Data stream

This article is about the more general meaning of the term "data stream". For the UK-specific DSL technology called "Datastream", also see the IP Stream article.

In telecommunications and computing, a data stream is a sequence of digitally encoded coherent signals (packets of data or datapackets) used to transmit or receive information that is in transmission.

In electronics and computer architecture, a data stream determines for which time which data item is scheduled to enter or leave which port of a systolic array, a Reconfigurable Data Path Array or similar pipe network, or other processing unit or block. Often the data stream is seen as the counterpart of an instruction stream, since the von Neumann machine is instruction-stream-driven, whereas its counterpart, the Anti machine is data-stream-driven.

Non-SQL databases

Another solution would be to use an object-oriented database management system, which, as the name implies, is a database designed specifically for working with object-oriented values. Using an OODBMS would eliminate the need for converting data to and from its SQL form, as the data would be stored in its original object representation.

Databases such as Caché do not require manual ORM. SQL access to non-scalar values is already built in. Caché allows the developer to design any combination of OO and table structured storage within the database instead of resorting to external tool sets.

Object-oriented databases have yet to come into widespread use. One of their main limitations is that switching from an SQL DBMS to a purely object-oriented DBMS means you lose the capability to create SQL queries, a tried and tested method for retrieving ad-hoc combinations of data. For this reason, many programmers find themselves more at home with an object-SQL mapping system, even though most commercial object-oriented databases are able to process SQL queries to a limited extent. Caché has a built-in SQL parser so that interrogations on the object may be done in a straightforward SQL manner.

Data governance

Data governance encompasses the people, processes and technology required to create a consistent, enterprise view of an organisation's data in order to:

* Increase consistency & confidence in decision making
* Decrease the risk of regulatory fines
* Improve data security
* Maximize the income generation potential of data
* Designate accountability for information quality

Data Governance initiatives improve data quality by assigning a team responsible solely for data's accuracy, accessibility, consistency, and completeness, among other metrics. This team usually consists of executive leadership, project management, line-of-business managers, and data stewards. The team usually employs some form of methodology for tracking and improving enterprise data, such as six sigma, and tools for data mapping, profiling, cleansing and monitoring data.

Database transaction

A database transaction is a unit of work performed against a database management system or similar system that is treated in a coherent and reliable way independent of other transactions. A database transaction, by definition, must be atomic, consistent, isolated and durable. These properties of database transactions are often referred to by the acronym ACID.

Transactions provide an "all-or-nothing" proposition stating that work units performed in a database must be completed in their entirety or take no effect whatsoever. Further, transactions must be isolated from other transactions, results must conform to existing constraints in the database and transactions that complete successfully must be committed to durable storage.

Anti-spam techniques

The U.S. Department of Energy Computer Incident Advisory Capability (CIAC) has provided specific countermeasures against electronic mail spamming.

Some popular methods for filtering and refusing spam include e-mail filtering based on the content of the e-mail, DNS-based blackhole lists (DNSBL), greylisting, spamtraps, Enforcing technical requirements of e-mail (SMTP), checksumming systems to detect bulk email, and by putting some sort of cost on the sender via a Proof-of-work system or a micropayment. Each method has strengths and weaknesses and each is controversial due to its weaknesses.