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  2. Kimball lifecycle - Wikipedia

    en.wikipedia.org/wiki/Kimball_lifecycle

    It involves the database environment as well as security. Extract, transform, load (ETL) design and development is the design of some of the heavy procedures in the data warehouse and business intelligence system. Kimball et al. suggests four parts to this process, which are further divided into 34 subsystems [3]: Extracting data

  3. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...

  4. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    The process of dimensional modeling builds on a 4-step design method that helps to ensure the usability of the dimensional model and the use of the data warehouse. The basics in the design build on the actual business process which the data warehouse should cover. Therefore, the first step in the model is to describe the business process which ...

  5. Database security - Wikipedia

    en.wikipedia.org/wiki/Database_security

    One technique for evaluating database security involves performing vulnerability assessments or penetration tests against the database. Testers attempt to find security vulnerabilities that could be used to defeat or bypass security controls, break into the database, compromise the system etc. Database administrators or information security administrators may for example use automated ...

  6. Data-centric security - Wikipedia

    en.wikipedia.org/wiki/Data-centric_security

    Data-centric security is an approach to security that emphasizes the dependability of the data itself rather than the security of networks, servers, or applications.Data-centric security is evolving rapidly as enterprises increasingly rely on digital information to run their business and big data projects become mainstream.

  7. Data vault modeling - Wikipedia

    en.wikipedia.org/wiki/Data_Vault_Modeling

    Data vault is designed to avoid or minimize the impact of those issues, by moving them to areas of the data warehouse that are outside the historical storage area (cleansing is done in the data marts) and by separating the structural items (business keys and the associations between the business keys) from the descriptive attributes.

  8. Data security - Wikipedia

    en.wikipedia.org/wiki/Data_security

    Software-based security solutions encrypt the data to protect it from theft. However, a malicious program or a hacker could corrupt the data to make it unrecoverable, making the system unusable. Hardware-based security solutions prevent read and write access to data, which provides very strong protection against tampering and unauthorized access.

  9. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    Collecting data from numerous sources and analyzing it using different data analysis tools has its advantages, including overcoming the risk of method bias; using data from different sources and analyzing it using multiple analysis methods guarantees businesses and organizations robust and reliable findings they can use in decision making.