What Exactly is Big Data?
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How does Big Data affect technology?
Big Data affects technology by creating a space for developing new softwares. Since the beginning and implementation of Big Data, companies how found a need to fill when it comes to organizing the information. As well as the organization of these large data sets, the usage of the information collected has become just as vastly important. Collecting, organizing, clearing and distributing the information has generated a market for developing softwares. |
Emerging Technologies surrounding Big Data
Column-oriented databases
Traditional, row-oriented databases are excellent for online transaction processing with high update speeds. Column-oriented databases store data with a focus on columns, instead of rows, allowing for huge data compression and very fast query times. |
NoSQL databases
There are several database types that fit into this category, such as key-value stores and document stores, which focus on the storage and retrieval of large volumes of unstructured, semi-structured, or even structured data. |
Hadoop
An open source platform software infrastructure for storing and processing large data sets. It is flexible enough to be able to work with multiple data sources, either aggregating multiple sources of data in order to do large scale processing, or even reading data from a database in order to run processor-intensive machine learning jobs. It has several different applications, but one of the top use cases is for large volumes of constantly changing data, such as location-based data from weather or traffic sensors, web-based or social media data, or machine-to-machine transactional data.
An open source platform software infrastructure for storing and processing large data sets. It is flexible enough to be able to work with multiple data sources, either aggregating multiple sources of data in order to do large scale processing, or even reading data from a database in order to run processor-intensive machine learning jobs. It has several different applications, but one of the top use cases is for large volumes of constantly changing data, such as location-based data from weather or traffic sensors, web-based or social media data, or machine-to-machine transactional data.