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Even though data tends to be chaotic, it is the lifeblood of an enterprise. Outdated, inaccurate, inconsistent, and duplicated data can translate to severe issues affecting operations, hence amplifying the importance of data architecture.
The data architecture of a company helps align its data insights with its business strategies. Using the data architecture, businesses collect, integrate, enhance, store, and deliver data to employees.
Unfortunately, not all businesses can afford to hire a data architect, so they delegate data tasks to chief data officers instead. Whatever role a company needs, one thing is for sure: the need for data architecture is stronger than before.
The Lowdown
Essentially, data architecture helps create more defined schemas, integrations, transformations, storage, and workflows required for the creation of data framework and enables data access, assessment, and analytics. These processes all point to a goal: business success!
As more agencies and institutions rely on technology and data, the demand for Data Architecture degree holders has grown significantly over the years.
Hopefuls can start by obtaining a bachelor’s degree in Data Architecture and related fields, such as Data Science, Data Engineering, Data Management, and Data Analytics.
Taking those professional skills to the next level is a graduate degree in Data Architecture. Also involving Data Science Engineering methods, a master’s program focuses on the processes and guidelines for managing data from the moment it is captured in source systems to the time it is consumed and used in business.
What is Data Architecture?
Data architecture describes the manner through which data is collected, transformed, distributed, and consumed. It establishes the framework for data storage and how information flows through that storage system.
Artificial Intelligence (AI) applications and data processing depend on and benefit from sound data architecture. The Internet of Things (IoT) also requires data architecture to generate new data sources and manage data.
Superior data architecture and management “cleanses” and “deduplicates” or removes duplicate data from computing systems involving big data systems.
As well as integrating data across domains, such as departments or geographies, modern data architectures also remove the complexity of managing everything in one place, allowing data silos to be broken down. Data architecture is also integral to the utilization of enterprise application integration software.
For managing and processing data, modern data structures and data models often rely on cloud platforms. Computing scalability allows for the rapid completion of data processing tasks. Scalable data storage helps enterprises cope with rising data volumes.
Strong Demand for Data Architects
Did you know that data professionals’ roles are changing? Traditionally, data scientists built data warehouses and analyzed data using limited resources. As state-of-the-art technologies for advanced database systems emerge, data architects, data scientists, and data analysts can implement new methods.
The latest Bureau of Labor Statistics information sets database architects’ median annual wage at $112,120. The demand for employment is projected to grow 8% from 2022 to 2032, making it a promising field.
Data architects hold one of the most interesting careers in data-driven and technology-focused businesses. Keeping a data architect career means visualizing data flow management in order to define how databases operate, taking into account the type and source of data.
The work of database architects plays an important role in product development and related processes.
If you are a certified data management professional and data architect who earned a master’s degree, you are also expected to be skilled in setting the structure for the development and implementation of data governance.
How to Become a Data Architect
Data Architect education is crucial in producing experts in this field. Professionals start to study Data Architecture through bachelor’s programs.
These undergraduate programs involve data management, programming, database development, big data development, systems analysis, and technological architectures as part of their coursework.
In most cases, Master of Science degrees are required if you’re aiming for higher positions or higher pay.
Your experience may be the most important aspect of your employment application. Top employers will likely require candidates to have experience handling network management, performance management, and application architecture.
Data Architect Soft Skills
Also, it pays to have the following soft skills to stay ahead of the competition:
Effective Communication
As a data architect, effective communication is a must. You should learn to listen carefully to managers, data analysts, and relevant staff in order to design the best data model. This also means you need to take time to explain difficult concepts to non-technical colleagues.
Industry Expertise
As a data architect, you should already have enough knowledge and understanding of data management and analytics. You should have ideas on maintaining flexibility in the face of big data developments and understand how to collect, analyze, and utilize data in your chosen industry.
Problem-Solving Skills
Problem-solving skills are necessary for data architects. You should know how to handle high-level data challenges efficiently and effectively.
Management Skills
Leadership and advising a data modeler, data engineer, database administrator, and junior architect team.
Data Architect Certifications
Take advantage of the opportunity to earn more certifications and qualifications. IBM, Salesforce, and Hortonworks all offer opportunities for data architects to expand their expertise and learn. You can maximize many programs and other resources to learn new things about data architecture.
Data Architecture professionals are not required to be licensed. Although a database architect is considered a licensed engineer, a license is not always required to practice.
Data Architect certifications and continuing education are valuable to most data architects, enabling them to stay on top of the latest big data.
Similarly, membership in professional organizations provides data architects with increased opportunities for networking and career advancement.
Which College Offers A Degree in Data Architecture?
Determining the discipline of data architecture and what colleges offer them is the first step to finding this lucrative and important career track.
Undergraduate programs focusing solely on Data Architecture aren’t common in the United States. Instead, many programs integrate the discipline into different tracks, such as Data Science, Computer Science, Software engineering, Computer Engineering, and other related fields.
The altered versions of Data Architecture are Database Management and Management Information Systems.
Northeastern University’s Master’s Degree in Data Architecture
The Data Architecture and Management degree on the master’s degree level is offered solely by Northeastern University in Boston, Massachusetts.
The Master of Science in Data Architecture and Management program furthers the skills of data scientists, business analysts, and engineers in performing data integration, also called data preparation or data curation. With a master’s degree, data architects become qualified for senior positions as long as they meet the industry requirements.
Offered through the Northeastern University College of Engineering, this graduate program covers the numerous components of advanced data architectures, including:
- Advanced-Data Management
- Data Warehousing
- Business Intelligence
- Data Science Engineering
- Big-data Engineering.
- Advanced Big-data programming
- Advanced-Data Science
- Cloud Computing
- Multi-thread Concurrent Computing
Data engineers possess a unique set of skills that are sought after in multiple industries. The jobs essentially involve processing huge amounts of fragmented data, often from thousands of sources, to identify business opportunities and reduce risks.
Frequently Asked Questions
Are data architecture, data engineering, data analysis, and data management related fields? How are they the same, and how do they differ?
The work of data architects and data engineers is dependent on one another. Both play an important role in conceptualizing and developing an Enterprise Data Management Framework.
A data architect is in charge of visualizing the framework and creating the blueprint. A data engineer, in turn, utilizes those to create the “digital framework.”
Data managers focus on data access and data collection, while data analysts extract insights from data. These data-driven and data-focused technical skills are crucial to developing the right structures, data workflow, and processes.
Do Data Architects have to be skilled in coding?
Unlike data analyst jobs that don’t necessarily require coding skills, data architects are expected to be prepared for coding work. This skill is needed for setting up data structures and implementing data-driven systems.
Data architecture may entail implementing systems on the cloud and server structures, which all require coding skills and some knowledge of programming.
Data Architecture courses may also include refreshers on topics such as machine learning and programming languages.
Summary Points
- Using computer science and design skills, data architects are responsible for database design. They help implement solutions for storing and managing data for business analytics purposes.
- There is an ongoing increase in data architect demand, giving you access to growing job opportunities in the future.
- An MS in Data Architecture degree, particularly offered in the US by Northeastern University, is your gateway to advanced data architecture education and training. These courses prepare students for career advancement.
- It is not uncommon for data architects to work in industries including technology, entertainment, healthcare, finance, and government. Such is the trend as almost every business utilizes data and obtains relevant insights to enhance business workflow and drive optimal business performance.
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