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EDW and Hadoop

Where do WE Go from Here ?
•


      Hadoop –
Enterprise DW–
          BI –
HADOOP
CLUSTER                  Open Source       -




          FAULT TOLERANT               -

                                       -

     REPLICATION                       -
                   MPP
HADOOP
                     HADOOP •
TERABYTE
                   PETABYTE

                              •
           -NODE
Hadoop
     Hadoop Distributed File System HDFS •
    Column Oriented                HBASE •

                 DW              HIVE •
         Structured               SQL
                           UNSTRUCTED
                                  PIG •
             4GL
HADOOP                       Zookeeper •
         DICTIONARY
HADOOP COMMON COMPONENETS
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
• “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.
HADOOP
               •
               •
         SQL   •
               •
               •

               •

               •
               •
BIG DATA   HADOOP
           BIGDATA   •


                     •

                     •
Edw and hadoop

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Edw and hadoop

  • 1. EDW and Hadoop Where do WE Go from Here ?
  • 2. Hadoop – Enterprise DW– BI –
  • 3. HADOOP CLUSTER Open Source - FAULT TOLERANT - - REPLICATION - MPP
  • 4. HADOOP HADOOP • TERABYTE PETABYTE • -NODE
  • 5. Hadoop Hadoop Distributed File System HDFS • Column Oriented HBASE • DW HIVE • Structured SQL UNSTRUCTED PIG • 4GL HADOOP Zookeeper • DICTIONARY
  • 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. • “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. HADOOP • • SQL • • • • • •
  • 10. BIG DATA HADOOP BIGDATA • • •