The Data Profiling module explains what data profiling is and why it is useful.
The typical key outputs from data profiling are explained such as;
- Frequency distribution
- Max and min values
- Length analysis etc.
Learn what data profiling is.
Learn the most common outputs from data profiling:
- Frequency Distribution
- Minimum and Maximum value analysis is.
- Length analysis
- Data Type Analysis
- Format analysis
- Uniqueness Analysis
- Completeness Analysis
Who is Suitable?
No prior knowledge is required so all Data Practitioners can undertake the course.
As this is a data assessment and control module the content is especially useful for data profilers and data analysts but would also be a useful for a wide spectrum of data roles; including but not exclusive to data owners, data modellers, data architects and data lineage analysts.
- What is data profiling?
- Why would an organisation undertake data profiling?
- What are some typical outputs from data profiling?
- How can data profiling help to identify primary keys?
- What is the difference between data profiling and data quality rules?
- Can you explain high and low cardinality?
- Why is it useful to split data quality into dimensions?
- Does the presentation of data differ between data analysis and data profiling?
- What are outliers?
- What is meant by data that is not fit for purpose?
An Interactive Presentation
10+ Interactive Questions
3 Final Practice Tests – 30 questions over 30 minutes
Final Examination – 60 questions over 30 minutes