Manage and Maintain Data Quality
You’ve gotta plug the holes before you can bail the boat!
RETIRED CONTENT
Please note that the content on this page is retired. This content is not maintained and may contain information or links that are out of date.Organizations with poor data quality find themselves dealing with one or more of the following data quality problems:
- Time is being wasted reconciling data quality issues: data is either out-of-date, different across multiple systems, absent, or any number of quality issues.
- The business is unable to back their decisions with concrete data, which is impacting their bottom line.
- The reputation of the enterprise is being eroded because of miscommunications with customers and suppliers as a result of bad data.
- Clean-up efforts are costly, and seem to yield no results, as the data continues to be plagued with defects.
With standardized data quality management practices and regular clean-ups of data systems, your organization will realize the following benefits:
- Quicker and more accurate business reports that are not conflicting and help to aid decision making.
- Concrete data to back business decisions.
- Strong customer/supplier relationships as there is little miscommunication or confusion around relevant data.
- We are saving time and money by catching and clearing up data as it enters our system, before it has a chance to impact our business.
Book Your Workshop
Onsite Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn’t enough, we offer low-cost onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
Module 1: Scope the Project
The Purpose
- Introduce Workshop
- Understand how bad data impacts your organization
- Scope the project
Key Benefits Achieved
- Understanding of poor data quality impacts
- Pilot implementation selected
- Stakeholders, metrics, and pilot project now identified
| Activities: | Outputs: | |
|---|---|---|
| 1.1 | Cost of Poor Data Calculator |
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| 1.2 | Selection of Pilot implementation |
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| 1.3 | Identification of Stakeholders |
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| 1.4 | Definition of Goals and Objectives |
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| 1.5 | Definition of key metrics |
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Module 2: Data Audit
The Purpose
- To assess the state of your data systems and determine issues.
Key Benefits Achieved
- Understanding of the issues with your data systems and the extent of your data quality problems
| Activities: | Outputs: | |
|---|---|---|
| 2.1 | Select an auditor |
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| 2.2 | Identify your data sources |
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| 2.3 | Identify critical areas of data quality issues |
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Module 3: Optimize Process
The Purpose
- Identification of Root Causes of Data Issues
- Identify immediate remedies
- Determine governance structure
- Identify people, process, technology and data that can applied to plug the holes
- Establish Baseline metrics
Key Benefits Achieved
- Understanding of your data quality issues and what processes to put in place to “plug these holes”
| Activities: | Outputs: | |
|---|---|---|
| 3.1 | Identify root causes |
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| 3.2 | Look for immediate opportunities to plug the holes |
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| 3.3 | Identify a governance structure |
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| 3.4 | Identify people, process, technology and data that can applied to plug the holes |
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| 3.5 | Establish metric baselines |
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Module 4: Clean & Correct Data Systems
The Purpose
- To create a plan to clean your data systems
- To identify people, process, technology and data that can be used to bail the boat
- Create an implementation plan
Key Benefits Achieved
- An understanding of how to clean your data systems and what technology solutions are available to help
| Activities: | Outputs: | |
|---|---|---|
| 4.1 | Create a plan for bailing the boat |
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| 4.2 | Identify people, process, technology and data that can be used to bail the boat |
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| 4.3 | Implement process changes |
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