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Data Quality Firewall
A data quality firewall is the use of software to protect a computer system from the entry of erroneous, duplicated or poor quality data. Gartner estimates that poor quality data causes failure in up to 50% of customer relationship management systems.{{Citation needed, date=July 2008 Older technology required the tight integration of data quality software, whereas this can now be accomplished by loosely coupling technology in a service-oriented architecture. Features and functionality A data quality firewall guarantees database accuracy and consistency. This application ensures that only valid and high quality data enter the system, which means that it obliquely protects the database from damage; this is extremely important since database integrity and security are absolutely essential. A data quality firewall provides real time feedback information about the quality of the data submitted to the system. The main goal of a data quality process consists in capturing erroneous and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gartner
Gartner, Inc is a technological research and consulting firm based in Stamford, Connecticut that conducts research on technology and shares this research both through private consulting as well as executive programs and conferences. Its clients include large corporations, government agencies, technology companies, and investment firms. In 2018, the company reported that its client base consisted of over 12,000 organizations in over 100 countries. As of 2022, Gartner has over 15,000 employees located in over 100 offices worldwide. It is a member of the S&P 500. History Gideon Gartner founded Gartner, Inc in 1979. Originally private, the company launched publicly as Gartner Group in 1986 before Saatchi & Saatchi acquired it in 1988. In 1990, Gartner Group was acquired by some of its executives, including Gartner himself, with funding from Bain Capital and Dun & Bradstreet. The company went public again in 1993. In 2000, the name was simplified from ''Gartner Group'' to Gartn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Customer Relationship Management
Customer relationship management (CRM) is a process in which a business or other organization administers its interactions with customers, typically using data analysis to study large amounts of information. CRM systems compile data from a range of different communication channels, including a company's website, telephone, email, live chat, marketing materials and more recently, social media. They allow businesses to learn more about their target audiences and how to best cater for their needs, thus retaining customers and driving sales growth. CRM may be used with past, present or potential customers. The concepts, procedures, and rules that a corporation follows when communicating with its consumers are referred to as CRM. This complete connection covers direct contact with customers, such as sales and service-related operations, forecasting, and the analysis of consumer patterns and behaviors, from the perspective of the company. According to Gartner, the global CRM market ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Quality
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for tsintended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. When this is the case, data governance is used to form agreed upon definitions and standards for data quality. In such cases, data cleansing, including standardization, may be required in order to ensure data quality. Definitions Defining data quality is difficult due to the ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Service-oriented Architecture
In software engineering, service-oriented architecture (SOA) is an architectural style that focuses on discrete services instead of a monolithic design. By consequence, it is also applied in the field of software design where services are provided to the other components by application components, through a communication protocol over a network. A service is a discrete unit of functionality that can be accessed remotely and acted upon and updated independently, such as retrieving a credit card statement online. SOA is also intended to be independent of vendors, products and technologies. Service orientation is a way of thinking in terms of services and service-based development and the outcomes of services. A service has four properties according to one of many definitions of SOA: # It logically represents a repeatable business activity with a specified outcome. # It is self-contained. # It is a black box for its consumers, meaning the consumer does not have to be aware of the s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Quality
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for tsintended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. When this is the case, data governance is used to form agreed upon definitions and standards for data quality. In such cases, data cleansing, including standardization, may be required in order to ensure data quality. Definitions Defining data quality is difficult due to the ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Cleansing
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting or a data quality firewall. After cleansing, a data set should be consistent with other similar data sets in the system. The inconsistencies detected or removed may have been originally caused by user entry errors, by corruption in transmission or storage, or by different data dictionary definitions of similar entities in different stores. Data cleaning differs from data validation in that validation almost invariably means data is rejected from the system at entry and is performed at the time of entry, rather than on batches of data. The actual process of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Validation
In computer science, data validation is the process of ensuring data has undergone data cleansing to ensure they have data quality, that is, that they are both correct and useful. It uses routines, often called "validation rules", "validation constraints", or "check routines", that check for correctness, meaningfulness, and security of data that are input to the system. The rules may be implemented through the automated facilities of a data dictionary, or by the inclusion of explicit application program validation logic of the computer and its application. This is distinct from formal verification, which attempts to prove or disprove the correctness of algorithms for implementing a specification or property. Overview Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. Thei ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
