Blog by Philip Russom
Research Director for Data Management, TDWI
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NOTE
-- I recently completed a TDWI Best Practices Report titled Next Generation Master Data Management. The goal is to help user organizations understand MDM lifecycle stages so they can better plan and manage them. TDWI will publish the 40-page report in a PDF file on April 2, 2012, and anyone will be able to download it from www.tdwi.org. In the meantime, I’ll provide some “sneak peeks” by blogging excerpts from the report. Here’s the fourth excerpt, which is the ending of the report.]
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Posted by Philip Russom, Ph.D. on March 16, 20120 comments
Blog by Philip Russom
Research Director for Data Management, TDWI
I’ve just completed a TDWI Best Practices Report titled Next Generation Master Data Management. The goal is to help user organizations understand MDM lifecycle stages so they can better plan and manage them. TDWI will publish the 40-page report in a PDF file on April 2, 2012, and anyone will be able to download it from www.tdwi.org. In the meantime, I’ll provide some “sneak peeks” by blogging excerpts from the report. Here’s the third in a series of three excerpts. If you haven’t already, you should read the
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Posted by Philip Russom, Ph.D. on March 2, 20120 comments
Blog by Philip Russom
Research Director for Data Management, TDWI
I’ve just completed a TDWI Best Practices Report titled Next Generation Master Data Management. The goal is to help user organizations understand MDM lifecycle stages so they can better plan and manage them. TDWI will publish the 40-page report in a PDF file on April 2, 2012, and anyone will be able to download it from www.tdwi.org. In the meantime, I’ll provide some “sneak peeks” by blogging excerpts from the report. Here’s the second in a series of three excerpts. If you haven’t already, you should read the
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Posted by Philip Russom, Ph.D. on February 17, 20120 comments
Blog by Philip Russom
Research Director for Data Management, TDWI
I’ve just completed a TDWI Best Practices Report titled Next Generation Master Data Management. The goal is to help user organizations understand MDM lifecycle stages so they can better plan and manage them. TDWI will publish the 40-page report in a PDF file on April 2, 2012, and anyone will be able to download it from www.tdwi.org. In the meantime, I’ll provide some “sneak peeks” by blogging excerpts from the report. Here’s the first in a series of three excerpts.
Defining Master Data Management
To get us all on the same page, let’s start with a basic definition of MDM, then drill into details:
Master data management (MDM) is the practice of defining and maintaining consistent definitions of business entities (e.g., customer or product) and data about them across multiple IT systems and possibly beyond the enterprise to partnering businesses. MDM gets its name from the master and/or reference data through which consensus-driven entity definitions are usually expressed. An MDM solution provides shared and governed access to the uniquely identified entities of master data assets, so those enterprise assets can be applied broadly and consistently across an organization.
That’s a good nutshell definition of what MDM is. However, to explain in detail what MDM does, we need to look at the three core activities of MDM, namely: business goals, collaborative processes, and technical solutions.
Business Goals and MDM
Most organizations have business goals, such as retaining and growing customer accounts, optimizing a supply chain, managing employees, tracking finances accurately, or building and supporting quality products. All these and other data-driven goals are more easily and accurately achieved when supported by master data management. That’s because most business goals focus on a business entity, such as a customer, supplier, employee, financial instrument, or product. Some goals combine two or more entities, as in customer profitability (customers, products, and finances) or product quality (suppliers and products). MDM contributes to these goals by providing processes and solutions for assembling complete, clean, and consistent definitions of these entities and reference data about them. Many business goals span multiple departments, and MDM prepares data about business entities so it can be shared liberally across an enterprise.
Sometimes the business goal is to avoid business problems. As a case in point, consider that one of the most pragmatic applications of MDM is to prevent multiple computer records for a single business entity. For example, multiple departments of a corporation may each have a customer record for the same customer. Similarly, two merging firms end up with multiple records when they have customers in common.
Business problems ensue from redundant customer records. If the records are never synchronized or consolidated, the firm will never understand the complete relationship it has with that customer. Undesirable business outcomes include double billing and unwarranted sales attempts. From the view of a single department, the customer’s commitment seems less than it really is, resulting in inappropriately low discounts or service levels. MDM alleviates these problems by providing collaborative processes and technical solutions that link equivalent records in multiple IT systems, so the redundant records can be synchronized or consolidated. Deduplicating redundant records is a specific use case within a broader business goal of MDM, namely to provide complete and consistent data (especially views of specific business entities) across multiple departments of a larger enterprise, thereby enabling or improving cross-functional business processes.
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ANNOUNCEMENTS
Keep an eye out for part 2 and part 3 in this MDM blog series, coming February 17 and March 2, respectively. I’ll tweet so you know when each blog is posted.
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Posted by Philip Russom, Ph.D. on February 3, 20120 comments
By Philip Russom
Before January runs out, I thought I should tender a few prognostications for 2012. Sorry to be so late with this, but I have a demanding day job. Without further ado, here are a few trends, practices, and changes I feel we can expect in 2012.
Big data will get bigger.
But, then, you knew that. Enough said.
The connection between big data and advanced analytics will get even stronger.
My base assumption is that advanced analytics has become such an important priority for user organizations that it’s influencing most of what we do in business intelligence (BI), data warehousing (DW), and data management (DM). It even influences our attitudes toward big data. After all, the current frenzy – which will become more operationalized than ad hoc in 2012 – is to apply advanced analytic techniques to big data. In other words, don’t do one without the other, if you’re a BI professional.
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Posted by Philip Russom, Ph.D. on January 23, 20120 comments
Happy New Year to everyone in the TDWI community! I wish you an enjoyable and prosperous year. Squinting down the path ahead, it is indeed going to be a busy year at TDWI as we roll out our World Conferences, Summits, Forums, Seminars, Webinars, Best Practices Reports, Checklists, and more. The next World Conference is coming up February 12-17, in Las Vegas. This event is always one of the major gatherings of the year in business intelligence and data warehousing, and I am looking forward to being there and interacting with attendees, exhibitors, TDWI faculty, and a few croupiers here and there.
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Posted by David Stodder on January 5, 20120 comments