Data Quality Fundamental Course
Understand key concepts, principles and terminology related to Data Quality
Business,Business Analytics and Intelligence,Data Quality Management
Lectures -36
Duration -2.5 hours
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Course Description
Data quality is not necessarily data that is devoid of errors. Incorrect data is only one part of the data quality equation. Managing data quality is a never-ending process. Even if a company gets all the pieces in place to handle today’s data quality problems, there will be new and different challenges tomorrow. That’s because business processes, customer expectations, source systems, and business rules all change continuously. To ensure high-quality data, companies need to gain a broad commitment to data quality management principles and develop processes and programs that reduce data defects over time.
Much like any other important endeavor, success in data quality depends on having the right people in the right jobs. This course helps you understand key concepts, principles, and terminology related to data quality and other areas of data management.
Goals
- Determine data quality requirements by studying business functions, gathering information, and evaluating output requirements and formats.
- Profile selects data sets to ensure quality and develops the data visualizations necessary to both manage and communicate data quality.
- Coordinate business efforts to deliver data that is fit for use in critical processes, analysis, and reports.
- Collaborate with business application team to document information architecture requirements as needed
- Serve as a subject matter expert and perform data quality-related functions for urgent, high-visibility, high-profile, and strategic projects while meeting challenging deadlines.
Prerequisites
- Basic understanding of Enterprise Data Management
- Basic understanding of Data Warehouse Concepts

Curriculum
Check out the detailed breakdown of what’s inside the course
Data Quality
5 Lectures
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What is Data Quality? 05:55 05:55
-
Example of Data Quality 07:53 07:53
-
Can we achieve 100 % Data Quality? 08:21 08:21
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What can be done to achieve 100% Data Quality? 07:42 07:42
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How can we measure Data Quality? 03:24 03:24
Data Quality Dimensions
8 Lectures

Data Quality Vs Data Governance
1 Lectures

Data Life Cycle
7 Lectures

Data Quality Life Cycle
1 Lectures

Data Profiling
4 Lectures

Business Expectations and Impacts of Low Data Quality
8 Lectures

Data Quality Roles
1 Lectures

Instructor Details

Inf Sid
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 like Informatica Power center, SSIS, ODI and IDQ, Data Virtualization, DVO, MDM.
Course Certificate
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