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Data architects are technical professionals in charge of an organizations data systems. They use their IT and design skills to plan, analyze, and implement data solutions for internal use and user-facing applications. Years of study and experience are required to become a data architect; however, its an in-demand role that can get you a six-figure pay package.

Sample Data Architecture Certification from IBM

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Data is currently among the most valuable enterprise assets in the world today. NewVantage Partners 11th annual survey of chief data officers (CDOs) and chief data and analytics officers indicates that 82% of organizations intend to increase investments in data modernization in 2023.

Investment in data products, artificial intelligence (AI), and machine learning was cited as a top priority. This suggests that most businesses require experts who can ensure that their data is readily accessible, organized, and constantly updated. That is where the role of a data architect comes in.

A data architect specializes in developing and optimizing database models to hold and easily access company data. These professionals analyze system specifications, build data models, and guarantee the datas integrity and security.

Data architects are typically part of a companys data science team. They oversee data system initiatives and work closely with data analysts, other data architects, and data scientists. They typically report to the data system and data science leaders. If a company has a CDO, a senior data architect could report directly to that individual.

So, why are data architects necessary in the first place, given that companies could hire data scientists, data analysts, and other data experts? The role of data architects is vital. Without these specialists, data security compliance and data flow can be compromised. This is because they provide the framework for data infrastructure protocols. The architect determines how the other members of the data science team and the company as a whole will construct these systems and manage stored data.

Data architects are specialists at collecting and storing enormous amounts of data. They use their understanding of data collection, analysis, and storage to create an enterprise-wide data structure. Being excellent at math, having the capacity to solve complex problems, and possessing programming expertise are all necessary for this position. They can work for government agencies, universities, IT, financial, or even technical services firms.

Data is at the core of all applications and software. Over time, improperly structured data can look like a pile of spaghetti. This can lead to extended disorder in the software development process and long-term issues for developers. This is where the role of a data architect is important.

Contrary to the widespread belief that data architects solely focus on databases, much more is there to their job than simply creating structured query language (SQL) tables. In the software development process, the role of a data architect is to convert business requirements into established guidelines and standards. This requires deciphering obscure details and transforming them into something logically tangible. Usually, this theoretically tangible construction assumes the shape of technical specifications, modeling of data structures, their interrelationships, connections, and long-term viability concerning business requirements.

When coders create databases ad hoc, the resulting construction could become unstable over time. A data architect would analyze current requirements and design data pipelines that are versatile enough to accommodate future changes, feature additions, or any other need that may arise over time.

While a data architect and engineers roles are closely related, they are not the same.

Together, data architects and engineers create a companys data framework. The data architect conceptualizes the entire framework while the data engineer implements the plan. Data architects prepare the data and construct the framework that data scientists or analysts utilize. Data engineers assist data architects in developing the search and retrieval architecture.

Regarding the difference between data analysts and data architects, the former operates more on the business side of things. Their daily responsibilities include cost estimates, business case writing, stakeholder consultations, and high-level content, which is closer to marketing and sales functions.

The function of a data architect is more hands-on and positioned closely to the software development divisions. Their technical proposals often get turned into software. A data architects day would be spent organizing, refactoring, and unraveling data at a macroscopic level. This includes reorganizing or establishing new data structures for an app and resolving how these models are standardized, passed on, and utilized.

However, like analysts, a data architect can navigate between the various business layers and stakeholders. This activity aims to collect specifications and convert them into a suitable format for software development.

To become a data architect, aspirants need to follow the following steps:

1. Obtain a bachelors degree in a related discipline

A bachelors degree in computer engineering, computer science, information technology, or a comparable field is typically necessary for data architects. Masters degrees can prove helpful but are not mandatory. Usually, data architects have many years of experience in application design, system development, and data management. Therefore, you should successfully finish coursework in these areas.

2. Apply for a summer internship while in college

Data architecture isnt generally an entry-level position. As such, you should gain as much experience as possible early on to prepare for this role. Look for apprenticeships in IT that will help you develop application frameworks and network administration skills. Most leading technology companies offer summer internships to seniors in college, which can give you a leg up in your career as a data architect.

3. Get certified

Being certified always helps. The Institute for Certification of Computing Professionals offers the most popular certification, Certified Data Professional (CDP). Before taking a certification test, applicants must possess at least two years of IT work experience and a bachelors degree.

4. Build on your experience

Those interested in data architecture may require three to five years of work experience and proven project success. Apply for entry-level positions in programming and database management. Keep honing your database development, design, management, modeling, and warehousing capabilities. This is a good time to take on gig projects to add to your portfolio, such as helping a small business migrate its data systems.

5. Apply for a data architect job

After four to five years of experience, youre ready to apply for a data architect position. Look for work in financial markets, educational institutions, healthcare and insurance firms, and other organizations that gather and analyze massive amounts of client data. Software as a service (SaaS) and artificial intelligence companies also employ data architects to power their applications.

See More: What Is Data Science? Definition, Lifecycle, and Applications

Like a regular architect, a data architect designs an organizations data layout blueprint. These designs are then used to create databases as well as other systems. However, this is just a basic explanation, and the roles and responsibilities of a data architect are much more.

