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Data sanitization methods are also applied for the cleaning of sensitive data, such as through heuristic-based methods, machine-learning based methods, and k-source anonymity. [ 2 ] This erasure is necessary as an increasing amount of data is moving to online storage, which poses a privacy risk in the situation that the device is resold to ...
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]
Google Sheets – as part of Google Workspace; iRows – closed since 31 December 2006; JotSpot Tracker – acquired by Google Inc. Smartsheet – Online spreadsheet for project management, interactive Gantt, file sharing, integrated with Google Apps [8] Sourcetable [9] – AI spreadsheet that generates formulas, charts, SQL, and analyzes data.
Data center-infrastructure management (DCIM) is the integration [25] of information technology (IT) and facility management disciplines [26] to centralize monitoring, management and intelligent capacity planning of a data center's critical systems. Achieved through the implementation of specialized software, hardware and sensors, DCIM enables ...
A key component of the security-readiness evaluation is the policies that govern the application of security in the network including the data center. The application includes both the design best practices and the implementation details. [2] As a result, security is often considered as a key component of the main infrastructure requirement.
Data center services encompass all of the services and facility-related components or activities that support the implementation, maintenance, operation, and enhancement of a data center, [1] which is an environment that provides processing, storage, networking, [2] management and the distribution of data within an enterprise.
The lights-out [45] data center, also known as a darkened or a dark data center, is a data center that, ideally, has all but eliminated the need for direct access by personnel, except under extraordinary circumstances. Because of the lack of need for staff to enter the data center, it can be operated without lighting.
[21] [22] The need for data cleaning will arise from problems in the way that the datum are entered and stored. [21] Data cleaning is the process of preventing and correcting these errors. Common tasks include record matching, identifying inaccuracy of data, overall quality of existing data, deduplication, and column segmentation. [23]