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An operational system is a term used in data warehousing to refer to a system that is used to process the day-to-day transactions of an organization. These systems are designed in a manner that processing of day-to-day transactions is performed efficiently and the integrity of the transactional data is preserved.
Sometimes operational systems are referred to as operational databases, transaction processing systems, or online transaction processing systems (OLTP). However, the use of the last two terms as synonyms may be confusing, because operational systems can be batch processing systems as well.
Any enterprise must necessarily maintain a lot of data about its operation.
| Organization | Probably |
|---|---|
| Manufacturing Company | Product data |
| Bank | Account Data |
| Hospital | Patient Data |
| University | Student Data |
| Government Department | Planning data |
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In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.
In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database.
In computer science, ACID is a set of properties of database transactions intended to guarantee data validity despite errors, power failures, and other mishaps. In the context of databases, a sequence of database operations that satisfies the ACID properties is called a transaction. For example, a transfer of funds from one bank account to another, even involving multiple changes such as debiting one account and crediting another, is a single transaction.
In computer science, transaction processing is information processing that is divided into individual, indivisible operations called transactions. Each transaction must succeed or fail as a complete unit; it can never be only partially complete.
A database transaction symbolizes a unit of work, performed within a database management system against a database, that is treated in a coherent and reliable way independent of other transactions. A transaction generally represents any change in a database. Transactions in a database environment have two main purposes:
In computing, extract, transform, load (ETL) is a three-phase process where data is extracted, transformed and loaded into an output data container. The data can be collated from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on reccurring schedules either as single jobs or aggregated into a batch of jobs.
The IBM Information Management System (IMS) is a joint hierarchical database and information management system that supports transaction processing.
Data engineering refers to the building of systems to enable the collection and usage of data. This data is usually used to enable subsequent analysis and data science; which often involves machine learning. Making the data usable usually involves substantial compute and storage, as well as data processing.
An operational data store (ODS) is used for operational reporting and as a source of data for the enterprise data warehouse (EDW). It is a complementary element to an EDW in a decision support environment, and is used for operational reporting, controls, and decision making, as opposed to the EDW, which is used for tactical and strategic decision support.
Online transaction processing (OLTP) is a type of database system used in transaction-oriented applications, such as many operational systems. "Online" refers to that such systems are expected to respond to user requests and process them in real-time. The term is contrasted with online analytical processing (OLAP) which instead focuses on data analysis.
A transaction processing system (TPS) is a software system, or software/hardware combination, that supports transaction processing.
Real-time business intelligence (RTBI) is a concept describing the process of delivering business intelligence (BI) or information about business operations as they occur. Real time means near to zero latency and access to information whenever it is required.
In information science and information technology, single source of truth (SSOT) architecture, or single point of truth (SPOT) architecture, for information systems is the practice of structuring information models and associated data schemas such that every data element is mastered in only one place, providing data normalization to a canonical form.
Operational intelligence (OI) is a category of real-time dynamic, business analytics that delivers visibility and insight into data, streaming events and business operations. OI solutions run queries against streaming data feeds and event data to deliver analytic results as operational instructions. OI provides organizations the ability to make decisions and immediately act on these analytic insights, through manual or automated actions.
Operational database management systems, are used to update data in real-time. These types of databases allow users to do more than simply view archived data. Operational databases allow you to modify that data, doing it in real-time. OLTP databases provide transactions as main abstraction to guarantee data consistency that guarantee the so-called ACID properties. Basically, the consistency of the data is guaranteed in the case of failures and/or concurrent access to the data.
Transaction data or transaction information is a category of data describing transactions. Transaction data/information gather variables generally referring to reference data or master data – e.g. dates, times, time zones, currencies.
The term is used for two different things:
The following is provided as an overview of and topical guide to databases:
Hybrid transaction/analytical processing (HTAP) is a term created by Gartner Inc., an information technology research and advisory company, in its early 2014 research report Hybrid Transaction/Analytical Processing Will Foster Opportunities for Dramatic Business Innovation. As defined by Gartner:
Hybrid transaction/analytical processing (HTAP) is an emerging application architecture that "breaks the wall" between transaction processing and analytics. It enables more informed and "in business real time" decision making.
TPC-C, short for Transaction Processing Performance Council Benchmark C, is a benchmark used to compare the performance of online transaction processing (OLTP) systems. This industry standard was published in August 1992, and eventually replaced the earlier TPC-A, which was declared obsolete in 1995. It has undergone a number of changes to keep it relevant as computer performance grew by several orders of magnitude, with the current version as of 2021, 5.11, released in 2010. In 2006, a newer OLTP benchmark was added to the suite, TPC-E, but TPC-C remains in widespread use.