course | Data Quality Management
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DIGTR-760 | Data Quality Management
Course Sector : Digital Transformation and Innovation
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 2025-04-14 | 2025-04-18 | Barcelona | $4,950 | Book now |
| 5 Days | 2025-05-11 | 2025-05-15 | Riyadh | $4,250 | Book now |
| 5 Days | 2025-09-15 | 2025-09-19 | Abu Dhabi | $4,250 | Book now |
| 5 Days | 2025-09-22 | 2025-09-26 | Dubai | $4,250 | Book now |
| 5 Days | 2025-11-03 | 2025-11-07 | Los Angeles | $5,950 | Book now |
| 5 Days | 2025-12-22 | 2025-12-26 | Dubai | $4,250 | Book now |
Course Introduction
This 2-days Data Quality Management training program address the key aspects of Data Quality management & provides practical take away actions that will enable you to start a Data Quality initiative in your organization.
The training program draws up the Data Quality discipline as defined in the DAMA body of knowledge (DMBoK).
Course objective
- Understand The Business Rules of Data Quality.
- Identify Data Lifecycle Management (DLM).
- Understand Data Governance Management Standards and Compliance.
- Identify Differences between Good data quality and Bad data quality.
- Understand Data Quality Management approach and Scenarios.
- Identify DQ Tools and features.
- Understand the DAMA DMBoK Wheel.
- Master using data analysis Techniques.
- Master use profiling to assess Data Quality.
- Identify Data Correction Techniques.
- Understand How to Demystify Data Cleansing.
- Understand DMBoK Dimensions of Data Quality.
- Master applying Data Quality Dimensions.
- Understand how to apply Root cause analysis process and the 5-Why Approach for better DQ.
- Define financial cost of data quality management.
- Understand How to Create the Data Quality Roadmap.
- Master avoiding common data quality mistakes.
- Create Data Governance Management Action Plan.
Training Methodology
The training program is implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).
This program focuses on exercises, case studies, workshops, and individual and group presentations, among other integrated training methodologies.
A detailed report is submitted to each participant and the training department in your organization on the results of the participant's performance and the return on training.
Course Outline | Day 01
Data Measuring and Profiling Techniques:
- The importance of measuring Data Quality.
- Data analysis Techniques.
- How profiling can assess Data Quality?
- Typical Outputs of Data Quality Profiling.
Course Outline | Day 02
- Validation Rules of Based Monitoring.
- Data Correction Techniques.
- How to Demystify Data Cleansing?
- Data Modelling.
- Data Flow Diagrams (DFDs).
Course Outline | Day 03
Applying DMBoK Dimensions of Data Quality:
- Data Quality Facets (DMBoK).
- What are the Dimensions of Data Quality?
- Understanding DMBoK Dimensions of Data Quality.
- How to apply Data Quality Dimensions?
Course Outline | Day 04
- Data Quality indicators (DQI) Characteristics.
- What are the link between Governance and Data Quality?
- Understanding Root cause analysis process and the 5-Why Approach: how to apply them for better DQ?
- Defining Financial cost.
Course Outline | Day 05
- How to Create the Data Quality Roadmap
- How to avoid common data quality mistakes?
- Create Data Governance Management Action Plan.
- Workshop.
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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