Informatica Data Quality Online Training

Informatica Data Quality is the data quality management system developed by Informatica Corporation. Informatica Data Quality is a suite of applications and components that you can integrate with Informatica PowerCenter to deliver enterprise-strength data quality capability in a wide range of scenarios. The system is intended for empowering the organization for solving the data quality problems & achieve real, sustainable data quality improvements. With Informatica IDQ Training offered by BestOnlineTrainers, you will be able to increase your value in proactively monitoring and cleansing data and in empowering the business to share in the responsibility for data quality and governance. The course will help trainees in understanding the basics of data quality & the functionality of Informatica Data Quality.

Informatica Data Warehousing can be beneficial for:

• Professionals playing a key role in a data warehouse project, from project managers to DBAs to data modelers and application developers
• IT professionals who want to enhance their career by getting cross training into data warehousing
• IT Professionals who want to learn Informatica tool
• Students who are keen to learn about data warehousing, Informatica, Data Storage, Tera Data concepts, etc

We guarantee learning at your convenience & pace.

• Instant Access:
  Get instant access to self-paced training after signup.
• Streaming video recording:
  Watch lessons any time at your schedule, free recording.
• Exercises:
  Practical exercises help you test what you are learning as you go.
• Free Demo:
  Sign up for free demo to check whether the course is right for you and interact with the faculty live.
• Experienced Trainers:
  We only hire the industry’s best trainers
• Live free interactive web sessions:
  Ask the Expert Shell Scripting trainers about the career prospects and clarify your questions any time after you complete the course.
• Structured Curriculum Schedule:
  Progress with your complete daily interactive lessons and assignments.
• Faculty Mentoring:
  Turn in daily and weekly homework for personalized feedback from faculty.
• Virtual Office Hours:
  Live interaction with the faculty and other students around the world.
• Hands on Live Projects:
  Work on live lab sessions to tackle real-world projects. Get 100% faculty guidance and ratings.

Informatica Data Quality Online Training

• Informatica Analyst 9
• Analyst GUI
• Metadata and Data access/import
• Column Profiling
• Frequency/Patterns/Statistics/Drill downs
• Rule Profiling
• Out Of The Box rules
• Custom rules
• Reference Tables Management
• Project Collaboration
• Data Quality Score carding

Informatica Developer 9

• Developer GUI
• Developer Profiling including:
• Mid-stream profiling
• Join analysis profiling
• Building Data Quality Mapplets and Rules
• Data Standardization
• Cleanse, transform and parse data using DQ transformations such as the Case Converter, Merge, Labeler,Standardize, Parser
• Address Validation
• Perform address validation and create AV mapplets and mappings
• Matching
• Group data prior to matching to improve matching performance
• Perform DQ and Identity Matching to identify duplicate records
• Develop Matching Mapplets
• Associate and Consolidate matched data
• Work with the Data Quality Assistant
• Power Center Integration
• Parameterization Data Quality Workshop

Association/Consolidation Transformation

• Application and usage of the transformation to eliminate duplicates
• Using different strategies in Consolidation transformation
• Advanced Consolidation transformation usage and Row based

Address Validator Transformation

• Configuring AV transformation using the CMS
• Setting the properties in AD50.cfg file
• End to End scenario featuring the AV transformation

Match Transformation

• Configuring the Key gen transformation and Match
• Understanding the various strategies as a part of the classic Match transformation
• Setting the SSAPR and initializing IMO (Identity Match transformation)

Exception Transformation

• Configuring Bad Record/Consolidation exception transformation
• Editing the DQA tables as a part of the Analyst tool
• Recycling records using Exception transformation

Usage of All Data Quality Transformations in a customer scenario Example of an All DQ Mapping with optimized results