Salah Kamel, a Founder of Semarchy says, “I was born and raised in data.” Kamel has been an innovator throughout his career and was awarded the 2016 DAMA International Excellence in Data Management Award. The annual award recognizes organizations or individuals who have made significant contributions to Data Management principles. His latest contribution is the xDM platform, an innovation in multi-vector Master Data Management (MDM) that leverages smart algorithms and material design to simplify Data Stewardship, Data Governance, and Data Integration. It is implemented via an agile and iterative approach that delivers business value almost immediately, and scales to meet enterprise complexity.
In an interview with DATAVERSITY, Kamel discussed xDM and how it works within the enterprise. Owing to the algebraic concept that “x” can be anything, xDM is unique in its breadth of ability to master any kind of data – Reference Data, Metadata, location, product, supplier, and others. Kamel describes what he calls “the three pillars” of the xDM program:
“There are so many smart algorithms that we can leverage on a daily basis to help the business users, and to help the Data Stewards, and to help the data champions leverage their data. By introducing those algorithms into the mix, we’re getting into a better value proposition. We’re closer to AI. We’re getting too smart algorithms for data classifications, for Data Modeling, for prioritizing the work queues of Data Stewards.”
This is what he calls the smart pillar of the program. Historically, Master Data Management has been a lot of hard, manual work, which is time-consuming, he said. “All these tasks within the product right now are fully automated, and they can grow and evolve and learn from whatever data you give them so they can empower the data consumers” and turn them into data producers. “That’s exactly what intelligent MDM is about,” he said. “The second pillar is agility, agility, agility.” He said it’s important for companies to be continually evolving:
“Getting Data Governance right the first time doesn’t make any sense, and getting MDM right the first time doesn’t mean anything, because it’s a journey. A week later things might change, and that’s why you need a set of products or a set of initiatives that are agile enough to cope with very fast sprints – within a couple of weeks – to get things delivered and delivered in production.”
Kamel considers the third pillar the most important – the ability to measure. “Measurable means you need to be able to derive metrics and derive tangible outcomes out of your initiatives that translate into a return on investment. If you don’t measure it, chances are your MDM initiative is failing.” When a program is smart, agile, and measurable, “You get what we call Intelligent MDM.”
Responsive Design Language Adds Portability
Similar to what other companies do when they create a mobile app from a desktop app, Semarchy has created a smaller, smart device-sized version so that features of the desktop app can be used in the field.
“The first thing that xDM brings to the picture is material design.” Material design is the language Google created for smart applications used on phones and tablets. This language provides responsiveness that allows users to access the desktop and mobile versions seamlessly, he said. “There’s not a single MDM application today on the market that can get into the pockets of business users” and provide a way to take action on that data in the field. With xDM, business users can manage tasks, engage with workflows, collaborate with peers, query data, and find value in their data, he said.
“I’m looking on the dashboard on my phone, and I figure out that there’s a number there that is wrong, and I know that by clicking on this dashboard, I can launch my MDM application and correct it on the fly,” and…”At the end of the day, what I’ve done is that I’ve transformed myself from being a consumer business user to an active guy, sitting in the middle of the enterprise and contributing to better Data Quality.”
SemQL Provides AI Capabilities
Another feature of xDM is called “SemQL,” he said, which is based on their Semantic Query Language. “In a typical Big Data world, you’ll try to get numbers about the revenues, or the behaviors, or the risk,” a process that uses AI based on numbers, he said. “The AI that you might want in an MDM is AI that’s based on the semantics of the data that you’re manipulating.” SemQL can show the relationships between objects, “Using natural language that is geared toward business users,” he said.
The AI is baked into the foundation of the application, allowing users to say, “I’m looking at this product. Show me everything you know about this product and its neighbors, up to five degrees of relationships,” he said. This gives business users the ability to clearly understand relationships and find opportunities that were not visible before, he said. “Because you were looking at your data in a flat list. Mining relationships from a flat list doesn’t make sense.”
Advanced Application Customization
Another facet of xDM is advanced application customization, which includes dynamic, context-aware forms and fields. “I’m entering a product. I’m going to spell it in a certain way. I’m going to start with the brand name and probably add some information about its dimensions, and say that it’s jeans.” The process of entering product info in certain fields will trigger a series of acceptable word choices for the rest of the form, he said, creating the opportunity, “To mine the data and get this information from the users as early as possible, derive it, and enrich it, and make it available later on.”
Guided Data Authoring
By using chatbots, a company can take customization a step further and achieve an even greater level of efficiency. “This is what we call ‘guided data authoring’ of the application, where you have a chatbot behind the scene correcting you and gathering information from you to be able to create and author and maintain and master this core data of the enterprise.”
He used an example of a new employee charged with creating a new product using Slack chat as a guide:
“They type in ‘create product’ and the bot answers, ‘What type of product would you like to create?’ If the answer is ‘I don’t know,’ it says, ‘Here is a list of some product types. Which one would you like to try?’” Kamel said. “Besides helping with the creation of product, the process of working with the bot ensures quality Master Data from the start. The chatbot becomes your Data Steward.”
Kamel sees Semarchy’s unique value proposition as the combination of being smart, agile, and measurable, all within the same product, brought to business users, using language that they use every day, and offering the option of mobile access, he said. “We feel that this is a pretty good set of unique features that we’re bringing to the market.” Having these tools in one place has made it easier for Semarchy’s customers to be up and running in less time. He said that 80 percent of their customers are in production in fewer than ten weeks:
“For a Master Data Management application, being in production in less than ten weeks – and that’s huge. In less than three months, you’re done, it’s in production, and your users can really start being empowered and getting the value out of the product.”
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This article originally appeared in Dataversity*