Enterprise Information Architecture remains a core concept in the world of data management. Its importance is heightened in these current times as real-time mobile accessibility combined with increasing data size and velocity force enterprises into taking a closer look at how their data gets architected.
Organizations need to know that deriving business value out of data depends on related concepts like data governance and data quality. It is extremely difficult, if not impossible, to implement any data governance program without an emphasis on information architecture. This article looks at the latest trends and concepts in the practice of Enterprise Information Architecture.
Adaptive’s Enterprise Architecture Manager
The Platinum sponsor Adaptive held a large presence at this year’s Enterprise Data World conference. The company is considered to be a thought leader in the areas of Metadata and IT portfolio management as well as Information Architecture. Their entire product line leverages the Adaptive Framework, an automated system that handles the capturing, storing, visualization, and analysis of any organization’s resources around technology — from processes and documented strategies to hardware and stewardship. The Adaptive Foundation is a related, industry compliant product able to import similar information from various structured data sources.
Enterprise Architecture Manager (EAM) is the flagship of Adaptive’s product line, a fully-fledged solution well suited for the EIA role. EAM captures the full range of an organization’s Enterprise Architecture “from strategic intent to business processes to enabling resources.” In short, it handles more than just an organization’s IT and data resources. The tool uses the Adaptive Reference Model and its eleven architectural domains to model the enterprise information.
Leveraging an easy to use web-based drag-and-drop interface, EAM supports the latest in meta-modeling standards, including the Zachman Framework, TOGAF9, SWOT Analysis, and Balance Scorecard, as well as others. The product scales nicely and is easy to deploy at large, widely-distributed organizations.
Any organization looking to capture strategic intent, ensuring its understanding throughout the enterprise, needs to explore Adaptive Enterprise Manager. It enhances the development of Enterprise Architectures to align business and IT strategies, processes and resources across multiple data sources. EAM is an industry leading Enterprise Information Architecture tool.
Iasa Global Provides Professional Development for Enterprise Architects
Experienced and new enterprise architects looking for a professional organization need to check out Iasa, a premier association focused on the IT architecture profession. The Austin, Texas firm helps in the development and delivery of standards related to Enterprise Architecture. They also provide educational and accredited certification programs for interested professionals.
Iasa is relatively new, having been formed in 2002. Like DAMA, Iasa sports chapters in both the United States and all over the world. The organization has over 70,000 members, located in over 50 countries.
As part of its focus on education, Iasa’s website features a robust repository filled with various multimedia resources covering the gamut of the IT architecture world, including the different roles found within the Enterprise Architecture profession, a collection of analyses on concepts making up the next generation in IT, as well as an inventory of the related skills that are a part of any professional enterprise architect. The organization also provides formalized (both virtual instructor led and onsite) training with the following course schedule.
Iasa offers the Certified IT Architect and Iasa Foundation Certification programs as the only vendor independent architect certifications in the IT industry. The organization also hosts Enterprise Architecture-related events both under their own banner, and at conferences like Enterprise Data World.
Fledgling and experienced enterprise architects can became Iasa members for a yearly due of $75. Student memberships are available for half the price of a regular membership. In addition to the training and certification benefits, members also receive free subscriptions to Iasa’s bi-monthly newsletter and quarterly magazine, as well as access to the ITABoK, the IT Architect Book of Knowledge, an industry-proven collection of best practices in Enterprise Architecture. Membership is Iasa is a no-brainer for any enterprise architect looking to further enhance his or her career.
The Knowledge Warehouse’s Approach to Data Lifecycle Management
The Knowledge Warehouse, better known as Knoware, is a New Zealand-based company specializing in the development of Data Warehouse and Business Intelligence systems. One important aspect in the architecture of these kinds of systems is the concept of Data Lifecycle Management (DLM), which covers the flow of data, information, and Metadata throughout the various IT applications at an organization.
According to Knoware, DLM “encompasses principles, policies, practices, systems, and tools used by an organization to manage information through every phase of its existence.” While in many instances the business value of data decays over time, this is not always the case. For example, timely access to older data may be a requirement for regulatory purposes. In short, a well-honed Data Lifecycle Management process leads to “better data, better decisions, better business.”
The risks for an enterprise not implementing Data Lifecycle Management include unlawful early disposal of data or conversely the perpetual retention of uncritical data. Failure to design ease of data management and retrieval into a DLM system leads to being unable to access data at the critical speed of business.
