Data Architect Job Profile
What Is Data Architecture?
Data Architecture (also called information architecture) is a subfield of IT architecture. The underlying structures and processes associated with data or information are considered in Data Architecture. In this context, data in companies is
Data Architecture is the responsibility of a Data Architect or equivalent role. Its goal is to translate business requirements into data and system requirements, and to manage data and its flow within the enterprise. Today, many organizations are modernizing their existing Data Architectures to lay the foundation for their digital transformation and take full advantage of AI opportunities.
What Are the 6 Principles of Data Architecture?
- Data is a common good: Data Architecture should break down departmental data silos in your organization and provide a complete picture of your business to all stakeholders.
- Users need appropriate access to data: A modern Data Architecture must provide interfaces that allow users to easily consume data with the appropriate tools.
- Security is essential: Modern Data Architectures are designed with security in mind and support data policies and access controls at the raw data level.
- Common vocabulary: Common data sets such as product catalogs, fiscal calendar dimensions, and KPI definitions require a common vocabulary to avoid conflicts during the analysis phase.
- Data curation: Invest in core data curation capabilities (modeling key data relationships, cleansing raw data, curating relevant dimensions and metrics).
- Increase data flow agility: Reduce the number of data movements required to reduce costs, improve data timeliness, and improve business agility.
What Components Are Part of the Data Architecture?
- Data pipeline: Describes the process by which data is collected, moved, and coordinated. This includes collecting, enhancing, storing, analyzing, and distributing data.
- Cloud storage: Not all Data Architectures use cloud storage, but many modern Data Architectures rely on public, private, or hybrid cloud instances for agility and flexibility.
- Cloud Computing: In addition to storage purposes, many modern Data Architectures use cloud computing for data analysis and management.
- Application Programming Interfaces: Modern Data Architectures use APIs to make it easier to share or share data.
- AI and ML models: Artificial intelligence and machine learning are used to automate systems for tasks such as data collection or labeling. At the same time, Data Architecture is helping to deploy AI and ML at scale.
- Data streaming: streaming is a continuous flow of data from a source to a destination that is processed and analyzed in real time.
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What Are the Responsibilities of a Data Architect?
The tasks of a Data Architect are broad and range from conceptual and strategic work to hands-on activities. The primary role of a Data Architect is to design, build, and evolve a data architecture that aligns with organizational processes and workflows. A Data Architect plans and maintains a data model based on predetermined Data Architecture principles. He or she designs data flows, identifies data sources, and defines interfaces to data sources and related IT systems. The actual implementation of the Data Architecture is overseen by a Data Architect. Other typical tasks of a Data Architect are:
- Leading Data Architecture projects
- Participating in IT projects as a data expert
- Supporting various departments in the design of suitable data models
- Basic specifications for data quality
- Development of storage concepts
What Does the Requirement Profile of a Data Architect Look Like?
Depending on the organization for which a Data Architect works and the process of designing the Data Architecture, the requirements for the position can vary greatly. The basic requirements for a Data Architect range from being very knowledgeable in data modeling, database management systems, and information management to having specific SQL and database management skills. In most cases, a degree in computer science or a degree in business administration should be available. Due to the strategic nature of the job, a conceptual approach and structured mindset is required of the Data Architect, as well as relevant work experience.
What Skills Are Needed to be a Data Architect?
- Ability to identify the data requirements of an operation or department and develop an architecture to meet those requirements.
- In-depth knowledge of all types of data storage and processing technologies.
- Knowledge of cloud services, including the ability to design architectures using cloud technologies.
- Working knowledge of application design and software development.
- Experience with computer clusters and distributed systems.
What Is the Difference Between Data Architecture and Data Modeling?
According to the Data Management Book of Knowledge (DMBOK 2), Data Architecture defines a plan for managing data assets. Data Architecture aligns with business strategy to define strategic data requirements and designs to meet those requirements. Accordingly, data modeling is “the process of discovering, analyzing, representing, and communicating data requirements in a precise format (data model).”
Both Data Architecture and Data Modeling aim to bridge the gap between business goals and technology. Data Architecture, however, is about a macro view that aims to understand and support the relationships between organizational characteristics, technologies and data types. Data Modeling, on the other hand, focuses on a focused view of a particular system or business case.
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