Peter Vogel: What market is CA ERwin Data Modeler part of? What are the essential issues/characteristics in this market?
Donna Burbank: Data modeling is a core component in a number of markets that manage or use data including Data Integration, Business Intelligence (BI), Data Warehousing, Master Data Management (MDM), and Data Governance. Data modeling provides a blueprint for data assets that can be used by both the business and technical staff to define and modify data structures. For example, business analysts use CA ERwin Data Modeler (CA ERwin) to define core business requirements, which are then integrated with the technical architecture at the database design level.
Challenges with data management include ensuring that all data is of the same high quality, maintaining data integrity and standardizing data fields across different data sources. Companies that understand their customer, product, and competitive data have a distinct advantage. Data Modeling helps organizations maintain a clear, consistent view of their strategic information -- helping them understand the data they have, what it means, and the relationships between data elements.
PV: What challenges do you see in CA ERwin Data Modeler's future?
DB: The major challenge is to keep up with new data formats and on-demand/cloud platforms. Where much of an organization's data was historically stored on-premise in traditional relational databases (RDBMS), today there are new platforms and data formats to deal with: unstructured data in emails and documents; XML and related formats for Web development; cloud-oriented databases; and so forth. CA ERwin's challenge is to provide the same level of data management and model-driven development options for these new data sources as we historically have for the traditional database market.
Posted by Peter Vogel on 12/22/2010 at 1:16 PM
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