 3 stars: data is available in a non-proprietary structured format, such as Comma-separated values (.csv). 4 stars: data follows W3C standards, like using RDF and employing URIs. 5 stars: all of the others, plus links to other Linked Open Data sources.
Given the fairly static yet voluminous nature of machine-generated data, data owners rely on highly scalable tools to process and analyze the resulting dataset. Almost all machine-generated data is unstructured but then derived into a common structure. [4] Typically, these derived structures contain many data points/columns. With these data ...
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Excel for the web is a free lightweight version of Microsoft Excel available as part of Office on the web, which also includes web versions of Microsoft Word and Microsoft PowerPoint. Excel for the web can display most of the features available in the desktop versions of Excel, although it may not be able to insert or edit them.
Computational studies, used to find a starting point for a laboratory synthesis or to assist in understanding experimental data, such as the position and source of spectroscopic peaks. [ 7 ] Computational studies, used to predict the possibility of so far entirely unknown molecules or to explore reaction mechanisms not readily studied via ...
Free and open-source software also allow free use, sharing, and modification, perhaps with a few specified conditions. [64] The use of some software is governed by an agreement (software license) written by the copyright holder and imposed on the user. Proprietary software is usually sold under a restrictive license that limits its use and ...
Introduction to Algorithms is a book on computer programming by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.The book is described by its publisher as "the leading algorithms text in universities worldwide as well as the standard reference for professionals". [1]