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In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.
By contrast, column-oriented DBMS store all data from a given column together in order to more quickly serve data warehouse-style queries. Correlation databases are similar to row-based databases, but apply a layer of indirection to map multiple instances of the same value to the same numerical identifier.
All data can therefore be accessed and read without a Database Management System (DBMS), or CHRONOS itself, as it is in plain text format. This eliminates the need for maintaining a DBMS solely for reading preserved static databases as well as the need to, potentially riskily, migrate database files to newer database formats. [ 9 ]
Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.
Hierarchical storage management (HSM), also known as tiered storage, [1] is a data storage and data management technique that automatically moves data between high-cost and low-cost storage media. HSM systems exist because high-speed storage devices, such as solid-state drive arrays, are more expensive (per byte stored) than slower devices ...
Data management solutions are tools and technologies that organizations use to manage their data. These solutions can include a wide range of different tools and technologies, such as databases and data warehouses, data integration and ETL (extract, transform, load) tools, data governance and quality tools, and data visualization and reporting ...
Data can be described as the elements or units in which knowledge and information is created, [2] and metadata are the summarizing subsets of the elements of data; or the data about the data. [3] The main goal of data preservation is to protect data from being lost or destroyed and to contribute to the reuse and progression of the data.
A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; [2] this may lead to data being well-managed in the present ...