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Data Quality Testing
at the service
of Open Data
we love data
we love high quality data
us 😊
Data quality testing concept
ODH day 2022
Data quality rules
Data quality rules
validity accuracy
completeness
integrity consistency
timeless
Data quality testing concept
ODH day 2022
Development of codeless data quality testing
2023
Today is the big day
Having a tool is not
sufficient to have
high data quality
Data quality is a
journey made of
analysis, exploration
and goals
Outline of presentation
- The journey behind data quality testing
- CatchSolve and Open Data Hub
The journey behind
data quality testing
Analysis Exploration Goals
3 stages of the journey
Analysis Exploration Goals
3 stages of the journey
Analysis
Dataset and domain
Requirements and
constraints
Risk assessment
Severity
likelihood
Dataset and domain
Requirements and
constraints
Risk assessment
We obtain the information about what to test, why we test it
and the key requirements for choosing how to test it
Analysis Exploration Goals
3 stages of the journey
Exploration
Tools Processes
Analysis Exploration Goals
3 stages of the journey
Goals
Data quality KPIs Meta-KPIs
Improvement
requires
continuous work
CatchSolve and
Open Data Hub
Our core
technology
Customization #1
Open Data Hub
Customization #...
We adapt our core data
testing technology to be
compatible with companies’
requirements and needs
In this way, the
adoption of data quality
testing is eased
Tourism’s dataset example
Mobility’s dataset example
Analysis
Dataset and domain
Requirements and
constraints
Risk assessment
Mobility and Tourism Low number of KPIs
No configuration by
user
Integration Open Data
Hub system
Mobility: sensor might
not send data
Tourism: fields might be
empty or missing
Open and closed data
Mobility: sensor might
send inaccurate data
Exploration
Tools Processes
CatchSolve’s core
technology
Openapi
Who sees the results
and of what
Plan of automation of
the tests
tests configuration
processes
Goals
Data quality KPIs Meta-KPIs
Differentiated by
domain
Data quality KPIs
Tourism
Mobility
validity
completeness
accuracy
timeliness
Empty (null) values
Values = 0
Missing compulsory fields
Not changing sensor values
Old sensor data ( > 1h)
Negative values
Tourism
Mobility
Empty (null) values
Values = 0
Missing compulsory fields
Not changing sensor values
Old sensor data ( > 1h)
Negative values
Don’t fear errors.
Fear not knowing them.
Only by knowing them,
you can improve your data
CatchSolve info@catch-solve.tech
www.catch-solve.tech

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