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Trends in Information Analysis & Data Management

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Trends in Information Analysis and Data Management

Trends in Information Analysis and Data Management
Over the last decade, advancements in digital technology have enabled companies to collect huge amounts of new information. This data is so large in scope, it has traditionally been difficult to process and analyze this information using standard database management systems such as SQL. The commoditization of computer technology has created a new paradigm in which data can be analyzed more efficiently and effectively than ever before. This report analyzes the some of the most important changes that are currently taking place within this new paradigm.
The first part of this report covers trends in database analysis by analyzing the field of data mining. The report covers the topic of data mining by providing an explanation of it, and then by providing examples of real-world examples of data mining technology. Benefits and challenges of data mining are then provided.
The second part of the report outlines an even more recent trend in data science, which is the increasing usage of noSQL databases to analyze “big data,” also referred to web-scale datasets. The most recent and major technological developments in the industry are then provided and described.
Data Mining
Background & Definition
Data mining involves the process of discovering and extracting new knowledge from the analysis of large data sets. This is most often done through the use of data mining software, which identifies correlations between different variables in a given data set. Data mining is primarily used to analyze data stored in relational databases, which consists of tables joined together by key variables in each.1 For nearly thirty years, relational database systems have been the primary type of database used to store data. Before data mining was available, analysts performed

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