Data Lifecycle Management systems need to handle both structured and unstructured data stored in a variety of formats. This also needs to happen in a fashion transparent to the user. Data retention requirements need to be sharply defined. Like many other large IT-related initiatives, starting with small, manageable sub-tasks and creating a project road map helps to facilitate success.
For implementing a successful DLM process, Knoware recommends using what it calls the 5D Model. This includes the following:
- Discovering what data assets exist and how they are used.
- Describe and characterize those data assets.
- Define the business and legal requirements with using the data assets.
- Determine the management process for the data lifecycle.
- Deploy the lifecycle management elements.
Doing it again and again becomes the sixth silent part of the 5D model. The Data Lifecycle Management process should become part of any organization’s Data Quality or Data Governance program.
Royal Dutch Shell Deploys a Global Data Architecture Strategy
As an oil conglomerate with a worldwide presence, Shell has activities in over 90 countries with nearly 44,000 retail service stations. Upstream activities include energy exploration and development, while refinement, retail, and B2B activities make up their downstream work.
Shell’s Data Architecture Framework includes a strong dollop of governance, which is important given the regulatory requirements of their business. A data taxonomy includes items normally present in any Metadata repository, along with a focus on conforming to a maturity model. All this comes together in a company-wide Enterprise Data Catalogue, allowing for projects to be scoped and overlaps to be mitigated, which improves overall company efficiency.
Important to Shell is the realization that strong Data Architecture leads to improved Data Quality, which of course, ultimately enhances business value. They found that modeling their “world” in breadth provided a measure of scope, followed by more granular modeling in depth as it benefited the business. The use of general business terms helped in preventing over-abstraction; the DMBOK was used where necessary to provide consistency in terminology.
CLAPR Brings a Pragmatic Take on Enterprise Data Architecture
At this year’s Enterprise Data World, three industry veterans, Jim O’Brien, Peter Aiken, and Jack Billig, gave a presentation on the CLAPR Framework, a pragmatic approach towards Enterprise Data Architecture. They made an important distinction that Enterprise Data Architecture is not a combination of data structures, database platforms, and server hardware. Combining data modeling with platforms and hardware leads to tighter coupling and thus, reduced flexibility.
Rather, this intrepid trio focused on the development of an “integrated set of models based on an extensible framework.” This included four Classifications on Locations (placement within an area), Activity (energy expended over time), Party (people or groups of people), and Resource (material utilized by an Activity.) The CLAPR framework was born. These different taxonomies also relate to each other through joins; for example the framework supports ResourceLocations, PartyActivities, etc.
In a typical modeling refinement process using the CLAPR Framework, root models undergo a transformation into singular entity types through iteration where the more detailed sub-types are defined by identifying the common characteristics unique to that level of granularity. A similar process occurs for relations and their constraints and properties.
Challenges in implementing the CLAPR Framework at an enterprise are similar to any other change in an IT practice requiring a new paradigm. From a lack of understanding and buy-in from leadership, to typical technical issues like legacy systems or inadequate tools for model management, these hurdles are worth overcoming to achieve the business value benefits possible from a clear framework for modeling enterprise data.
The Zachman Framework in Action at Wellmark Blue Cross Blue Shield
Wellmark Blue Cross Blue Shield and its subsidiaries provide health insurance to over two million people in Iowa and South Dakota. Given its acute need for quality Enterprise Information Architecture, the company’s enterprise modelers decided to leverage the Zachman Framework as part of their own architectural models and standards.
It was important for Wellmark to define standards each Zachman Framework cell, whether or not that cell was fully implemented. These model standards always include a definition for the cell it represents, each object for the model and all attributes, and relationships to other models in the same column and row of the Zachman Framework.
One pitfall Wellmark found involved slavishly trying to redefine the Framework column by column and row by row. Reliance on model diagrams also proved troublesome as they are provide a partial view of the model and are not part of the model definition. Ultimately, following John Zachman’s work in enterprise ontology proved useful to the Enterprise Architecture process at Wellmark in the manner of any quality IT framework.
Enterprise Information Architecture remains an important part of any large organization’s IT department, touching on most other data-related disciplines including modeling, Master Data Management, and Data Governance. Resources smartly spent on EIA usually provide a robust return on investment.