Creating Your Data Governance Dashboard
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Transcript of Creating Your Data Governance Dashboard
Be Certain, Be Trillium Certain
Creating Your Data Governance Dashboard
Ravi Hulasi – Director of Sales Engineering Solutions
Follow the conversation: #YourDQDashboard
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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
What Content Do We Provide To The Dashboard?
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� Who created this rule?
What Content Do We Provide To The Dashboard?
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� What is the cost of policies that fail compliance checks?
What Content Do We Provide To The Dashboard?
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� Do my metrics cover all lines of business?
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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Business Rule Metadata
� Rule Creation / Edit metadata captured for every rule
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Business Rule Metadata
� V14 – Addition of rule categories and sub-categories
� Insert screenshot here
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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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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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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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Decision Points - Configuration
� Enter an expression or choose from the library
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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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Time Series Analysis
� Results Are Summarised Across Generations
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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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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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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}
Connect The Dashboard To The Data - Example
Output
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
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
Connect The Dashboard To The Data - Trillium
OLE DB Architecture
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
Demonstration Of Functionality
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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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Be Certain, Be Trillium Certain
Q&A