What is not included here, is the time it takes staff to synchronize and determine what the “truth” or information of record is.This activity often turns into projects, and projects that occur anyone wants to build anything that uses or attaches to this data. It is necessary to determine who entered what, and when it was done to determine which information is more current.

Where and What are Your Truths?

While we all know this, we almost all accept it as a problem that we ourselves did not create. It is almost always left to be done later, which we all know never seems to happen. One of the ways that some organizations deal with this is to use data warehouses and store information about validity and truth within the meta data repositories. More data, more work, more synchronization and more updates.

Yes, it’s better than redoing the research projects each and every time we wish to use the data, but not necessarily the best use of our time.So what can be done now? As we seek to develop projects that need or use the data, we can seek to reuse data that already exists where possible, and seeks out those who will take responsibility for keeping it current.

Easier said than done, but if we are to find those who experience pain in not doing this, it is possible. The other things we can do is build bridges back to the best known source of the information and attempt to decommission the areas we find not to be valid or reliable as we find them. There are very few projects on our books that are willing to incur the expense in doing this type of work, but as business and IT organizations, we need to treat this as some sort of “tax” or “levy” for using common information in the first place.

Organizations who are information intelligence focuses, those who primarily provide and use data to create revenue are the most able to gain from such a perspective. Problems we created years ago don’t go away over night, but the best way to eat an elephant is chunk by chunk, and if we don’t put this one on the menu, no one will ever eat it, and the pain will cost us far more over time than these one time taxes ever will!

Highest Level: An information environment, which includes an organizational culture around information, as well as information strategies. The strategies include planning and maintaining relationships from business to information through structures and technology. It also includes data governance at the highest levels.

Second Level: The Enterprise Information Architecture which includes Information principles, rules for detailed information governance and sharing, information content design, and linkage to the Business Architecture.

Third Level: Information Management which includes Data Stewardship, Information Security and Access tools, processes and procedures, Extraction and Transition and Loading Strategies, Database Server Administration Policies & Guidelines, Data Quality and Integrity Rules, Data Definition Standards, Dictionaries and Content Indices.

Lowest Level: At the most granular level, the Information Architecture contains the information architecture made up of databases, data warehouses, logical, physical & data warehouse data models, backup and recovery procedures, database execution scripts, meta-data management, data performance and auditing, etc.

A brief description of the main components of an Enterprise Architecture:

The following are components of an Enterprise Architecture. Each individual component is part of the Framework.

1. The business architecture component analyzes the company’s business drivers, opportunities, goals, objectives, and strategies. For instance, does the company plan to develop new product lines, infiltrate new markets, and reduce operating costs, or increase customer satisfaction and loyalty? What are the most critical business problems or opportunities? The business-architecture model also provides a high-level blueprint of all critical business events and processes, along with a description of their relationships and interdependencies.

2. The organizational architecture entails a comprehensive examination of current IT processes, services, organizational structures, roles and responsibilities, and core competencies. All these components are carefully analyzed to see how well they facilitate the creation of flexible application and technical architectures that can quickly adapt to support new business requirements. It may also be referred to as the operational architecture by some.

It addresses fundamental questions such as: How well are IT services managed? How well the IT organization does contributes to the overall enterprise’s success? Are IT services closely aligned with the business strategy? Is the current IT technology infrastructure a barrier to supporting or expanding business?

3. The application architecture lays down the core business applications required to enable business processes and successfully run the business. The application architecture model encompasses all legacy systems, software packages, and distributed systems, along with an appraisal of their strategic value and impact on the business.It also identifies the new applications that are required to satisfy up-and-coming business needs. An assessment of the health of current applications is equally important to include, Fournier says, both from a functional and technical standpoint. Finally, the application architecture must carefully analyze the interdependencies and interoperability needs that are required between business applications.

4. The information architecture examines the key information assets of the enterprise. What are the types, locations, and timing of information that are required to achieve the prime objectives laid out in the enterprise business plans and processes? What types of information need to be shared? In what state is operational and informational data? The creation of the information architecture model also encompasses building an inventory for all operational files, databases, data warehouses, and data marts that are required by current and planned business applications.

5. The technical architecture model scrutinizes the underlying technologies that are required to run the applications, such as computing platforms, networks, operating systems, database management systems, storage devices, and middleware. The technical architecture model can be broken down into specific sub-models, such as platforms, networks, security, and more. For example, some companies have developed a comprehensive security architecture blueprint to enable e-commerce in a secure fashion. Throughout the construction of the technical architecture model, potentially overlapping or incompatible technologies are identified, and those that do not make the grade become candidates for being phased out.

The Data Architecture of an Organization is a depiction of the useful data of an organization. It shows the hierarchies and dependencies of that data to other data at the set level of abstraction. It is not necessary for there to be a database oriented realization of the data in an architecture. Much of the useful data of an organization has no automated expression at all. At the Business Architecture level, the Data Model should be thought of in conceptual terms – key business domains, rather than a fully detailed Entity Relationship Diagram.

The process architecture relates business processes with data architecture.

A Data Architecture is a hierarchy of data sets and proper subsets.