Dan Linstedt
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Dan Linstedt
Daniel Linstedt is an American data architect known for having developed the data modeling method data vault for data warehouses and business intelligence. He developed the model in the 1990s and published the first version in the early 2000s. In 2012, Data Vault 2.0 was announced and it was released in 2013. In addition to data modeling, the data vault method incorporates process design, database tuning and performance improvements for ETL/ ELT, Capability Maturity Model Integration (CMMI) and agile software development. Dan holds a Bachelor of Science in computer science from California State University, Chico. Since 2020, he has been the chief executive officer (CEO) of DataVaultAlliance Holdings LLC. Selected works * ''The Business of Data Vault Modeling'' (2010-11-19) by author Daniel Linstedt and co-authors Kent Graziano and Hans Hultgren * ''Super Charge Your Data Warehouse: Invaluable Data Modeling Rules to Implement Your Data Vault (Data Warehouse Architecture Book 1)' ...
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Data Architect
A data architect is a practitioner of data architecture, a data management discipline concerned with designing, creating, deploying and managing an organization's data architecture. Data architects define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way. It is closely allied with business architecture and is considered to be one of the four domains of enterprise architecture. Role According to the Data Management Body of Knowledge, the data architect “provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture.” According to the Open Group Architecture Framework (TOGAF), a data architect is expected to set data architecture principles, create models of data that enable the implementation of ...
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Agile Software Development
In software development, agile (sometimes written Agile) practices include requirements discovery and solutions improvement through the collaborative effort of self-organizing and cross-functional teams with their customer(s)/ end user(s), adaptive planning, evolutionary development, early delivery, continual improvement, and flexible responses to changes in requirements, capacity, and understanding of the problems to be solved. Popularized in the 2001 ''Manifesto for Agile Software Development'', these values and principles were derived from and underpin a broad range of software development frameworks, including Scrum and Kanban. While there is much anecdotal evidence that adopting agile practices and values improves the effectiveness of software professionals, teams and organizations, the empirical evidence is mixed and hard to find. History Iterative and incremental software development methods can be traced back as early as 1957, Gerald M. Weinberg, as quoted in " ...
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Living People
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Data Architecture
Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. Overview A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration, for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems. A data architecture, in part, describes the data structures used by a business and its computer applications software. Data architectures address data in storage, data in use, and data in motion; descriptions of data stores, data groups, and data items; and mappings of those data artifacts to data qualities, applications, locations ...
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Chief Executive Officer
A chief executive officer (CEO), also known as a central executive officer (CEO), chief administrator officer (CAO) or just chief executive (CE), is one of a number of corporate executives charged with the management of an organization especially an independent legal entity such as a company or nonprofit institution. CEOs find roles in a range of organizations, including public and private corporations, non-profit organizations and even some government organizations (notably state-owned enterprises). The CEO of a corporation or company typically reports to the board of directors and is charged with maximizing the value of the business, which may include maximizing the share price, market share, revenues or another element. In the non-profit and government sector, CEOs typically aim at achieving outcomes related to the organization's mission, usually provided by legislation. CEOs are also frequently assigned the role of main manager of the organization and the highest-ranking offic ...
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California State University, Chico
California State University, Chico, or commonly, Chico State, is a public university in Chico, California. Founded in 1887, it is the second oldest campus in the California State University system. As of the fall 2020 semester, the university had a total enrollment of 16,630 students. The university offers 126 bachelor's degree programs, 35 master's degree programs, and four types of teaching credentials. Chico is a Hispanic-serving institution (HSI). History On March 12, 1887, a legislative act was enacted to create the Northern Branch of the California State Normal School. Less than a month later, Chico was chosen as the location. On June 24, 1887, General John Bidwell donated of land from his cherry orchard. Then on July 4, 1888, the first cornerstone was laid. On September 3, 1889, doors opened for the 90 enrolled students. The library opened on January 11, 1890, with 350 books. On June 20, 1891, the first graduation took place, a class of 15. In 1910, Annie Kennedy Bidw ...
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Computer Science
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to Applied science, practical disciplines (including the design and implementation of Computer architecture, hardware and Computer programming, software). Computer science is generally considered an area of research, academic research and distinct from computer programming. Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing Vulnerability (computing), security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Progr ...
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Bachelor Of Science
A Bachelor of Science (BS, BSc, SB, or ScB; from the Latin ') is a bachelor's degree awarded for programs that generally last three to five years. The first university to admit a student to the degree of Bachelor of Science was the University of London in 1860. In the United States, the Lawrence Scientific School first conferred the degree in 1851, followed by the University of Michigan in 1855. Nathaniel Southgate Shaler, who was Harvard's Dean of Sciences, wrote in a private letter that "the degree of Bachelor of Science came to be introduced into our system through the influence of Louis Agassiz, who had much to do in shaping the plans of this School." Whether Bachelor of Science or Bachelor of Arts degrees are awarded in particular subjects varies between universities. For example, an economics student may graduate as a Bachelor of Arts in one university but as a Bachelor of Science in another, and occasionally, both options are offered. Some universities follow the Oxford a ...
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Capability Maturity Model Integration
Capability Maturity Model Integration (CMMI) is a process level improvement training and appraisal program. Administered by the CMMI Institute, a subsidiary of ISACA, it was developed at Carnegie Mellon University (CMU). It is required by many U.S. Government contracts, especially in software development. CMU claims CMMI can be used to guide process improvement across a project, division, or an entire organization. CMMI defines the following maturity levels for processes: Initial, Managed, Defined, Quantitatively Managed, and Optimizing. Version 2.0 was published in 2018 (Version 1.3 was published in 2010, and is the reference model for the rest of the information in this article). CMMI is registered in the U.S. Patent and Trademark Office by CMU. Overview Originally CMMI addresses three areas of interest: #Product and service development – CMMI for Development (CMMI-DEV), #Service establishment, management, – CMMI for Services (CMMI-SVC), and #Product and service acquisi ...
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Data Modeling
Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. Overview Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system. There are three different types of data models produced while progressing from requirements to the actual database to be used for the information system.Simison, Graeme. C. & Witt, Graham. C. (2005). ''Data Modeling Essentials''. 3rd Edition. Morgan Kaufmann Publishers. The data requirements are initially recorded as a conceptual data model which is essentially a set of technology independent specifications about the data and is used to discuss initial requirements with ...
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Extract, Load, Transform
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format. This enables faster loading times. However, ELT requires sufficient processing power within the data processing engine to carry out the transformation on demand, to return the results in a timely manner. Since the data is not processed on entry to the data lake, the query and schema do not need to be defined a priori (although often the schema will be available during load since many data sources are extracts from databases or similar structured data systems and hence have an associated schema). ELT is a data pipeline model.Using Redshift Spectrum to load data ...
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