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TOGAF in Data Architectural Way
Updated on 23 June, 2017
10.2K+ views
• 5 min read
In today’s world of competition, rest assured that your organization definitely has invested in some kind of funds systems viz- CRM, ECM, eCommerce apps, and more. Despite the efforts and investment, many employees are struggling with finding their required data, whether it is built or not. This leads to failing your customers’ expectations and can miss real opportunities to engage, deliver and satisfy.
Though your business has the technology and talent, there are some limiting factors that can inhibit your organization’s success. Also, an enterprise always wants to manage its data across the organization, ensuring that it can implement the newest solutions quickly and effectively. To establish this, you need to follow some protocols.
The solution for this is to maintain proper Data Architecture. Data Architects are liable for providing critical data to the correct people at the right time. They do it by mapping and visualizing the data models in an easily understood format that allows your technology investments to support achieving your business goals. Due to the data architect’s coordination in forming a successful data architecture, customers will get a superior digital experience.
Definition of Data Architecture
The Open Group Architecture Framework (TOGAF) provides a methodology and a set of tools for developing an enterprise architecture, which includes data architecture as well. As per the IT aspect of an organization, a simplified approach with reference to TOGAF, to establish data architecture is as follows-
The Data Architecture approach can be divided into four major areas as follows-
- Business Vision
- Data Management
- Data Governance
- Gap Analysis
Major Areas of Data Architecture
Let us have a look at the subsequent sections, along with their respective areas, as follows.
1. Business Vision
The reason behind establishing the data architecture is to develop a high-level vision of the business values to be delivered. The business vision is to ensure the precision and uniformity of data, and all data should be captured from the correct source without any manual intervention.
According to the business vision, the data architecture policies and standards are defined. The scope of data architecture is defined as per the organizational needs. Let us consider an instance where the scope of data architecture is limited to Business KPIs of enterprise business activities.
2. Data Management
If the data is structured and comprehensive, it enables the effective use of data. The purpose of data management activities is as follows:
- Identifying the master data, reference data, and transactional data.
- Identifying the utilization of the data entities of business functions, processes, and services.
- Identifying how and where data entities are created, stored, delivered, and reported.
- Identifying data conversion complexity level to exchange information between applications.
- Identifying software required for data integration with the customers.
Let us have a look at some data management aspects:
Data Modelling
Data modeling describes the structure of data entities with their relationships. It consists of 3 types-
- The conceptual data model holds implementation details to focus on the entities and their relationships and attributes that are evoked in the domain where the problem arises. Generally, this model is used for communication with the stakeholders.
- The logical data model is an updated version of the conceptual data model in data management technology. A perfect example of this is relational databases. It includes the subject of normalization.
- The physical data model consists of the implementation of data entities. It includes optimizations consisting of merging entities, duplicating data, creating identification keys and indexes.
Process-Data map
Process-data mapping helps to understand the data entities utilizing the business functions, processes, and services.
C – Create, R – Read, U – Update, D – Delete
3. Data Governance
Data Governance ensures that the enterprise should have accountability, quality, integrity, and security of data. The purpose of data governance is to:
- Identifying the organizational structure and the standards required to manage the data.
- Identifying the employees with skills and roles for data transformation in an enterprise.
- Identifying the data entities to manage the business processes.
- Identifying the data controller and archival requirements.
Let us have a look at some data management aspects:
- Ownership (Role–Data matrix) –
It identifies the organizational structure and the standard bodies involved in the management of data entities. Following is the diagram to explain this in an easy way.
C- Create, R- Read, U- Update
- Security–
The Data Security aspect depicts which actor (person, organization, or system) can access to which attributes through various business processes and applications. It can be well studied from the diagram.
- Life-Cycle:
The Data life cycle captures data entities and the processes involved in various stages throughout the life cycle of one process. It stems from the creation stage, progresses to the storing stage, and finally ends when it is deleted.
4. Gap Analysis
This process consists of verifying the data architecture against the data principles and business vision. Following are the solutions to understand what gap analysis is and how to overcome the gaps by finding high-level solutions-
- Compliance Assessment–
This matrix illustrates the functional and technical charges in the current architecture.
- Complaint Solutions–
This matrix illustrates the potential building block architecture and solution for functional and technical charges in the current architecture.
The outcome of the data architecture is not restricted to the architecture definition document, updated versions of the architecture vision, and the validated data principles. A data architecture framework is the major part of the TOGAF course, which provides a set of rules for developing the entire organization’s architecture.
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Conclusion
TOGAF in data architecture can be a great asset. TOGAF is the Open Group Architectural Framework, a globally recognized architecture framework that can help guide companies toward successful business outcomes. TOGAF allows organizations to design and manage how data is used and integrated into their IT solutions. TOGAF offers data models, architectures, techniques, best practices, and governance principles that allow companies to understand their goals while integrating previously gathered information.
It helps organizations make informed decisions by providing them with up-to-date knowledge of the technology available. TOGAF enables concise communication between business and technical stakeholders throughout the development process and acts as a reference for professionals specializing in data architecture. The TOGAF approach gives companies confidence in making well-thought-out decisions based on reliable information about implementing their chosen technologies. If you are looking for a framework to help you design and implement an effective data architecture, TOGAF may be the right choice.
Frequently Asked Questions (FAQs)
1. What are the 3 types of architectural models?
There are 3 types of architectural models used today: TOGAF in data architecture, Software, and Business. TOGAF is a highly popular model used to create architectures in software engineering and info systems – it outlines processes, principles, and best practices when working with data architectures. Software models focus on improving IT projects, while business models help improve strategic development.
Each model offers something different, so depending on your project needs, you can choose which type would work best for you!
2. What is the TOGAF architecture Development Method?
The TOGAF architecture development method, also known as the Open Group Architecture Framework, provides an organized approach to developing enterprise architecture. This systematic process follows a common framework and includes steps from creating an initial business case and scoping the project to defining principles so that the results are quantifiable and easy to measure.
3. What are the three levels of a data architecture?
Data architecture is all about structure, typically consisting of three levels. The first level is conceptual, which involves defining an organization's business requirements and summarizing where the data comes from. The second level is logical, which involves refining the conceptual design details to make it possible to use a specific technology or framework. Lastly, physical architecture describes how the data should be stored, like choosing between cloud servers, databases, hardware configurations, etc., while keeping track of current versions and maintenance activities.
4. Why is TOGAF the best enterprise architecture?
The Open Group Architecture Framework (TOGAF) is an industry-standard framework for enterprise architecture. It offers a clear, organized way to break down information for an enterprise project and manage it more effectively. TOGAF provides practical guidance on all aspects of the organization's planning, designing, implementing, and managing change. The benefits of using TOGAF include increased agility, improved decision-making process, and better organizational performance. Additionally, many enterprises have found that they save time, effort, and money in their enterprise architecture efforts by using TOGAF.