SOLUTIONS
Data Quality Has Become a Strategic Corporate Issue
With a renewed focus on regulatory compliance and corporate governance, data quality has become a strategic corporate issue. More than ever, executives are focusing on the accuracy of the information that they now have to attest to as part of their financial and corporate reporting.
Sarbanes-Oxley is providing motivation for companies to take a more critical look at the accuracy and timeliness of their data. A company’s reporting accuracy is a reflection of the quality of the data, which is driven by the people, processes and technology.
A survey conducted by PricewaterhouseCoopers shows that 75 percent of respondents are experiencing significant impacts as a result of defective data.
What is LoganBritton's Critical Distinction Over
Vendor Driven Solutions?
> Immediate and Tangible Results <
You would not think of running your business without Key Performance Indicators or KPI’s. LoganBritton will enable you to demand that those KPI’s be accurate through measurable and actionable metrics called Key Quality Indicators or KQI’s.
The LoganBritton approach is to offer a scalable and repeatable process for ongoing data quality auditing that results in the delivery of KQI’s in reports or dashboards to notify and inform appropriate individuals about the state of their critical data.
Chances are that right now someone in your organization
is making major business decisions
based on bad data
This could be something as innocuous as producing redundant marketing mailings to existing customers, or can be as severe as making misguided strategic business decisions based on faulty information. The problem seems so obvious. Therefore, why don’t companies have a rigorous process in place to protect their most valuable asset? Because they don't know how.
Many companies are overwhelmed by the subject of Data Quality and the myriad of software tools, multiple options and methodologies. They don’t know where to start. Meanwhile, critical data is becoming more and more unreliable. Traditionally this has been distinctly true of “customer” and “prospect” data, as well as financial data. In some cases today it applies to an even greater extent to supply chain data, in particular to product. Ventana Research recently published a report stating that 80% of the respondents lack confidence in the quality of their product data.
Let LoganBritton help you achieve the results you need to attain true Data Confidence in your customer, prospect, financial, and product data.
Unique Approach to Data Quality Management
LoganBritton offers a critical distinction over most vendor driven solutions, which cater to the strengths of their products, rather than
addressing the data quality issue. This approach is a results-based approach which has three distinct elements:
The LoganBritton Data Quality Audit (DQA) is an engagement designed to provide you with the immediate and tangible results.
This audit is a results-based data quality health check which allows you to define a segment of your critical data for analysis
with guaranteed results. LoganBritton will perform a variety of profiling and data quality analysis against multiple dimensions
of data quality to achieve a comprehensive view of your data. This Data Quality Audit will expose some of your critical data
quality issues. We will then show you the future impact that these discoveries can have on your business.
Not all data quality tools are created equal. As part of the Data Quality Audit, LoganBritton will make very specific recommendations on which tools, technologies or methods should be considered to achieve your specific results. We believe in equipping the right people in your organization with the right tools, empowering them to make informed data quality decisions based on complete and reliable information.
LoganBritton takes a true engineering approach to your Data Quality Management challenges. This solution is architected to address information challenges at the outset, providing a proactive approach to understanding your business data and the resources that directly affect the quality and integrity of your corporate information.
Data Governance
Assist in the creation of a Data Governance Program using LoganBritton’s Data Quality Management Methodology.
This iterative approach is a formal and detailed analysis that involves the business users at all levels.
We will perform intensive and data profiling, discovery and analysis of your critical high-exposure business
data against multiple dimensions of data quality, and will provide impact and exposure analysis reports.
Using the results of the data profiling tasks, we will remediate and report on the success of the identified critical
Data Quality Issues. Regarding tools, we can help you wade through the sea of Data Quality and profiling tools
and assist with tool selection if needed
Maintaining a dynamic Data Quality environment involves creating a monitoring and feedback mechanism for quality analysts, data stewards and corporate compliance officers. LoganBritton provides actionable Data Quality metrics known as Key Quality Indicators or (KQI’s). These are high level indicators in the form of reports and dashboards used to monitor your critical data enabling the implementation of preventative measures.
LoganBritton Data Quality Audit
Rapid data quality health check with actionable results
The Data Quality Audit ™ (DQA) – This audit is a results-based data quality health check which allows you to gain complete insight on a segment of your critical data. This is the quickest and most cost-effective way to begin to develop a Data Quality initiative in your company.
This is a limited consulting engagement providing you with the immediate and tangible results:
- KQI Report - The first deliverable is a comprehensive set of reports which detail the KQI’s. These are measures detailing the accuracy, integrity, consistency, completeness and validity of the selected data segment.
- Audit Assessment - The assessment details the timeliness and accessibility of the data, and uses these results as a predictive measure to project the impact on analysis and provide high-level analysis for the business.
Data Quality Engineering
The LoganBritton Approach
Data Quality Engineering