Description

IBM InfoSphere QualityStage Essentials v11.5 training program instructs how to assemble QualityStage equal employments that examine, normalize, coordinate, and solidify information records. Professionals will pick up understanding by building an application that consolidates client information from three source frameworks into a solitary ace client record.
Radiant Techlearning offers IBM InfoSphere QualityStage Essentials v11.5 training program in Classroom & Virtual Instructor Led/Online Mode.

 

Duration: 32 Hours

 

Learning Objectives

On completion of this course, professionals should be able to:

  • List the common data quality contaminants
  • Describe each of the following processes:
  • Investigation
  • Standardization
  • Match
  • Survivorship
  • Describe QualityStage architecture
  • Describe QualityStage clients and their functions
  • Import metadata
  • Build and run DataStage/QualityStage jobs, review results
  • Build Investigate jobs
  • Use Character Discrete, Concatenate, and Word Investigations to analyze data fields
  • Describe the Standardize stage
  • Identify Rule Sets
  • Build jobs using the Standardize stage
  • Interpret standardization results
  • Investigate unhandled data and patterns
  • Build a QualityStage job to identify matching records
  • Apply multiple Match passes to increase efficiency
  • Interpret and improve match results
  • Build a QualityStage Survive job that will consolidate matched records into a single master record
  • Build a single job to match data using a Two-Source match

Prerequisites

In order to benefit from this course, professionals should have prior knowledge in:

  • Familiarity with the Windows operating system
  • Familiarity with a text editor

Audience Profile

  • Data Analysts responsible for data quality using QualityStage
  • Data Quality Architects
  • Data Cleansing Developers

Course Details

Module 1 Data Quality Issues

  • Listing the common data quality contaminants
  • Describing data quality processes

Module 2 QualityStage Overview

  • Describing QualityStage architecture
  • Describing QualityStage clients and their functions

Module 3 Developing with QualityStage

  • Importing metadata
  • Building DataStage/QualityStage Jobs
  • Running jobs
  • Reviewing results

Module 4 Investigate

  • Building Investigate jobs
  • Using Character Discrete, Concatenate, and Word Investigations to analyze data fields
  • Reviewing results

Module 5 Standardize

  • Describing the Standardize stage
  • Identifying Rule Sets
  • Building jobs using the Standardize stage
  • Interpreting standardize results
  • Investigating unhandled data and pattern

Module 6 Match

  • Building a QualityStage job to identify matching records
  • Applying multiple Match passes to increase efficiency
  • Interpreting and improving Match results

Module 7 Survive

  • Building a QualityStage survive job that will consolidate matched records into a single master record

Module 8 Two-Source Match

Building a QualityStage job to match data using a reference match

FAQs

Q: What is data quality?

 

A: Data quality enables to cleanse and manage data while making it available across any organization. High-quality data starts strategic systems to integrate all related data that is to provide a complete view of the organization and the interrelationships within it. Data quality generally is an essential characteristic which determines the reliability of decision-making.

 

Q: What are the skills gained through this course?

 

A: After this course:

  • The professional will be able to describe Quality Stage clients and their functions
  • One will import metadata
  • One can build and run DataStage/QualityStage jobs, review results
  • One will be able to use Character Discrete, Concatenate, and Word Investigations to analyze data fields
  • One can describe the Standardize stage
  • One can identify Rule Sets
  • One will build jobs using the Standardize stage

 

Q: Who can take this course?

 

A: Data Analysts who are responsible for data quality using QualityStage, Data Quality Architects, Data Cleansing Developers. Before taking this course the candidates must have prior knowledge of windows operating system and text editor

 

Q: What are the benefits of data quality?

 

A: The benefits are:

  • It acts on trusted view
  • It accelerates data governance
  • Modernizes system with consolidation

 

Q: Name some data quality issues?

 

A: Some of the issues are:

  • Too much data
  • Inconsistent data
  • Incorrect data
  • Poor data security
  • Poor data recovery

 

Q: What is the benefit of doing training from Radiant Techlearning?

 

A: Radiant Techlearning is receptive to new ideas and always believes in a creative approach that makes learning easy and effective. We stand strong with highly qualified & certified technology Consultants, trainers and developers who believe in amalgamation of practical and creative training to groom the technical skills.

Our training programs are practical oriented with 70% – 80% hands on the training technology tool.  Our training program focuses on one-on-one interaction with each participant, latest content in curriculum, real time projects and case studies during the training program.

Our experts will also share best practices & will give you guidance to score high & perform better in your certification exams.

To ensure your success, we provide support session even after the training program.

You would also be awarded with a course completion certificate recognized by the industry after completion of the course & the assignment.

 

Q: How do you ensure the quality of training program?

 

A: Radiant has highly intensive selection criteria for Technology Trainers & Consultants, who deliver you training programs. Our trainers & consultants undergo rigorous technical and behavioural interview and assessment process before they are on boarded in the company.

Our Technology experts / trainers & consultant carry deep dive knowledge in the technical subject & are certified from the OEM.

Our training programs are practical oriented with 70% – 80% hands on the training technology tool.  Our training program focuses on one-on-one interaction with each participant, latest content in curriculum, real time projects and case studies during the training program.

Our faculty will provide you the knowledge of each course from fundamental level in an easy way and you are free to ask your doubts any time from your respective faculty.

Our trainers have patience and ability to explain difficult concepts in simplistic way with depth and width of knowledge.

To ensure quality learning, we provide support session even after the training program.

 

Q: What if I/we have doubts after attending your training program?

 

A: Radiant team of experts would be available on the email Support@radianttechlearning.com to answer your technical queries, even after the training program.

We also conduct a 3 – 4 hours online session after 2 weeks of the training program, to respond on your queries & project assigned to you.

 

Q: If I face technical difficulty during the class what should I do?

 

A: Technical issues are unpredictable and might occur with you as well. Participants have to ensure that they have the system with required configuration with good internet speed to access online labs.

If the problem still persists or you face any challenge during the class then you can report to us or your trainer. In that case Radiant would provide you the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.

 

Q: Does this training program include any project?

 

A: Yes, Radiant will provide you the most updated, high valued and relevant real time projects and case studies in each training program.

We included projects in each training program from fundamental level to advance level so that you don’t have to face any difficulty in future. You will work on highly exciting projects and that will upgrade your skill, knowledge and industry experience.

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