Root Cause Analysis
The Root Cause Analysis module discusses the investigation of the causes of identified data quality issues through a range of complementary techniques; this includes the process of documenting and agreeing the size and scope of the problem, ascertaining the business areas responsible for the fix and the areas requiring fixes.
Learn what Root Cause Analysis (RCA) is.
Learn why Root Cause Analysis (RCA) should be undertaken.
Learn the sequential steps of a Root Cause Analysis (RCA) process;
- The Charter Document
- The Problem Statement
- The RCA Investigation
- The Solution Design
- The Business Case
Who is Suitable?
No prior knowledge is required so all Data Practitioners can undertake the course.
As this is a data improvement and maintenance module the content is especially useful for data analysts and business analysts but would also be a useful for a wide spectrum of data roles; including but not exclusive to data owners, data stewards, data modellers, data architects and data lineage analysts.
- What does a prioritisation process of DQ issues look like?
- What are manual adjustments?
- Why are firms increasingly realising the need to treat customers fairly?
- What is a waterfall project approach?
- What are dependencies?
- Why is it important to agree on the size and scope of a problem?
- Why is remediating dq issues by simply changing the data not the best option for a firm?
- Is RCA always more cost effective than data scrubbing?
- Who is the stakeholder community?
- Could you explain RCA?
- How are solution design and RCA related?
An Interactive Presentation
10+ Interactive Questions
3 Final Practice Tests – 30 questions over 30 minutes
Final Examination – 60 questions over 30 minutes