Data mining term paper

Research on the effective usage of information and communication technologies for development (also known as ICT4D ) suggests that big data technology can make important contributions but also present unique challenges to International development . [72] [73] Advancements in big data analysis offer cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity , crime, security, and natural disaster and resource management. [74] [75] [76] Additionally, user-generated data offers new opportunities to give the unheard a voice. [77] However, longstanding challenges for developing regions such as inadequate technological infrastructure and economic and human resource scarcity exacerbate existing concerns with big data such as privacy, imperfect methodology, and interoperability issues. [74]

While data science focuses on the science of data, data mining is concerned with the process. It deals with the process of discovering newer patterns in big data sets. It might be apparently similar to machine learning, because it categorizes algorithms. However, unlike machine learning, algorithms are only a part of data mining. In machine learning algorithms are used for gaining knowledge from data sets. However, in data mining algorithms are only combined that too as the part of a process. Unlike machine learning it does not completely focus on algorithms. 

Assist faculty or other instructional staff in postsecondary institutions by performing teaching or teaching-related duties, such as teaching lower level courses, developing teaching materials, preparing and giving examinations, and grading examinations or papers. Graduate teaching assistants must be enrolled in a graduate school program. Graduate assistants who primarily perform non-teaching duties, such as research, should be reported in the occupational category related to the work performed. Excludes “Teacher Assistants” (25-9041).

The first product that performed OLAP queries was Express, which was released in 1970 (and acquired by Oracle in 1995 from Information Resources). [20] However, the term did not appear until 1993 when it was coined by Edgar F. Codd , who has been described as "the father of the relational database". Codd's paper [1] resulted from a short consulting assignment which Codd undertook for former Arbor Software (later Hyperion Solutions , and in 2007 acquired by Oracle), as a sort of marketing coup. The company had released its own OLAP product, Essbase , a year earlier. As a result, Codd's "twelve laws of online analytical processing" were explicit in their reference to Essbase. There was some ensuing controversy and when Computerworld learned that Codd was paid by Arbor, it retracted the article. OLAP market experienced strong growth in late 1990s with dozens of commercial products going into market. In 1998, Microsoft released its first OLAP Server – Microsoft Analysis Services , which drove wide adoption of OLAP technology and moved it into mainstream.

Data mining term paper

data mining term paper

The first product that performed OLAP queries was Express, which was released in 1970 (and acquired by Oracle in 1995 from Information Resources). [20] However, the term did not appear until 1993 when it was coined by Edgar F. Codd , who has been described as "the father of the relational database". Codd's paper [1] resulted from a short consulting assignment which Codd undertook for former Arbor Software (later Hyperion Solutions , and in 2007 acquired by Oracle), as a sort of marketing coup. The company had released its own OLAP product, Essbase , a year earlier. As a result, Codd's "twelve laws of online analytical processing" were explicit in their reference to Essbase. There was some ensuing controversy and when Computerworld learned that Codd was paid by Arbor, it retracted the article. OLAP market experienced strong growth in late 1990s with dozens of commercial products going into market. In 1998, Microsoft released its first OLAP Server – Microsoft Analysis Services , which drove wide adoption of OLAP technology and moved it into mainstream.

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