MDM is a journey, not a project

Fellow Roundtable writer David Loshin has commented in the past that: "MDM is popular because it is presented as a cure-all solution to all data problems in the organization."

521811631Many people see master data management (MDM) as the silver bullet to all of their business and data woes. But in reality, MDM is a journey – not a project. You need to phase your MDM journey and be clear on what business objectives you'll be able to influence versus that fall outside of your scope for each step of the journey. The business also needs to aware of its responsibilities.

How will MDM change (and improve) working practices? What will a single view of equipment, customers, locations and other domains mean for the business model?

In this post, I want to outline a few steps you can take to help you get started on the journey. Feel free to add your experiences in the comments section below. Read More »

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Examining the relationship between MDM and customer intelligence

women in restaurant, customer intelligence and MDMClaire runs a local restaurant with $500,000 in annual sales. She is thinking about revising the menu. To this end, she wants to learn more about her customer base. Specific questions include:

  • Which items should she axe?
  • Which should she add?
  • Are the current prices optimal?
  • Are "loss-leading" happy-hour specials worth it?

To answer these questions, does she need to purchase and deploy a proper master data management (MDM) application to do so?

It's doubtful. Odds are that this kind of solution is overkill for her small, single-location restaurant. Read More »

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MDM intersections, Part 2: Data governance

woman at computer doing data governanceMaster data management (MDM) is distinct from other data management disciplines due to its primary focus on giving the enterprise a single view of the master data that represents key business entities, such as parties, products, locations and assets. MDM achieves this by standardizing, matching and consolidating common data elements across traditional and big data sources. In turn, it's possible to develop and maintain a consistent definition and best representation of these business entities – and share their master data – across IT systems and business units.

In this two-part series, I'm examining the intersections between MDM and other data management disciplines. Part 1 discussed data quality. Part 2 concludes the series with a focus on data governance.

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The next wave of MDM: Integrating structured and unstructured data

In a recent post, I examined the relationship between big data and traditional MDM. Long story short: there really hasn't been a strong one. Before addressing the issue of whether and when that will change, let's look at some data.

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MDM intersections, Part 1: Data quality

Master data management (MDM) is distinct from other data management disciplines due to its primary focus on giving the enterprise a single view of the master data that represents key business entities, such as parties, products, locations and assets. MDM achieves this by standardizing, matching and consolidating common data elements across traditional and big data sources. In turn, it's possible to develop and maintain a consistent definition and best representation of these business entities – and share their master data – across IT systems and business units.

In this two-part series, I'll examine the intersections between MDM and other data management disciplines, starting with data quality.

How MDM intersects with data quality

crystal ball against mountains repesents data quality and MDMData quality intersects with MDM in many ways. Data profiling is used to evaluate sources for master data entities, including the performance of a baseline assessment of potential data quality issues that must be addressed. Postal validation and address verification is essential for location master data. And since most master data originates in free-form text fields (e.g., customer name, product description), the composite data elements (e.g., given name, family name, unit of measure, packaging type) must be parsed and standardized.

However, the biggest intersection between MDM and data quality is with the matching and survivorship processes used to create the best master data record to represent the single view of the business entities at the heart of MDM. These data quality rules must be customizable and supported by an interface that enables business users to interactively review, approve and document how the single view is constructed. The interface also needs to provide both metadata lineage and data linkage back to the originating master data source systems.

How has data quality intersected with your MDM?

Please share your perspective and experience regarding the intersection of MDM and data quality by posting a comment below.


Download an e-book about the intersection of big data, data governance and MDM.

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In search of the Holy Grail: Sorry Hadoop fans, only MDM delivers single view of customer

Single view of customer. It's a noble goal, not unlike the search for the Holy Grail – fraught with peril as you progress down the path of your data journey. If you're a hotelier, it can improve your customer's experience by providing the information from the casinos and the spa at check-in to better meet your customer's needs. If you're sending out marketing fliers, it can reduce mailing costs by providing a clean list of customer addresses. If you're a retailer, and a customer buys that Monty Python and the Holy Grail DVD, it can increase revenue by recommending additional related products like a "None Shall Pass" t-shirt. And, if you are a federal or state agency, it can help you meet compliance or regulatory requirements for reporting.

