Data Quality and the PPDM Business Rules - EnergyIQ© 2013. EnergyIQ, Inc. All rights reserved....

7061 S. University Blvd Centennial, CO 80122 303-790-0919 www.energyiq.info

© 2013. EnergyIQ, Inc. All rights reserved.

Data Quality and the PPDM Business Rules

Steve Cooper: President


Background

•  The PPDM Business Rules initiative provides a platform for sharing data quality rules

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Background

•  The rules by themselves are only part of the solution •  We need to also establish a consistent process for

applying the rules: –  Identify the most valuable data based upon an

analysis of workflows and decisions –  Apply the dimensions of data quality –  Develop the rules to provide a quantitative

assessment of the quality of the data that we care about

–  Manage and run the rules effectively –  Present the results so that critical trends and

problems can be easily identified

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Background

•  Establishing a consistent process for applying data quality rules is the focus of this presentation

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•  Most companies do not follow an established process


Data Value

•  Data quality initiatives are expensive and can be overwhelming

•  We need to focus resources on delivering the most value to the organization

•  This can be achieved by assigning a value to data based upon an assessment of business needs: –  Workflows –  Processes –  Decisions

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Data Value

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•  Assign a value to data based upon a scale: –  Level 1: Critical –  Level 2: Important –  Level 3: Useful –  Level 4: Supportive


Data Quality Dimensions

•  We need to be clear on what we mean by data quality

•  Typically data quality is defined and measured along a number of different dimensions - Accuracy -  Timeliness - Completeness - Currency - Consistency - Standards

•  We can establish quality requirements for the most valuable data along these dimensions


Data Quality Dimensions

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Data Quality Rules

•  Once the data value and quality matrix has been established it provides the framework for building the rules library

•  The PPDM Business Rules initiative will provide a comprehensive list of quality rules in the form of a definition and supporting information

•  The rules need to be translated into a format that can be executed to return a quantitative assessment of data quality: –  Combine rules –  Target different databases, subsets of a

database –  Process automatically or manually

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Data Quality Rules

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•  Individual rules can be created in standard SQL and stored in the PPDM data model

•  Rules should return a Quality % and list of exceptions: Quality % = 1- Exception Count Population Count


Data Quality Rules

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•  Rule Sets combine individual rules: –  Well Header –  Well Test –  Dates and Elevations …..

•  They can be run against a target subset of the database: –  State or County –  Formation –  Rig Operator …..

•  This combination of Rule, Rule Set, and Target enables sophisticated data quality analysis to be performed: –  Results can be stored in the PPDM database


Data Quality Rules Management

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Data Quality Results

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Data Quality Results

•  Establish acceptable thresholds and ranges •  Set meaningful targets for data vendors •  Assign a value to data in an acquisition •  Begin to treat data as an asset

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Summary

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Business Workflows

Decision Points

Data Requirements

Data Value

Data Quality

QualityRules

Metrics

Business Analysis

Data Analysis (PPDM)

Fix/Audit


Summary

•  The PPDM Business Rules initiative provides a great foundation for any data quality initiative

•  To be successful, however, a consistent and robust process must be adopted for developing and executing data quality rules

•  The process must include an analysis of the needs of the business and the corresponding value of the data

•  We must be able to effectively manage large numbers of rules and how they are executed

•  Data quality visualization is important •  The PPDM data model is a great place to store the

data quality rules, exceptions, and results

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7061 S. University Blvd Centennial, CO 80122 303-790-0919 www.energyiq.info

Steve Cooper Ph.D. Principal EnergyIQ

Questions?

[email protected]


Data Value: Data Objects

•  It is difficult to think about data attributes in isolation •  It makes more sense to think in terms of data

objects about related information: –  Well location –  Depths and elevations –  Directional surveys –  Tests

•  This ties in to the concept of the Common Object Model –  See PPDM Houston conference

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Data Quality and the PPDM Business Rules - EnergyIQ© 2013. EnergyIQ, Inc. All rights reserved....

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Transcript of Data Quality and the PPDM Business Rules - EnergyIQ© 2013. EnergyIQ, Inc. All rights reserved....