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Data Wrangling
Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one " raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of data wrangling is to assure quality and useful data. Data analysts typically spend the majority of their time in the process of data wrangling compared to the actual analysis of the data. The process of data wrangling may include further munging, data visualization, data aggregation, training a statistical model, as well as many other potential uses. Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. It is closely aligned with the ETL process. Backg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Mapping
In computing and data management, data mapping is the process of creating data element mappings between two distinct data models. Data mapping is used as a first step for a wide variety of data integration tasks, including: * Data transformation or data mediation between a data source and a destination * Identification of data relationships as part of data lineage analysis * Discovery of hidden sensitive data such as the last four digits of a social security number hidden in another user id as part of a data masking or de-identification project * Consolidation of multiple databases into a single database and identifying redundant columns of data for consolidation or elimination For example, a company that would like to transmit and receive purchases and invoices with other companies might use data mapping to create data maps from a company's data to standardized ANSI ASC X12 messages for items such as purchase orders and invoices. Standards X12 standards are generic E ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Digital Library
A digital library (also called an online library, an internet library, a digital repository, a library without walls, or a digital collection) is an online database of digital resources that can include text, still images, audio, video, digital documents, or other digital media formats or a library accessible through the internet. Objects can consist of digitization, digitized content like Printing, print or photography, photographs, as well as born-digital, originally produced digital content like word processor files or social media posts. In addition to storing content, digital libraries provide means for organizing, searching, and information retrieval, retrieving the content contained in the collection. Digital libraries can vary immensely in size and scope, and can be maintained by individuals or organizations. The digital content may be stored locally, or accessed remotely via computer networks. These information retrieval systems are able to exchange information with each ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Lake
A data lake is a system or data repository, repository of data stored in its natural/raw format, usually object binary large object, blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc., and transformed data used for tasks such as Data reporting, reporting, data visualization, visualization, data analytics, advanced analytics, and machine learning. A data lake can include structured data from relational databases (rows and columns), semi-structured data (Comma-separated values, CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio data, audio, video). A data lake can be established ''on premises'' (within an organization's data centers) or ''in the cloud'' (using cloud services). Background James Dixon, then chief technology officer at Pentaho, coined the term by 2011 to contrast it with data mart, which is a smaller repository of interesting attribute ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for Business intelligence, reporting and data analysis and is a core component of business intelligence. Data warehouses are central Repository (version control), repositories of data integrated from disparate sources. They store current and historical data organized in a way that is optimized for data analysis, generation of reports, and developing insights across the integrated data. They are intended to be used by analysts and managers to help make organizational decisions. The data stored in the warehouse is uploaded from operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the data warehouse for reporting. The two main workflows for building a data warehouse system are extract, transform, load (ETL) and extract, load, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Consistency
Data inconsistency refers to whether the same data kept at different places do or do not match. Point-in-time consistency Point-in-time consistency is an important property of backup files and a critical objective of software that creates backups. It is also relevant to the design of disk memory systems, specifically relating to what happens when they are unexpectedly shut down. As a relevant backup example, consider a website with a database such as the online encyclopedia Wikipedia, which needs to be operational around the clock, but also must be backed up with regularity to protect against disaster. Portions of Wikipedia are constantly being updated every minute of every day, meanwhile, Wikipedia's database is stored on servers in the form of one or several very large files which require minutes or hours to back up. These large files—as with any database—contain numerous data structures which reference each other by location. For example, some structures are indexes whic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Validation
In computing, data validation or input validation is the process of ensuring data has undergone data cleansing to confirm it has data quality, that is, that it is 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 data consistency, consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Null Value
Null may refer to: Science, technology, and mathematics Astronomy *Nuller, an optical tool using interferometry to block certain sources of light Computing *Null (SQL) (or NULL), a special marker and keyword in SQL indicating that a data value does not exist, is not known, or is missing. *Null character, the zero-valued ASCII character, also designated by , often used as a terminator, separator or filler. This symbol has no visual representation. *Null device, a virtual file that discards data written to it, on Unix systems /dev/null *Null pointer or reference (sometimes written NULL, nil, or None), an object pointer (or reference) not currently set to point (or refer) to a valid object Mathematics *Null (mathematics), a zero value in several branches of mathematics Physics *Null (physics), a point in a field where the field quantity is zero *Null (radio), a concept in electromagnetism Arts and media *The Null Corporation, an imprint of the band Nine Inch Nails * ''Null'' (Intro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Cleaning
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. Data cleansing can be performed interactively using data wrangling tools, or through batch processing often via scripts 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 Structuring
Data ( , ) are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information can be extracted. Data are collected using techniques such as m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Discovery
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term "data mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (''mining'') of data itself. It also is a buzzword ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Wrangling From Messy To Clean Data Management
Data ( , ) are a collection of discrete or continuous values that convey information, describing the quantity, qualitative property, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpretation (logic), interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as table (information), tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be Data (computer science), used as variable (research), variables in a computational process. Data may represent abstract ideas or concrete measurements. Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw fact ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
