Data Quality, Health Check & Accelerators

Data Quality Management

Data Quality Management is a fundamental and on-going process, which benefits every business area, and helps to ensure that business information is reliable, complete, consistent, current and correctly interpreted.

Solutions: The Cost of Poor Data Quality

How InfoBluePrint Can Help

InfoBluePrint supplies a range of proven services to help companies achieve business value through effective Data Quality Management. These can be implemented as individual projects or provided as a holistic Data Quality Improvement Solution designed to address all aspects of Data Quality (DQ):

Data Quality
Assessments/
Health Checks

Discover the current baseline state of data quality
Perform data profiling & identify specific data errors
Measure compliance of data against well-defined business and data rules
Quantify the extent of inaccurate, non-standardised, duplicate or missing data

Design of
Customised DQ
Improvement
Approach

Perform root cause analysis
Identify and design corrective & preventive interventions required
Define programmatic and manual data cleansing solutions
Design processes and solutions to action activities
Create dashboards to communicate ongoing data quality status

Implement
Data Quality
Improvement
Actions

Implement data correction solutions
Perform programmatic and manual data cleansing supported by audit trails
Record match, merge, link or deduplicate
Build single-view of customer, product, materials, etc
Data enhancement and enrichment using internal and/or external data sources
Implement preventive measures
Address root cause issues
Formulate data governance requirements

Monitoring
of Data Quality

Establish data quality assurance mechanisms
Implement production class monitoring and control solution
Implement data governance and data stewardship functions
Create ongoing processes to maintain the desired data quality targets

Data Quality Health Check

At InfoBluePrint we know that your data is your most important asset. Many businesses have found, to their detriment, that projects and services cannot be effectively delivered using unreliable data. Together with the extra pressures of ever-increasing compliance requirements, the need to boost revenues and to minimise costs, this drives the imperative to improve data quality even higher on the list of business priorities.

The InfoBluePrint Data Quality Health Check is built on a proven methodology and accompanied by a set of supporting tools that are very quick to implement, that provides a rapid and objective assessment of your existing data quality issues, straight out of the box. This service can be used stand alone or as an integrated part of projects supporting and enabling Marketing & Sales, Digital Strategies, Data Governance, Customer Centricity, Regulatory Compliance, Business Intelligence, Big Data and Analytics, System and Data Integration and Data Migrations.

A set of proven business & data quality rules to immediately get you up and running

A full suite of summary of dashboards, summary & detailed reports to monitor data quality

A toolkit for rapid implementation

Reliable reference data to rate your compliance with industry standards

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Master Data Quality Accelerators

Backed by the InfoBluePrint Data Quality Management Methodology, we have developed specifications, rules libraries, a regular expressions library, solution architecture, data models and reference data for South African party data (e.g. customer, supplier, counterparty, intermediary and employee) that can be leveraged to
fast track your data quality project, both architecturally and programmatically.

This solution has several benefits:

Realise the value and ROI of a data quality software technology purchase much faster
Avoid time-consuming and costly trial and error development that is inherent to data quality assessment and data cleansing activity
Immediate access to tried and tested reference data gathered over many years, specifically in the SA context
Comprehensive libraries of proven business and data rules and regular expressions (regexes) for data validation & correction
Consistent and reliable results
Common data models for any data source and any data structure, resulting in re-use and benefit from the same data quality assessment and cleansing code
Audited programmatic data cleansing – detailed visibility of what was cleansed and why
Modular design for complete customisation and easy maintenance