Information Management: The Value of an Enterprise Data Model (Part 2 of 2)
Enterprise data models have a host of benefits that your enterprise can enjoy. We explore the benefits and uses of an EDM.
By Mehdi Hatami
Last week we looked at how an enterprise-wide data strategy can help you cope with the growing complexity, number, and use of applications and examined how this model is the foundation of associated solutions and how it’s different from other business information management solutions. This week we take a closer look at the benefits and uses of such a model.
Almost every development methodology, architecture framework, and data modeling textbook recommends three levels of data models:
Together, these levels form a comprehensive view of the data structure across an enterprise. Historically, these three levels enabled the construction of various client/server ERP, CRM, and other applications reliant on a central database for data management.
Today, however, our view of the data is not limited to a local relational database or to one LOB or operation within an organization. Data needs to be modeled and represented at different levels and across boundaries within an enterprise with the goal of integration, sharing, and efficiency.
An enterprise data model (EDM) -- a high-level, textual and graphical view of data across an enterprise -- provides such a representation. The model consists of enterprise-wide subject areas, fundamental entities and their relationships, and unified terms and definitions.
Developed in cooperation with key decision makers, an EDM represents strategic information requirements of the enterprise (e.g., accounts, policies, products, services, customers) and provides a common view of the information including terms and data-related business rules. Strategic information needs are defined or modeled based on known (current or planned) business policies and strategies independent of the technologies in place at the organization.
The EDM includes a central metadata dictionary or repository that provides consistent, standard definitions for information. The metadata repository enables the discovery of common threads, cross-functionality, and common definitions of the business entities by providing contextual clarity to information. Even when no systems or schemas are developed as a result, the metadata repository is an invaluable tool for improving information flow and for rationalizing relationships between LOBs.
An EDM improves communication between IT and business staff by clarifying the rules involving business information and by placing a governing entity -- a data steward -- in charge of data quality and flow. To embrace data stewardship is to place the accountability, control, and quality management of enterprise data in the hands of subject-matter experts who can establish common subject areas and eliminate costly redundancies.
The EDM is the foundation for future logical and physical data models, upon which future critical business projects depend. Without a view of enterprise’s systems and schemas, OLTP systems, data warehouses, and XML schemas cannot function at their optimal level, if at all. The goal of EDM is a foundation of data that is a shareable, consistent, reusable atomic source of information for the transaction processing systems, data warehouse, and XML data exchange.
The EDM becomes a reference model: a blueprint for integrated information management systems across the enterprise. It is the basis for understanding of current and future application information needs and for improvements to information delivery, exchange, and integration.
Enterprise data models have many uses, making them an increasingly necessary element for successful organizations:
- The logical model and the associated definitions and relationships can be used by enterprise information architects to standardize information modeling and to align project information models
- Having an enterprise data model improves data custodianship or data stewardship by ensuring a consistent view of the information across the organization
- An enterprise data model is extremely helpful for planning, estimating, and prioritizing projects; it enables advance information evaluation as well as strategic planning by enterprise architects
Today, many organizations are involved in initiatives to design and build an enterprise data warehouse or to consolidate their existing data marts. An enterprise data model is extremely beneficial to these initiatives.
As service-oriented architecture becomes more critical to companies active in a global market, many organizations are interested in implementing master data management (MDM) to manage their common information in one master data store. An enterprise data model makes sure the information that is defined as master data has a consistent definition across the enterprise.
Your organization can choose to build your enterprise data model in house or purchase a commercial model for your particular industry. While models developed in house are more strictly tied to a company’s business needs and processes, consulting firms and major software developers offer a number of valuable and comprehensive industry models.
Enterprise information architecture and enterprise data models help organizations understand their accumulated information; however, they are only blueprints. The value of these initiatives will only be known once an organization seriously commits to them and implements and deploys them with methodological rigor.
Just as the blueprints for a house will not serve as a shelter, it is only when the house is built that other benefits -- a place to entertain friends or from which to run a business -- will become apparent and can be enjoyed. In addition, a blueprint must also be flexible to environmental changes, external challenges, and changing customer needs. The information model should represent actual or intended structures and have built into it flexibility and room for extensions.
To effectively define an accurate information model that is truly representative of the business, the enterprise data architecture team needs the input, commitment, and cooperation of IT and all other lines of business. Successful deployment depends on clear direction from key organization stakeholders and effective communication between all levels.
Mehdi Hatami is lead consultant at Adastra Corporation, a Toronto- and Prague-based international leader in business information management. You can contact the author at email@example.com.