DataStage Online Training

One of the most demand course in market is data ware house which has many ETL tools and one of them is datastage which has been given a brief elaboration for the students.

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Overview of datastage:

Retors Lernen labs introduces many latest courses that are highly demand in market for aspirants who are looking forward for a great career in their respective fields. One of the most demand course in market is data ware house which has many ETL tools and one of them is datastage which has been given a brief elaboration for the students. Datastage is an ETL tool that extracts data from different sources to transform in such a way that the end result meets the business needs or requirements. There are many of types of files like sequential files, databases, indexed files from which the data is extracted and analysis is done from source to target. It has many advantages like it can integrate data from any organization and can load it to any external data source. It supports parallel processing of files and can access data from these sources to perform operations or modifications. Few of the stages performed in the process of getting output like filter stage, aggregator stage, lookup stage, copy stage and sort stage.

The architecture of datastage has four components they are administrator, manger, designer and director. In administrator stage the projects are assigned, setup datastage users. Manager helps in storage and usage of metadata. In Designer interface stage creating applications and jobs are performed means source and destination are defined. In director phase jobs are executed, monitored and scheduled. Datastage jobs are performed by linking stages to define data and process flows. Datastage job sequence specifies particular sequence of jobs to be performed. Datastage shared containers has reusable job elements comprising many links and stages. Datastage stages has built in components which defines particular process. Table definitions means a set of related columns which are stored in repository.

Why data stage?

Many organizations and companies maintain databases to store data it may be the details of employees , project details and many other databases are stored which are required for functions or operations depending on the requirement of the client or company. Many ETL tool are used by the companies for extracting, transforming and loading data into the systems the popular and flexible tool for this operations is data stage. Its necessity and requirement has been increased more and more in the present market. Professionals from analyst field, web developers, and software developers are showing more interest in using this tool. It is mainly used for data integration means extract data from one or many sources, transform as per the company needs and load them into the target destinations. The main advantage of this tool which is increasing demand in the market because it supports graphical user interface for ETL operations.

It is more of technically advantage for the organisations as it doesn’t require more training for the developers and supports reuse of the end product. It helps in saving time as it prepares documentation by its own that means it supports self-documentation which helps the team members to discuss sessions regarding projects frequently. There are many other powerful ETL tools like informatica and others it supports many features like it supports multiple partitioning where data is processed and recollected with datastage. It offers 7 types of multi-processing partitions and it lets drag and drop functionality which helps clients to understand the process easily. There are upto 60 transformation stages built in stages of datastage. The latest editions of datastage are available in the market like enterprise edition, server edition, MVS edition and IBM infosphere data stage.

Eligibility criteria:

The eligibility criteria for this tool are

  • The candidate should have minimum experience in data ware house
  • They should have capability to understand the client requirements
  • Candidate should have good problem skill
  • They should have knowledge on ETL and interfaces working
  • Minimum of computer graduation with knowledge on databases and their functionality

Prerequisites:

The prerequisites for learning this course are

  • Basic knowledge in data ware, data science
  • knowledge in UNIX helps to write scripts
  • basic knowledge on data bases and sql

Learning outcomes:

  • Basic understanding of datastage tool and its uses
  • Managing RDBMS
  • One can learn how to manage, create and delete process in projects
  • Processing, debugging can be learned
  • how to load data into multiple destinations
  • One can learn how to extract data and the process of putting them in sequential way
  • One can understand how data is operated in different computer architectures.

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Key Features

Assignment based real time project oriented training

Trainers handpicked from the Corporate World who have got exposure to work with Global MNCs.

Highly interactive and work on very limited batch size to maintain a proper faculty student ratio

After training support in terms of resume preparation and placement
assistance.

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