Master data management (MDM) solutions, like SAS MDM, are designed to provide that single, consistent view of the customer across multiple sources of data. But with many other technologies claiming the ability to provide a single view, is MDM still the best approach available today?

master data management provides the single view of customer

Master data management provides a single, consistent view of the customer.

I first learned about MDM about nine years ago while interviewing for a job with a Big 6 enterprise software firm. My old drummer was a hiring manager, and he thought I’d be a good fit for a spot on his team as a sales engineer. (See mom, jamming on that guitar for years did pay off.) Wikipedia was my best friend as I ramped up quickly on terms like MDM, customer data integration (CDI), product information management (PIM) and enterprise service hub (ESB). Amazingly, some combination of my computer engineering degree, my buddy and my enthusiasm got me the job.

I spent the next six years becoming an expert in the MDM space. In this world, “single view of the truth,” survivorship rules, and the differences between systems of record and sources of record were often religiously debated. Along the way, I converted a lot of CSV files into XML to load into the MDM hub, and I even wrote a few tools in VB.Net to do so. Read More »

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Shifting ownership to the source – The future of MDM?

woman using social media on cell phoneMost companies are battling with master data challenges whether they realise it or not.

When you're consolidating financials from multiple billing systems, you're doing MDM. When you're migrating legacy systems to a new target environment, you're doing MDM. When you're trying to perform root-cause analysis across multiple systems for a customer complaint, you're doing MDM.

We may be linking master data visually or removing duplicates in a one-off operation – but fundamentally, it's still managing master data in some fashion.

Of course, the impact of poorly managed master data is keenly felt by customers and service providers alike. Read More »

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Does MDM need to be part of your data strategy?

woman contemplating MDMA while back, I ran a four-part series on this site about the notion of a formal data strategy. (Read the first installment here.) TLDR: Adopting one certainly can't hurt, but I'm not a fan because the intelligent use of data should be part and parcel to every organization's business strategy.

Today I'll discuss what place – if any – master data management (MDM) plays in such a strategy.

A tale of two organizations

Allow me to channel my inner Dickens. Consider two large, mature, international organizations with complicated systems, interfaces and data warehouses. This is where the similarities end. Organization A manages its data exceptionally well. Data quality is extremely high and it has imbued a strong culture of data governance. Throughout the organization, employees understand the importance of data. Read More »

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Dovetail process flow and master data management

man working with data outside at nightIn my last post, I discussed the issue of temporal inconsistency for master data, when the records in the master repository are inconsistent with the source systems as a result of a time-based absence of synchronization. Periodic master data updates that pull data from systems without considering alignment with in-process business activities create the potential for this inconsistency. The way to address this is straightforward: don’t do your master data consolidation as a periodic process. Instead, push your identity resolution and master data management (MDM) into your business processes.

That is, of course, easier said that done. It typically requires two key activities that are not insignificant:

  • Align all enterprise process flows and all related master data touch points with the master record life cycle.
  • Renovate existing systems to use defined master data services as a way to manage entity data.

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Streaming data analytics: A better way to fight fraud and cybercrime

confident woman fighting fraud and cybercrime with streaming dataThe numbers are daunting.

  • More than 40 million Americans have their identities stolen each year.
  • Credit card companies lose more than $200 billion annually due to fraud.
  • Cybercrime-related losses exceed $3 million per claim for large companies.

If you’re like me, those stats are enough to give pause. To fuel the concern, 24/7 news channels often focus on technology as the culprit that enables modern day fraud and crime. It leaves some to reason that each new technological advance might not be something to cheer. Yet while technology for wrong gets the headlines, we rarely hear about the things proactive companies are doing with technology to protect us.

The banks we do business with, the retailers where we shop and the credit card companies that finance many of our purchases are all working behind the scenes to cut or eliminate those daunting numbers. They do it for the benefit of their organizations – and for us, their customers.

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