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Oracle Database Select database Category There are 4 new stages in the database That is in 8 version I way Enterprise Classic Federation Netezza Enterprise ODBC To read the data from Oracle We have 4 options in Reading Method Read Method = Table /user-defined SQL / Auto generated / SQL builder generated SQL Oracle Data set… Continue reading Oracle stage properties
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Features of Data Stage Any to Any Platform Independent Node Configuration Portion Parallelism Pipeline Parallelism Any to Any Reads the data from any Source and loads it to any Target. Any SRC ↔ Any Target Platform Independent Designed for one O.S, can be executed – – >Platform generally can be either Software or Hardware.… Continue reading Runtime Architecture
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What is the Unstructured Data? Unstructured data is an information that does not have a predefined data model or does not fit well into relational tables. It is broadly classified into two types Non-Textual unstructured data is a multimedia data like still images, videos, and MP3 audio files Textual unstructured data are like email messages, instant messages,… Continue reading Excel Data in Datastage (unstructured datastage)
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In general, we have 4 Architecture Simple ODS – Operations Data source NDS – Normal Data source Integrity we can implement this Architecture either in Inmon Model or Kimball Model Top to bottom Bottom to top Universally – 8 Architecture Inmon – Simple, ODS, NDS, Integrity Kimbell – Simple, ODS, NDS, Integrity. Simple SRC… Continue reading Datastage data Architecture
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Table name = dim 1 Write method = upset Upset order = update then insert Compile and RUN In SQL plus, Select * from dim 1; Skip S no S name 1 111 shilpa 2 222 Renuka 3 333 Archama To insert new values delete SRC ; Insert in to SRC Values (222, ‘Anil’); Insert… Continue reading Oracle Enterprise stage
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EX:- Suppose we have an customer Table, we have some fields which are frequently, ofliny, slowly, Rarely, Rapidly changed Different types of loadings Initial incremental Initial data (source) :- C ID CN Add 11 A HYD stored in Achieve Data base or OLTP… Continue reading Slowly Changing Dimensions
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Combining primary rows with Secondary rows based on key column values The stage that perform Horizontal combining are Join Look – up Merge These Stage differ with each other w. r. t input requirements Treatment of unmatched records Memory usage Description join lookup Merge Input Names Primary /i/pReference lookupS1 – -> lookup Types of joins… Continue reading Overview of Combining
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Step 1 Start DB/2 repository and Data stage Server (In the Task box, we have a Green colour icon, àRight click àStart) DataStage Server Start Program Web sphere Application server profiles à default start the server Next click on Web Console we find the login page that is Server has Started If the server is not started, the page cannot be… Continue reading Scheduling Batches
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Partitioning is the process of dividing an input data set into multiple segments, or partitions. Each processing node in your system then performs an operation on an individual partition of the data set rather than on the entire data set. Data Stage basically allows 2 types of partitioning: Key Based Partitioning Keyless Partitioning How to… Continue reading Overview of data process for combine and Partitioning
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It is a processing stage that supports n inputs and 1 output. Combining Source 1 and Source 1 without any key dependency Funnel requirements Structure of Source 1 and Source 2 should be the same Column Names should be the same in Source 1 and Source 2. Funnel types We have 3 Funnel types Continuous… Continue reading Combine data using the Funnel stage
