Informatica Data Quality Analyst - Beginner's Guide (Udemy.com)
Informatica Data Quality (IDQ) Analyst Course
Created by: Sid Inf
Produced in 2019
What you will learn
- Perform data profiling and root cause analysis to identify data quality issues opportunities and provide recommendations to work with business and IT for remediation.
- Work with business stakeholders to gather requirements, conduct data profiling and track metrics.
- Proactively identify, prioritize and re-mediate data quality issues.
- Work with cross-functional areas: IT, Data Architecture, Data Integration, Business Intelligence, Analytics, and business stakeholders.
- Participate as a member of key cross-functional working groups related to data quality, and the companys Data Governance Working Group representing the data domain.
- Partners with development and business resources in all phases of Data Quality Implementation.
- Perform analysis and provide recommendations for modification or creation of business/technical rules based on data results.
- Excellent analytical ability to understand business issues associated with data
Quality Score
Overall Score : 74 / 100
Course Description
Business analysts and developers use Informatica Analyst for data-driven collaboration. You can perform column and rule profiling, scorecarding, and bad record and duplicate record management. You can also manage reference data and provide the data to developers in a data quality solution.
Organizations use Informatica Analyst to accomplish the following tasks:
Profile data. Create and run a profile to analyze the structure and content of enterprise data and identify strengths and weaknesses. After you run a profile, you can selectively drill down to see the underlying rows from the profile results. You can also add columns to scorecards and add column values to reference tables.
Create rules in profiles. Create and apply rules within profiles. A rule is reusable business logic that defines conditions applied to data when you run a profile. Use rules to further validate the data in a profile and to measure data quality progress.
Score data. Create scorecards to score the valid values for any column or the output of rules. Scorecards display the value frequency for columns in a profile as scores. Use scorecards to measure and visually represent data quality progress. You can also view trend charts to view the history of scores over time.
Manage reference data. Create and update reference tables for use by analysts and developers to use in data quality standardization and validation rules. Create, edit, and import data quality dictionary files as reference tables. Create reference tables to establish relationships between source data and valid and standard values. Developers use reference tables in standardization and lookup transformations in Informatica Developer.
Manage bad records and duplicate records. Fix bad records and consolidate duplicate records.
Who this course is for:
Business AnalystsData AnalystsData ScientistsData Analytics ProfessionalsData Warehouse ProfessionalsBig Data ProfessionalsETL ArchitectsETL DevelopersETL Testing/QA Professionals
Instructor Details
- 3.7 Rating
17 Reviews
Sid Inf
Business Intelligence Consultant and Trainer with 14+ years of extensive work experience on various client engagements. Delivered many large data warehousing projects and trained numerous professionals on business intelligence technologies. Extensively worked on all facets of data warehousing including requirement gathering, gap analysis, database design, data integration, data modeling, enterprise reporting, data analytics, data quality, data visualization, OLAP.
Has worked on broad range of business verticals and hold exceptional expertise on various ETL tools likeInformatica Powercenter, SSIS, ODI andIDQ, Data Virtualization, DVO,MDM.
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2019 - Language:
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