Picking up from where we left off in the last part, here is a list of some more of the big data terminologies simplified
1. Legacy System–In the context of computing, this refers to outdated computer systems, programming languages or application software that are used instead of available upgraded versions. It refers to a system's difficulty (or inability) to be maintained, supported or improved, but continues to be used because it performs a needed function adequately.
2. Load Balancing–This basically refers to dividing the amount of work that a single computer has to do multiple computers or servers, so that more work gets done in the same amount of time, in order to achieve optimal results and utilization of the system.
3. Massively Parallel Processing- Refers to the co-ordinated processing of a programme using multiple processors (or Computers) to perform certain computational tasks at the same time. Each of the processor use its own operating system and memory.
4. NoSQL - NoSQL, often referred to as ‘Not Only SQL’ is a database management systems (DBMS) that do not follow all of the rules of a relational DBMS. They are used for very large databases which are particularly prone to performance problems caused by the limitations by traditional SQL. It is more consistent and can achieve higher availability and horizontal scaling.
5. Natural Language Processing - A component of Artificial Intelligence, NLP is the ability of a computer to understand human speech as it is spoken.
6. Object – Based Image Analysis -Digital images analysis can be performed with data from individual pixels, whereas big data object-based image analysis uses data from a selection of related pixels, called objects or image objects.
7. Oozie – This is a workflow processing system that lets users define a series of jobs written in multiple languages – such as Map Reduce, Pig and Hive -- then intelligently link them to one another. Oozie allows users to specify, for example, that a particular query is only to be initiated after specified previous jobs on which it relies for data are completed
8. Ontology – A term borrowed from Philosophy, Ontology means a systematic account of Existence. In computing, ontology is an explicit specification of a conceptualization. Ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for a domain
9. RFID – RFID or Radio Frequency Identification is a technology that incorporates the use of electromagnetic or electrostatic coupling in the radio frequency (RF) portion of the electromagnetic spectrum to uniquely identify an object, animal, or person.
10. Sentiment Analysis –Sentiment Analysis, also known as opinion mining is a process for tracking the mood of the public about a certain product, for example, by building a system to examine the conversations happening around it.
Hope these help you understand big data better.