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Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
Data transformation through matrix decomposition: DAAL provides Cholesky, QR, and SVD decomposition algorithms. Outlier detection: Identifying observations that are abnormally distant from typical distribution of other observations.
For example, a data analyst might analyze sales data to identify trends in customer behavior and make recommendations for marketing strategies. [ 37 ] Data science, on the other hand, is a more complex and iterative process that involves working with larger, more complex datasets that often require advanced computational and statistical methods ...
This is an accepted version of this page This is the latest accepted revision, reviewed on 6 January 2025. General-purpose programming language "C programming language" redirects here. For the book, see The C Programming Language. Not to be confused with C++ or C#. C Logotype used on the cover of the first edition of The C Programming Language Paradigm Multi-paradigm: imperative (procedural ...
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]
Data exploration is an approach similar to initial data analysis, whereby a data analyst uses visual exploration to understand what is in a dataset and the characteristics of the data, rather than through traditional data management systems. [1]
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Interactive data transformation (IDT) [13] is an emerging capability that allows business analysts and business users the ability to directly interact with large datasets through a visual interface, [9] understand the characteristics of the data (via automated data profiling or visualization), and change or correct the data through simple ...