1. Be Certain, Be Trillium Certain
Creating Your Data Governance Dashboard
Ravi Hulasi – Director of Sales Engineering Solutions
Follow the conversation: #YourDQDashboard
2. 2
Agenda & Overview
What Content Do We Provide To The Dashboard?
Functionality to consider
Business Rules Metadata
Rules Library
Decision Points
Repeat Analysis
Connect the dashboard to the data
Demonstration
Conclusion
3. What Content Do We Provide To The Dashboard?
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Who created this rule?
4. What Content Do We Provide To The Dashboard?
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What is the cost of policies that fail compliance checks?
5. What Content Do We Provide To The Dashboard?
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Do my metrics cover all lines of business?
6. Business Rule Metadata
Aggregate functions can be applied to passing / failing
records of an entity business rule
Full expression can be entered
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9. The Rules Library Is Key
Central store of Entity Business Rules, Attribute
Business Rules and Quality Projects
Allows reuse of rule logic against different schemas
Provides import and export capabilities
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10. The Rules Library Is Key – Points To Consider
Elements in the rules library can be applied in many
places across the platform
Entity / Attribute rules
Transformer
Decision Point
Create attribute business rules for a particular data
element e.g. account number and apply as a standard
Test rules locally before promoting to the library
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11. Decision Points – What Are They?
A batch module that splits the
data based on a user-defined
condition
Splits into passing or failing
records only
Can be chained to create a tree
of tests
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12. Decision Points - Configuration
Enter an expression or choose from the library
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13. Time Series Analysis – What Is It?
A project containing multiple generations of the same
entity
A generation is a fully loaded and profiled entity
Generations inherit the original entity characteristics
Entity Business Rules
Attribute Business Rules
Keys
Dependencies
Generations can be added at a defined interval or on an
ad-hoc basis
Rule results can be gathered across generations to
produce a trend
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15. Time Series Analysis in Quality Projects
Create a Time Series project
that points to the delimited
output of a transformer
process
Allows for separation of batch
Quality and Discovery
processes onto different
servers
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16. Time Series Analysis in Quality Projects
Add an Analysis process to the Quality
project
Time Series project is created
automatically and can be placed at any
step of the process flow
Can be executed in batch, on the same
server
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17. Connect The Dashboard To The Data -
Requirements
Consumption of repository data and metadata by other
applications
Dashboards
Reports
Use industry-standard technologies, avoid landing files
Abstract the Trillium internal architecture
discover –source business_rule –output {name passing_result} –
keypattern {1 0 1}
19. Connect The Dashboard To The Data - What is
OLE DB?
Object Linking and Embedding, Database
Microsoft API for accessing data in a uniform manner
OLE DB Consumer – A software component that requests data
e.g. Excel
OLE DB Provider – A software component that supplies data
20. Connect The Dashboard To The Data - OLE DB
Implementation in TSS
TSS 13.5.1 Client contains an OLE DB Provider
Presentation of a view of data as a table
Tables are defined by TCL scripts
Tables can be passed parameters
show_all_br?type=ebr&eid=1
Supports both Window Authentication and Legacy
security models
License controlled
22. Connect The Dashboard To The Data - Table
Definitions
Business Rules Results Summary
Business Rules Failed Records
Entity Metadata
Attribute Metadata
Attribute Values
Project Metadata
Time Series Metadata
24. Remember
Make use of the Rules Library
Decision Points allow you to split data into separate flows
Time Series allows you to monitor on an ongoing basis
Reporting Adapter allows efficient access to the repository from other
applications
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