Edw and hadoop

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A Hebrew Brief about Hadoop and what it is all about

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  • HI dear i am Priscilla by name, i read your profile and like to be in contact with you, that is why i drop this note for you, please i we like you to contact me in my privet mail box to enable me send my picture to you,and also tell you more about me thanks i we be waiting for your reply, (bernard_priscilla@yahoo.com)
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Edw and hadoop

  1. 1. EDW and HadoopWhere do WE Go from Here ?
  2. 2. • Hadoop –Enterprise DW– BI –
  3. 3. HADOOPCLUSTER Open Source - FAULT TOLERANT - - REPLICATION - MPP
  4. 4. HADOOP HADOOP •TERABYTE PETABYTE • -NODE
  5. 5. Hadoop Hadoop Distributed File System HDFS • Column Oriented HBASE • DW HIVE • Structured SQL UNSTRUCTED PIG • 4GLHADOOP Zookeeper • DICTIONARY
  6. 6. HADOOP COMMON COMPONENETS
  7. 7. HADOOP •– More than one-half (54%) of organizations surveyed are using or considering Hadoop for large-scale data processing needs– More than twice as many Hadoop users report being able to create new products and services and enjoy costs savings beyond those using other platforms; over 82% benefit from faster analyses and better utilization of computing resources– 87% of Hadoop users are performing or planning new types of analyses with large scale data– 94% of Hadoop users perform analytics on large volumes of data not possible before; 88% analyze data in greater detail; while 82% can now retain more of their data– Organizations use Hadoop in particular to work with unstructured data such as logs and event data (63%)– More than two-thirds of Hadoop users perform advanced analysis — data mining or algorithm development and testing
  8. 8. • “The bottom line is that Hadoop is the future of the cloud EDW, and its footprint in companies’ core EDW architectures is likely to keep growing throughout this decade. “ James Kobelius, Forrester Research• Companies will continue to use conventional BI for mainstream business users to do ad hoc queries and reports, but they will supplement that effort with a big- data analytics environment optimized to handle a torrent of unstructured data – which, of course, has been part of the goal of enterprise data warehousing for a long time.
  9. 9. HADOOP • • SQL • • • • • •
  10. 10. BIG DATA HADOOP BIGDATA • • •

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