More and more organizations are recognizing the need to manage business processes and information data sets on an enterprise-wide basis, bringing out a synergized alignment of the processes and resources with a strategic intent. Also, there is an increased need for accurate and reliable frameworks which are highly scalable supporting the rapidly changing business needs of users and consumers. To manage an organization today, the formation of an enterprise information architecture is being adopted as an essential tool in managing the knowledge repository. This article analyzes the enterprise data architecture within the information architecture space and explores the typical challenges and opportunities the organization faces in building this initiative.

Enterprise Data Architecture – A Critical Success Factor

Why is it important? Enterprise data architecture provides a holistic view of the organizational structure and the interrelationships across different units within an organization. If there is a lack of understanding, where an organization stands in terms of assets (software, technology, business process) and resources, it will be difficult to move in the right direction going forward.

Enterprise data architecture is essentially a knowledge bank repository consisting of core software for maintenance and development, the interactions between the architects, the business community and the development team along with the information data sets. The creation of enterprise data architecture center of excellence (CoE) can help companies reuse existing frameworks, improve the speed of implementation and enhance the success they achieve across projects.

Figure 1: Enterprise Architecture Reference Model

Opportunities for Enterprise Data Architecture – Managing Enterprise Capability

The usage of implementing a CoE for enterprise data architecture has benefited many business partners. The following are examples of notable areas where an enterprise data architecture (EDA) setup has added value to an organization.

Risk Analysis. The benefit of an EDA is illustrated when considering the case of extending credit to consumers. If a firm can successfully perform data mining beyond the openly available credit scores from credit risk agencies (CRA) establishing a multidimensional risk decision process in regard to extending a credit line, then the firm can, perhaps, quickly become an industry leader and build a monopoly in their line of business.

Mutual Funds. If a mutual fund company (MFC) can quickly identify un-invested cash from its investors, then it can quickly deploy the same for fresh investments yielding better returns. Again, if a MFC can holistically report their exposure towards a particular company, sector or region, then fund managers can smartly divert funds to other channels or lines of business. Thus, in times of crisis, a MFC is able to differentiate itself in the market.

The two aforementioned scenarios, both being real time, highly data-intensive operations require a well-planned, well-architected and a best-in-class IT enterprise-wide capability. For this to happen successfully, every organization needs to establish a CoE defining the data governance rules and possibilities as well as the channels of data availability,  Also, the delivery and integration of data within a highly scalable framework able to tap changing demands is a requirement.

Benefits

The enterprise data architecture CoE acts as single point of contact for all data architecture commitments and implementations, becoming the centralized model for any project. All the architecture components along with the architecture implementation plan are moved out from both the development and the business teams to a centralized pool functioning as a shared service to all the business enabling units. The following are some of the numerous benefits of an enterprise data architecture CoE:

• Involves all stakeholder areas
• Adopts best practices from within the organization
• Has well-defined strategic practices for each process area
• Evaluates available tools and methodologies standardizing implementation
• Establishes enterprise standards, procedures and governance
• Standardizes infrastructure, development methods and operational procedures
• Identifies the existing architecture services and discovers the overlaps and redundant architectures within the organization and determines which among those can be standardized
• Fills the void of the existing architecture services
• Creates repeatable processes, common business rules and components tailored to business needs
• Lays down rules and policies on how information is conceived and distributed
• Helps to increase business agility
• Enables reuse and faster time to market and increases ROI
• Helps to align the business to IT

Challenges

While many benefits of enterprise data architecture CoE exist, there are certainly challenges present when implementing one, including:

• Responsibility: Bestowing responsibility to a CoE team for all enterprise data and assets is challenging.
• Time to market: Since we have no time to define and implement a strategy, every project is tactical.
• Emphasis on development: The “code first and analyze later” approach is generally supported by the development community.

Many enterprises today are capitalizing upon the formation of an enterprise data architecture CoE which facilitates the use of knowledge bank repository and enables organizations to plan, align, control and implement the changes at a lower cost and at a quicker pace.

The use of the common standards, development methodologies and design processes along with business enterprise CoE has helped in maximizing the ROI of organizations. To get the most value out of a business, enterprises need to plan and architect right from the beginning by setting up CoE which defines the implement patterns across the organization and therefore creates a plan to optimize and maintain software.

Enterprise architecture is not simply a description of the technology favored by the IT organization, but is essentially the IT organization’s business plan.

Bibliography:

1. Flower, Martin. Patterns of Enterprise Application Architecture.
2. Minoli, Daniel. Architecture A to Z Frameworks, Business Process Modeling, SOA, and Infrastructure Technology.
3. Mutual Fund Terms and Terminology - www.investopedia.com.
4. Handbook of Software Engineering and Knowledge Engineering.

SOURCE: Enterprise Data Architecture: Opportunities, Challenges and Expectations

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