customer needs for data quality by irene polikoff

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© Copyright 2016 TopQuadrant Inc. Slide Customer Needs for Data Quality Irene Polikoff, CEO Ralph Hodgson, CTO TopQuadrant

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Page 1: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 1

Customer Needs for Data Quality

Irene Polikoff, CEORalph Hodgson, CTO

TopQuadrant

Page 2: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 2

TopBraid Enterprise Solutions Your Enterprise Solutions

Customize/

ConfigureYour Own

Solutions and Platform

IDETopBraid Platform Solution Engine

Search / Content Enrichment through the use of Taxonomies and

Ontologies

Data Governance: Reference Data Management/Metadata

Management/Data Lineage

Data Layer

Page 3: Customer needs for Data quality by Irene Polikoff
Page 4: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 4

What is Data Quality

The five C’s:– Consistency– Completeness– Correctness– Conformance– Comprehensibility

Plus– Precision– Temporality

Page 5: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 5

Examples of where TopQuadrant has met the needs for Data Quality

Consumer Products– Clearance in different markets

Production Reporting– Oil & Gas

Asset Management– V-CON project

Regulatory Compliance– Finance Sector

Page 6: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 6

Common Issues with ‘self created’ RDF Data

Careless URIs e.g., skos:label Incorrect use of predicates e.g, skos:broader

with a text value Missing rdf:type statements Inconsistent literals e.g., text versus integer Mal-formed strings Conflated values Inconsistent Units of Measure

Page 7: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 7

After initial load, data quality is about enforcing “required practices”

Each organization will have its own Common themes are:– Requiring some fields– Capitalizing names– Enforcing certain patterns (what characters are

allowed)– Enforcing “permissible” values– Complex rules with dependencies between fields– Totally “closed world”

Page 8: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 8

Quality-enabling tool support

Form generation based on:– class definition– SHACL constraints

Auto-completion of entries Cardinality enforcement Data types enforcement– SHACL + QUDT

Page 9: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 9

As an example – definition of a class

Page 10: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 10

As an example – resulting ‘instance’ form

Page 11: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 11

In some cases, enforcement is “soft”

Page 12: Customer needs for Data quality by Irene Polikoff

Data Validation happens in real time, but also “after the fact”

For information governed by EDG e.g., reference data, glossary terms, etc.

Page 13: Customer needs for Data quality by Irene Polikoff

It is an ongoing process summarized in dashboards and metrics

Page 14: Customer needs for Data quality by Irene Polikoff

© Copyright 2016 TopQuadrant Inc. Slide 14

We have been transitioning to using SHACL for class definitions and UI customizations

• Users can now create not only classes and properties, but also SHACL constraints

Page 15: Customer needs for Data quality by Irene Polikoff

Ask

Thank You

Ralph HodgsonE-mail: [email protected]: @ralphtq, @topquadrant

Irene PolikoffE-mail: [email protected]