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Featured Article
by Kuppusamy Bhaskar
Many organizations start a Data Quality Program solely as an IT initiative without business involvement, and then try to persuade business teams about the value of data quality. For business stakeholders to fully understand the importance and value of data quality, it's essential to get them involved from Day One as champions of the effort.
Follow these seven simple and practical steps to jump-start your Data Quality Program and make it quick, effective and able to meet your business needs. These ideas are from my practical experience of having implemented it at a large financial services company.
Step 1: Understand the business need for data quality
Take a "top down" approach by starting with the business and understanding their current pain points and the value to them of improved data quality. They're the key stakeholders, so it's best they drive the program and be part of the data quality process.
Case Study Lesson: we identified a small team of data stewards that engaged with business stakeholders to understand the issues they were facing due to lack of data quality. Those discussions led to detailed requirements gathering sessions.
Step 2: Define the scope
Take a "start small, finish big" approach. Identify the first set of systems and attributes that have major data quality issues where fixing them will give the best value for the effort.
Case Study Lesson: we identified source systems and data attributes that contributed to the key performance indicators (KPIs) of the business. We prioritized the data elements into low, medium or high in order to be included in the scope for measuring, monitoring and improving data quality.
Keep the scope narrow and yet effective so you can get back to the business with results sooner (days rather than weeks). Address disconnects or refinements early on.
Continue ...
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Greetings!
In this issue, we've got articles by Steve Minor, William McKnight, Kuppusamy Bhaskar, Prashanta Chandramohan, our editor Julie Hunt and myself:
- Hub Designs Sponsors 'Cruise For Life' to Fight Cancer
- Loqate: Accuracy and Intelligence from Address Data, by Julie Hunt
- MDM, SOA and PBM - Partners for Success, by Steve Minor
- IBM InfoSphere Master Data Management, by Dan Power
- Collibra for Data Governance, by William McKnight
- Seven Steps to Data Quality, by Kuppusamy Bhaskar
- Secrets of Successful Data Governance, by Dan Power
- Five Key Factors in Architecting a Master Data Solution,
by Prashanta Chandramohan
- Lean Is Not a Destination, It's a Journey, by Julie Hunt
- Orchestra Networks - EBX5 for Multidomain MDM, by Julie Hunt
Best regards --- Dan Power
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One in three people will face cancer in his or her lifetime, but no one has to face it alone.
On July 28th 2012, the participants in 'Cruise for Life', a one-of-a-kind boating event that raises money for the Jimmy Fund and Dana-Farber Cancer Institute, will help change the odds for patients facing all forms of cancer.
Hub Designs is sponsoring this event as one of our 2012 charities, and if you would like to learn more or make a contribution, please visit http://bit.ly/LjpyT7. Thank you in advance for your generosity!
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by Julie Hunt
It's always great to get a briefing from a very knowledgeable and flexible founder of a young company: tapping into original vision that has been tempered by the experience of customer implementations can be a rich experience. Continue ...
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by Steve Minor
The purpose of this article is to discuss how MDM, SOA and BPM each help strengthen each other.
The author shares some of his recent experience implementing MDM with these technologies. Continue ...
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by Dan Power
Brian Vile, Program Director, MDM Product Management at IBM, and Vasu Vallurupalli, Solutions Lead and Alliances Business Development Exec, sat down with the Hub Designs MDM Think Tank towards the end of 2011 to give us a briefing on changes in IBM's Master Data Management portfolio. Continue ...
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by William McNight
Stan Christiaens, COO at Collibra sat down with the Hub Designs MDM Think Tank in early March to give us a briefing on Collibra's Data Governance Software.
Collibra focuses on the data governance aspects of MDM. It addresses the four main elements of governance - organization, people/processes, documentation and operationalization. Continue ...
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by Prashanta Chandramohan
Over the last few years, Master Data has been recognized as one of the most important types of business information to be managed.
Organizations are heading in the right direction by implementing Master Data Management (MDM) systems to take control of critical data like customers, products, employees, suppliers, materials, etc. Continue ...
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by Julie Hunt
"Lean" and "Agile" concepts have infiltrated aspects of many different kinds of businesses, from managing manufacturing processes to developing software.
While there are several principles that define Lean processes, one of the most important ones is to provide more value more quickly to customers (both internal and external). There now seems to be interest in applying Lean and Agile to data governance, including very specific applications for data integration, MDM and data quality. Continue ...
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by Julie Hunt
Multidomain MDM hit its stride. User interest in multidomain MDM strategies has finally caught up with vendors' product capabilities and messaging. In Forrester's MDM Survey, 47% responded that the scope of their MDM programs include more than two data domains to master, while another 9% are focused on dual-domain solutions (e.g. customer and product).
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