A data architect bridges business and IT. Consequently, the data framework they create must conform to both their organizations goals and broader industry standards. For instance, C-suite executives would want to enhance the accuracy and availability of data insights to make better decisions. As a result, a data architect will prioritize this. They will also offer counseling or arguments if something is technically impossible.

The foundations of an organizations IT infrastructure are data models, metadata structures, and pipelines. Throughout the organizations life cycle, they recommend how data is collected, used, controlled, shared, and restored. In addition, they ensure compliance with regulatory requirements and data security. A data architect establishes and distributes a common data vocabulary alongside more technical artifacts. This helps maintain consistency across the organization, even in non-technical teams.

Data architects must track and sustain system health by performing regular tests, fixing issues, and quickly fixing bugs. In addition, they identify key performance indicators (KPIs) to gauge and track the efficacy of the data infrastructure and its individual components. If KPI targets arent met, a data architect would need to suggest methods, such as new technologies, that can improve the current framework.

A data architect calculates how information is safeguarded and who can control it. Further, this professional must ensure compliance with data-related rules, regulations, and guidelines. Consider healthcare data that contains confidential details, referred to as protected health information (PHI), and is bound by HIPAA regulations. If an organization works with medical records and paperwork not stored in medical facilities, it is the data architects job to set up access controls, data encryption, anonymity, and additional security measures.

The General Data Protection Regulation (GDPR) is for gathering, storing, and processing personal information in the European Union. This privacy legislation must be taken into consideration when creating any data architecture.

A data architect oversees the tasks of data engineers, comparable to how a building architect supervises a construction crew setting the foundation for a new building. This ensures their databases, apps, or other data systems conform to the framework. Depending on the development of their data unit, they would also need to coordinate with third-party data suppliers to develop architecture-compliant guidelines.

A data governance policy is an annotated document that details the objectives, processes, and company standards for data management. It outlines metrics and best practices to guarantee data quality, confidentiality, and security. This document ensures all parties agree on who is liable for what reasons and how information must be administered at various phases of its lifecycle. While data architects arent the only individuals who create policies, they significantly contribute to developing data-related regulations and norms.

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Like most technical professionals, data architects need both hard and soft skills to succeed in their roles. The top skill requirements for a data architect include:

A data architects daily tasks and responsibilities involve direct collaboration with data engineers or data scientists. This professional must, therefore, be intimately familiar with an extensive range of data-related technologies such as SQL/NoSQL databases, ETL/ELT tools, etc. Furthermore, a data architects experience with popular tools such as Microsoft Power BI and Tableau is a major asset.

A data architect would frequently need to fix several complexities with data systems, quickly locate the root cause of an issue, and create efficient solutions. In addition, data architects serve as mediators between organizations and data science experts. Their goal is to match technical specifications with business requirements. To succeed in this challenging endeavor, they must demonstrate critical thinking abilities. This facilitates the identification of a companys objectives and the use of its technical expertise to reduce expenses and maximize profits.

Data management reveals the value of a companys data, and it is the duty of a data architect to ensure that metadata rules are relevant to all of the companys data. This means that a data architect must have a solid understanding of data lifecycle management (DLM) and how metadata is applied during each phase of DLM.

Even though data architects rarely need to write code, proficiency in various prominent programming languages is necessary. This is because they must adapt data architectures for various applications in different programming languages.

The top skills here include:

Data architects increasingly need to understand AI, machine learning, natural learning processing, and pattern recognition. This is because AI solves real-world use cases just like data-related issues. An understanding of these tools is also required since they facilitate the use of clustering in text mining and data administration by data architects.

A key skill set for any data architect is data modeling. It entails depicting data flow with structured and architecturally correct diagrams to simplify an elaborate software system. Before creating an app, data models help stakeholders find and address flaws or vulnerabilities.

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A data architect is a mid-level or a senior-level role. As a result, this professional commands a high salary of $131,375 annually in the US, according to Glassdoor data last updated on June 21, 2023. On top of that, these professionals can earn additional cash compensation of $23,271 on average from bonuses, commissions, etc.

Data architect salaries can be as high as $200,000 annually or more, depending on the company one joins. For example, on average, Cisco pays its data architects $224,214 annually, while IBM salaries are close to $180,000. Further, this is an in-demand role in the financial services industry, with jobs available at leading banks such as JP Morgan and Bank of America.

Healthcare providers such as HCA Healthcare and Intermountain Health also employ data architects at a six-figure salary. Therefore, it is worth putting in the hard work, getting certified, honing your data architecture skills, and gaining experience since there is much room to grow in this career.

See More: Five Best Career Choices For Certified Data Scientists

Typically, data architects join as data architecture associates and move on to a more senior position until they ascend to the chief data officer (CDO) role. However, your skills as a data architect are highly transferable, and several other jobs can also be explored.

See More: 9 Skills You Need to Become a Freelance Data Scientist in 2021

Data architecture is now an in-demand role that companies such as Salesforce and IBM offer certifications for. Information is now central to nearly every business process, and enterprise applications need to utilize data meaningfully. A data architect can be a valuable asset to an organization and command a high salary by successfully mobilizing and monetizing information.

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