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Big Data simplified


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Big Data Analytics in simple ways.

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Big Data simplified

  1. 1. BIG DATA simplified! Pravin Hanchinal
  2. 2. Before we start...
  3. 3. Big Data
  4. 4. What you can do with Big Data?
  5. 5. 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)
  6. 6. What you can do in Big Data? Fetching Processing Visualizing
  7. 7. 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
  8. 8. Big Data Industry Overview
  9. 9. MapReduce •MapReduce is a processing technique and a program model for distributed computing based on java. •The MapReduce algorithm contains two important tasks, namely Map and Reduce.
  10. 10. Mapreduce
  11. 11. Hadoop Cluster
  12. 12. What you can do on Big Data? Get Started with this: CloudEra HortonWorks
  13. 13. Why Big Data? Business Intelligence
  14. 14. HortonWorks
  15. 15. Cloud Era
  16. 16. 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
  17. 17. Big Data in Nutshell
  18. 18. Got questions? Text/WhatsApp on 974-086-1099
  19. 19. Stay connected
  20. 20. What Next? Dive in and Explore
  21. 21. Typical Use Case
  22. 22. Resources h-virtualbox/
  23. 23. Resources MultiNode on Amazon: Run Sample MapReduce Examples: MapReduce examples: