1.What is MDM?
Master data management (MDM) is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.
2.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.
3.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. For rester predicts MDM will be a $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.
4.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.
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5.What is Data Warehousing?
A data warehouse is the main repository of an organization’s historical data, its corporate memory. It contains the raw material for management’s decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. Data warehousing collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. It is a repository of integrated information, available for queries and analysis.
6.What are fundamental stages of Data Warehousing?
Offline Operational Databases: Data warehouses in this initial stage are developed by simply copying the database of an operational system to an off-line server where the processing load of reporting does not impact on the operational system’s performance.
Offline Data Warehouse: Data warehouses in this stage of evolution are updated on a regular time cycle (usually daily, weekly or monthly) from the operational systems and the data is stored in an integrated reporting-oriented data structure.
Real Time Data Warehouse: Data warehouses at this stage are updated on a transaction or event basis, every time an operational system performs a transaction (e.g. an order or a delivery or a booking etc.)
Integrated Data Warehouse: Data warehouses at this stage are used to generate activity or transactions that are passed back into the operational systems for use in the daily activity of the organization.