Master Data Directions: Q&A with Siperian's Ravi Shankar
The Master Data Management (MDM) market is growing at a double-digit pace on the strength of three promised benefits: a cross-enterprise perspective for better business intelligence; greater consistency across customer records for improved transaction management; a solid foundation for service-oriented architectures (SOA). Has MDM turned the corner from leading-edge to must-have? Ravi Shankar, Director of Product Marketing at Siperian, shares his thoughts on MDM progress and next steps.
Has MDM gone mainstream? Do people “get it?”
There is huge awareness of MDM. Gartner recently hosted a MDM conference for the first time [piggy-backing on its CRM conference], and they pulled in about 500 attendees.
As to whether they “get it,” it depends on who you're talking to. Most of the IT people get it. Business users understand the moniker, but they might or might not understand MDM quite as well. I find that business users often require education in terms of what it can do for them and what value it brings. With IT people, it’s a different conversation; they want to know more about the features and how we differentiate ourselves from the competition.
Are you seeing awareness translate into bigger budgets for MDM?
It's a matter of awareness and the problem becoming urgent. We are seeing budgets increased and greater success in closing deals, particularly in the pharmaceutical and financial services industries.
Forrester predicts MDM will be $6 billion market by 2010, which is a 60-percent growth rate over the $1 billion MDM market last year. Gartner forecasts that 70 percent of Global 2000 companies will have a MDM solution by the year 2010. These are pretty big numbers.
What are the biggest technical and management challenges in adopting MDM?
Technical folks often have a challenge in data governance in selling the project and getting the funding. Management is looking for return on investment; they need MDM tied to quantifiable benefits that business leaders understand, like dollar amounts around ROI.
What are the typical ROI drivers?
On the revenue side it's improvements in the business process. For example, financial services can use MDM to improve Basel II compliance and reduce capital allocation. IT typically sees reductions in duplicated technology costs.
Lots of people talk about “data governance,” but how do you define it and how can organizations move toward governance without being overwhelmed?
Siperian calls it "Master Data Governance," and we define it as "the orchestration of people, policies, procedures and technology to manage enterprise data availability, usability, integrity and security for business process efficiency and compliance.”
Master Data Governance is complex. If you don’t do it right, the project may fail. You don’t want to put data governance on all your data; that's too expensive. You want to put governance only on data that leads to business process efficiency and compliance.
You have to go through a design phase to come up with a data governance framework that's independent of technology. Once that's done you need a flexible technology platform to enable the governance framework.
Is the debate on centralized v/s federated MDM behind us? Who won and which approach does Siperian follow?
It's not a question of who won and who lost. Gartner defines four different architectural styles for MDM: Consolidation, Registry, Coexistence and Transaction. They are all valid depending on the client circumstances. The different styles define a maturity model, and it is important that you are able to evolve your MDM solution along the maturity path. Siperian supports all four models.
Is there a future for SaaS-based MDM?
There are a couple of ways to answer that question. I don't think MDM is a place to do SaaS as in the salesforce.com model, where you are using the MDM hub to provide services coupled with applications. But there are other situations where MDM can be offered as a hosted technology. We have customers doing this, but it's not widely implemented because of the complexity in terms of the number of data sources that you can hook to the system. If you don’t have many data sources and there's little in-house IT infrastructure, you may consider outsourcing the hosting of the MDM solution. In cases where there are many data sources and strong in-house IT, we see customers preferring to keep the MDM implementation in-house.
What’s next for MDM in terms of capabilities?
In our view, the next evolution for MDM will be along the lines of Master Data Solutions specific for verticals — for example, to manage risk in financial services, to support new product introductions in retail, and to manage physician spend in the pharmaceutical industry.
In terms of specific capabilities, supporting custom application development and enterprise SOA will be the next big drivers for MDM. Composite applications cannot be cost-effectively developed without first integrating disparate data across different applications and legacy systems.
There will be other developments as well. In the area of metadata management, you'll see integration with enterprise metadata managers. In reporting and metrics, you'll see pre-defined and user-defined data capture and metrics generation, integration with major reporting/BI tools as well as prepackaged dashboards and reports to monitor data quality and data steward productivity. Finally in the area of business process management, you'll see native management of data state within any workflow tool of choice. You'll also see integrated management of reusable business rules for needs including cleansing, matching, survivorship and workflows.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.