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Definition:- ‘Big Data’ is similar to ‘small data’, butbigger•…but having data bigger it requires differentapproaches:• Techniques, tools and architecture•…with an aim to solve new problems• …or old problems in a better way
4Ways of BigData:-i)Volume-->DataQuantityDataSpeed ii)Velocity-->DataSpeed DataTypes iii)Variety-->DataTypes iv)Veracity-->Messiness
Growth:-i)Increase of storage capacities ii)Increase of processing power iii)Availability of data
Applications:-i)Homeland Security ii)FinanceSmarter iii)Healthcare iv)Multi-channel sales v)Telecom vi)Manufacturing vii)Traffic Control viii)Trading Analytics
Hadoop Technology:-A scalable fault-tolerant grid operating system for data storage and processing Commodity hardware HDFS: Fault-tolerant high-bandwidth clustered storage MapReduce: Distributed data processing Works with structured and unstructured data Open source, Apache license
Components:-i)PIG-->DataFlow ii)HIVE-->BatchSQL iiii)SQOOP-->DataImport iv)ZOOKEEPER--Coordination v)CHUKWA-->Display & Monitoring vi)MAPREDUCE-->JobScheduling vii)HBASE-->RealTime Query viii)HDFS -->HadoopDistributedFileSystemix)AVRO-->Serialization
Benefits:-Hadoop is designed to run on cheap commodityhardware• It automatically handles data replication and nodefailure• Handles large volumes of unstructured data easily• Last but not least – its free! ( Open source)

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	Creado por tdharmaputhiran hace más de 10 años