SAP Data Service Training Course Content

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SAP Data Service Training  Course Content Details

What is SAP data service

In computing, knowledge as a service (or DaaS) could be a relative of package as a service (SaaS). Like all members of the “as a service” (aaS) family, DaaS builds on the idea that the merchandise (data during this case) will be provided on demand to the user no matter geographic or structure separation of supplier and shopper. to boot, the emergence[when?] of service-oriented design (SOA) has additionally rendered the particular platform on that the info resides tangential. This development has enabled the emergence of the comparatively new idea of DaaS.[citation needed]SAP data service training in hyderabad kukatpally

Data provided as a service began primarily in net mashups, however as of 2015 is being progressively utilizedeach commercially and – less usuallyat intervals organisations like the world organization.

Traditionally, most organisations have used knowledge hold on in a very self-contained repository, that package was specifically developed to access and gift the info in a very human-readable kind. One results of this paradigm is that the bundling of each the info and also the package required to interpret it into one package, sold as a shopper product. because the range of bundled software/data packages proliferated and needed interaction among each other, another layer of interface was needed. These interfaces, together called enterprise application integration (EAI), usually attended encourage trafficker lock-in, because it is usually straightforward to integrate applications that area unit engineered upon identical foundation technology. For more info click here

SAP Data Service Course Content

01.DW Concepts

  • DW Lifecycle
  • DW Challenges

02.ETL Overview

  • ETL introduction
  • Staging Area
  • Business Rules
  • Performance
  • Slowly Changing Dimensions
  • Surrogate Keys
  • Facts and Dimension Tables
  • Different ETL Tools

03.Business Objects Overview

  • History
  • Components
  • Architecture

04.Data Services

  • Purpose of Data Services
  • Data Services architecture
  • Define Data Services objects
  • Data Services Designer interface

05.Data Services Objects

  • Object Hoerarchy
  • Jobs
  • Workflows
  • Data Flows

06.Environment setup

  • Creating repository
  • Setting Job Server
  • Setup for realtime operation
  • Setting multiple datastores
  • Starting Job servers

07.Source and Target Metadata

  • Data Stores
  • File formats for flat files
  • File formats for Excel files
  • File formats for XML files

08.Batch Jobs

  • Work with objects
  • Create a data flow
  • Use the Query transform
  • Use target tables
  • Execute the job


09.Troubleshooting Jobs

  • Use descriptions and annotations
  • Validate and tracing jobs
  • Use View Data and the Interactive Debugger
  • Use auditing in data flows

10.Functions,Scripts and Variables

  • Define built-in functions
  • Functions in expressions
  • Lookup function
  • Decode function
  • Variables and parameters
  • Data Services scripting language
  • Scripting custom functions

11.Important Transforms

  • Map Operation transform
  • Validation transform
  • Merge transform
  • Case transform
  • SQL transform
  • Other Transforms
  • Pivot transform
  • Hierarchy Flattening transform
  • Data Transfer transform
  • XML Pipeline transform

12.Other Transforms

  • Pivot transform
  • Hierarchy Flattening transform
  • Data Transfer transform
  • XML Pipeline transform

13.Error Handling

  • Recoverable work flows

14.Change Data Capture – Overview only

  • Update data over time
  • Database native CDC mechanisms
  • Source-based CDC
  • Target Comparison
  • Dataquality – Overview only
  • Fundamentals of DQ and Data Cleansing
  • Built in DQ Transformations
  • Data Validation
  • Name & Address cleansing
  • De duplication
  • Cleansing other data

15.Webservices and Realtime Integration – Overview only

  • Realtime jobs
  • SOAP Introduction
  • Web Services

SAP Data Service Training Demo

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Updated: May 11, 2017 — 4:59 am

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