Devops:
DevOps (a clipped compound of "development" and "operations") is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of the DevOps movement is to strongly advocate automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevOps aims at shorter development cycles, increased deployment frequency, and more dependable releases, in close alignment with business objectives.
Big data:
Big data is a term used to refer to the study and applications of data sets that are so big and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.

Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem."[5] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on."[6] Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,connectomics, complex physics simulations, biology and environmental research.
What is Hadoop?

It is an open-source java-based software framework used for processing and storing big data in a distributed computing environment on large clusters of commodity hardware nodes.
With its Distributed File System, it is possible to handle thousands of terabyte data and also provides a faster data transfer among the nodes and allows the system to seamlessly continue its operations in case of node failure.
Hadoop is also called as Apache Hadoop, as is a part of Apache project, which is sponsored by Apache Software Foundation.

Devops:
DevOps (a clipped compound of "development" and "operations") is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of the DevOps movement is to strongly advocate automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevOps aims at shorter development cycles, increased deployment frequency, and more dependable releases, in close alignment with business objectives.
Big data:
Big data is a term used to refer to the study and applications of data sets that are so big and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.

Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem."[5] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on."[6] Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,connectomics, complex physics simulations, biology and environmental research.
What is Hadoop?

It is an open-source java-based software framework used for processing and storing big data in a distributed computing environment on large clusters of commodity hardware nodes.
With its Distributed File System, it is possible to handle thousands of terabyte data and also provides a faster data transfer among the nodes and allows the system to seamlessly continue its operations in case of node failure.
Hadoop is also called as Apache Hadoop, as is a part of Apache project, which is sponsored by Apache Software Foundation.

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