There are some fields and industries that sound pretty lame, and others that just sound cool — Master Data Management is one of those that sounds pretty interesting. But what does a career in Master Data Management mean, and what will a job in that field require?
What is Master Data Management?
According to Gartner, Master data management (MDM) is “a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts.”
In short, Master Data Management (MDM) can be viewed as a discipline for specialized quality improvement defined by the policies and procedures put in place by a firm to provide the end user community with a trusted single version of the truth from which to base decisions.
According to Informatica, a data management firm, MDM involves a number of technology solutions (data integration, data quality, and business process management) in order to give businesses:
- A single view of the data: Creating a single, authoritative view of business-critical data from disparate, duplicate, and conflicting information.
- A 360-degree view of the relationships: Business rules let you identify the relationships among the data.
- A complete view of all interactions: Integrating the transactions and social interactions that have occurred with that product, customer, channel partner, or other data element gives you a complete view of a customer.
Master Data Management and Big Data
So how is MDM different than another business buzzword in Big Data? According to Dataversity, some of differences between Master Data and Big Data include:
- Volume: Comparatively, Master Data sets are much smaller than those for Big Data. One of the pivotal attractions for Big Data is that it encompasses enormous volumes; a person could argue that one of the points of attraction for Master Data is the opposite.
- Structure: Master Data tends to contain structured data, while the majority of Big Data is either unstructured or semi-structured.
- Relationship to the enterprise: Typically, MDM systems contain an organization’s most trusted data, which tends to be internal, while Big Data platforms quarter enormous amounts of external data from any number of cloud, social media, mobile, and other sources beyond the enterprise’s firewall.
Despite these differences, Big Data and MDM seem destined for a future together and there are ways in which Master Data Management can enhance Big Data applications, and vice-versa. In her article “Enterprise Master Data Management and Big Data: A Well-Matched Pair?”, Beth Stackpole of Tech Target writes:
At first blush, the two seem like a mismatched pair. Big data environments typically encompass large volumes of text and other forms of unstructured data from a variety of sources, such as social networks, Web server logs and sensors. Enterprise master data management (MDM) initiatives are meant to create a trusted source of highly structured transaction data throughout an organization.
But even with that apparent disconnect, data management analysts see a prospective link, with MDM processes having a role to play in aggregating useful information from pools of big data and then matching it against the master data in a company’s transaction systems.
Just as business leaders and executives are finding more ways that Big Data and MDM can work as a “well-matched pair”, graduate students are realizing that an MBA degree and a career in MDM are also a match made in data-heaven.
Master Data Management and the MBA
If you’re in the tech industry and want to break into business, an MBA can help you to stop thinking like an IT person and start thinking like a businessperson with an IT focus. With both skill sets, analyzing Master Data for a company could be a lucrative position.
According to US News & World Report, by 2018, the United State will face a shortage of as many as 190,000 people with the requisite analytical skills, in addition to hundreds of thousands of managers and analysts who understand both business operations and how to draw decision-driving insights from vast amounts of data.
MBA graduates with this type of know-how can pursue jobs in a number of emerging tech industries as companies want business graduate students with computer credentials to protect their digital assets. The Bureau of Labor Statistics puts median pay for information security analysts at $86,000 in 2012; job growth should hit 37 percent in the decade ending in 2022.
Translation: There’s a world of opportunity in data analytics and MDM.
What types of jobs are out there right now? A quick search on Indeed for Master Data Management yields the following results:
- DM Senior Programming Analyst: “We are looking for a talented Master Data Management (MDM) individual who will be responsible for delivery of the overall enterprise Customer Information Management (CIM) solution experience at ADC. This individual will lead the technical aspects of the delivery of CIM solutions & related components The individual will drive master data schema development, access business rules, and master Customer data design and migration processes for a CIM implementation. The candidate will be responsible for developing functional specs for business rules and workflow processes in addition to implementing configuration-setting changes.”
- Analyst Master Data Management: “This position is both technical and business focused with regard to Enterprise Master Data management and is responsible for providing support in designing, implementing and ongoing management of master data governance processes. This position will analyze master data across multiple systems, and monitor and ensure data integrity and data quality.”
- Master Data Management Functional Lead: “Experience in implementing business processes and governance models including specialized experience in developing and implementing Data Quality Management practices and tools and configuring Master Data Management software to meet requirements. Must be capable of gathering requirements, facilitating design of solution, documenting current and future state, writing functional specifications, performing configuration management, interpreting software test results, and troubleshooting and resolving functional issues.”