Concepts inQuery, analysis, and visualization of hierarchically structured data using Polaris
Data model
A high-level data model in business or for any functional area is an abstract model that documents and organizes the business data for communication between functional and technical people. It is used to show the data needed and created by business processes.
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Data analysis
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.
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OLAP cube
An OLAP cube is a set of data, organized in a way that facilitates non-predetermined queries for aggregated information, or in other words, online analytical processing. OLAP is one of the computer-based techniques for analyzing business data that are collectively called business intelligence.
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Information graphics
Information graphics or infographics are graphic visual representations of information, data or knowledge. These graphics present complex information quickly and clearly, such as in signs, maps, journalism, technical writing, and education. With an information graphic, computer scientists, mathematicians, and statisticians develop and communicate concepts using a single symbol to process information.
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Online analytical processing
In computing, online analytical processing, or OLAP, is an approach to swiftly answer multi-dimensional analytical queries. OLAP is part of the broader category of business intelligence, which also encompasses relational reporting and data mining.
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Data warehouse
In computing, a data warehouse (DW or DWH) is a database used for reporting and analysis. The data stored in the warehouse are uploaded from the operational systems (such as marketplace, sales etc. , shown in the figure to the right). The data may pass through an operational data store for additional operations before they are used in the DW for reporting. The typical ETL-based data warehouse uses staging, integration, and access layers to house its key functions.
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Exploratory data analysis
In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics in easy-to-understand form, often with visual graphs, without using a statistical model or having formulated a hypothesis. Exploratory data analysis was promoted by John Tukey to encourage statisticians visually to examine their data sets, to formulate hypotheses that could be tested on new data-sets.
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