Big Data simplified
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This document provides an overview of big data concepts including what big data is, how it is used, and common tools involved. It defines big data as a cluster of technologies like Hadoop, HDFS, and HCatalog used for fetching, processing, and visualizing large datasets. MapReduce and Hadoop clusters are described as common processing techniques. Example use cases mentioned include business intelligence. Resources for getting started with tools like Hortonworks, CloudEra, and examples of MapReduce jobs are also provided.
Big Data simplified
- 3. Big Data
- 5. What you can do with Big Data?
- 6. Big Data Big Data is a cluster of many technologies and tools that are used in various scenarios. (Hadoop + HDFS+ Hcatalog+Flume+PowerView) (HortonWorks + PowerView)
- 7. What you can do in Big Data? Fetching Processing Visualizing
- 8. How Big is Big Data? Byte of data: one grain of rice Kilobyte: cup of rice Megabyte: 8 bags of rice Gigabyte: 3 container of lorries Terabyte: 2 container ships Petabyte: covers Mumbai Exabyte: covers India Zettabyte: fills Indian Ocean
- 9. Big Data Industry Overview
- 11. MapReduce âąMapReduce is a processing technique and a program model for distributed computing based on java. âąThe MapReduce algorithm contains two important tasks, namely Map and Reduce.
- 12. Mapreduce
- 16. Hadoop Cluster
- 19. What you can do on Big Data? Get Started with this: CloudEra HortonWorks
- 20. Why Big Data? Business Intelligence
- 21. HortonWorks
- 22. Cloud Era
- 23. Why Hadoop? -> Hadoop modeling and development: MapReduce, Pig, Mahout -> Hadoop storage and data management: HDFS, HBase, Cassandra -> Hadoop data warehousing, summarization and query: Hive, Sqoop -> Hadoop data collection, aggregation and analysis: Chukwa, Flume -> Hadoop metadata, table and schema management: HCatalog -> Hadoop cluster management, job scheduling and workflow: ZooKeeper, Oozie and Ambari -> Hadoop Data serialization: Avro
- 24. Big Data in Nutshell
- 26. Got questions? Text/WhatsApp on 974-086-1099
- 28. What Next? Dive in and Explore
- 29. Typical Use Case
- 31. Resources https://ayende.com/blog/4435/map-reduce-a-visual-explanation MultiNode on Amazon: https://dzone.com/articles/how-set-multi-node-hadoop https://ayende.com/blog/4435/map-reduce-a-visual-explanation Run Sample MapReduce Examples: MapReduce examples: http://www.informit.com/articles/article.aspx?p=2190194&seqNum=3 https://hortonworks.com/hadoop-tutorial/how-to-process-data-with-apache-pig/