DATA— the four-letter word is a tremendous force that drives modern-day businesses. There isn't a single organization today that doesn't attempt to harness the power of data to find solutions to problems, make informed decisions, deploy strategy efficiently, and run smooth business operations cost-effectively. 

According to a Forbes article, 52% of global enterprises are actively analyzing data to derive operational insights for making better decisions. 71% of these businesses are of the view that organizational spending on data and analytics is going to speed up in the next few years.

Amidst the buzz around Data and the advanced level chatter about Big Data, several new organizational roles have emerged that are helping companies source, process, and assimilate complex data daily, from within the enterprise and beyond. Data Architect or Big Data Architect is one such role that is highly pertinent in today's data-driven world. Before we elaborate on what does a data architect do, let us understand what is Data Architecture. 

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Data Architecture Demystified

Simply put, Data Architecture is the organizational framework aligned with business processes that standardize the process of data collection, storage, transformation, distribution, and usage. The framework is created to secure sensitive data yet making the most relevant pieces accessible by authorized people at the right time. 

Keith D. Foote of Dataversity defines Data architecture as "A set of rules, policies, and models that determine what kind of data gets collected, and how it gets used, processed and stored within a database system."

The data architecture principles on which the entire framework is based considers data as an asset defined on pre-set parameters and is accessible, shareable, manageable, and can be secured. 

Enterprises deploy data architecture to primarily convert business needs into data and system requirements, align business processes with IT systems, and manage the complex flow of data and information within the organization. In a 2017 trends report, data architecture is labeled as both a business and technical decision, given the emergence of new business models and innovations that are increasingly being driven by data and innovation.

This brings us to the big question: Who builds this important Data Architecture? Data architecture is conceptualized and designed in alignment with business needs by a Data Architect. 

Who is a Data Architect? 

Data architects are IT professionals who are tasked with defining policies, procedures, models, and technologies that will be used to collect, organize, store, and retrieve information for the organization.

A data architect is an expert who formulates the organizational data strategy, including standards of data quality, the flow of data within the organization, and security of data. It's the vision of this data management professional that converts business requirements into technical requirements. 

As the critical link between business and technology, the demand for qualified data architects has been on the rise. 

A survey revealed that only 3.9% of data management professionals chose to be self-employed, while a whopping 96.1% of them were snapped up by organizations that wished to leverage data for tactical business advantage. The same survey forecasted that demand for data architects would intensify at the rate of 15.94% over the next few years. The Robert Half Technology 2020 Salary Guide pegged the average data architect salary at $141,250.

Did we get you interested in the role of a Data Architect? Let's discuss further with a detailed Data Architect job description, essential skills required to succeed in the role, and how to become a Data Architect.

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What Does a Data Architect Do?

According to DAMA International's Data Management Body of Knowledge, a Data Architect "provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture," 

A data architect understands the business needs, explores the existing data structure, and creates a blueprint for building an integrated framework of easily accessible, secure data aligned with business strategy. The data architect also defines the processes involved in testing and maintaining the database.

The titles Data Architect and Data Engineer are commonly mistaken and, worse, used interchangeably. But the role of a Data Architect is very unlike those of a Data Engineer. In this data engineer vs. data architect debate, while the latter design the blueprint of the data framework, the former puts this blueprint into action to build a data framework. 

A Data Architect takes into account all data sources concerning business operations and outlines a design to integrate, centralize, and maintain the data. On the other hand, a Data Engineer is responsible for building and testing sustainable Data Architectures for the organization for easy data search and retrieval. Data architects work in close collaboration with data engineers to build a sound data architecture.

What are the Responsibilities of a Data Architect?

The role of a data architect is that of a visionary leader in an organization. A data architect roles and responsibilities include:

  • Developing and implementing an overall organizational data strategy that is in line with business processes. The strategy includes data model designs, database development standards, implementation and management of data warehouses and data analytics systems.
  • Identifying data sources, both internal and external, and working out a plan for data management that is aligned with organizational data strategy.
  • Coordinating and collaborating with cross-functional teams, stakeholders, and vendors for the smooth functioning of the enterprise data system. 
  • Managing end-to-end data architecture, from selecting the platform, designing the technical architecture, and developing the application to finally testing and implementing the proposed solution.
  • Planning and execution of big data solutions using technologies such as Hadoop. In fact, the big data architect roles and responsibilities entail the complete life-cycle management of a Hadoop Solution. 
  • Defining and managing the flow of data and dissemination of information within the organization. 
  • Integrating technical functionality, ensuring data accessibility, accuracy, and security.
  • Conducting a continuous audit of data management system performance, refine whenever required, and report immediately any breach or loopholes to the stakeholders.

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What Skills Does a Data Architect Need to Possess?

Some of the must-have data architect skills include: 

  • Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques
  • Proficiency in data modeling and design, including SQL development and database administration
  • Understanding of predictive modeling, NLP and text analysis, Machine Learning
  • Ability to implement common data management and reporting technologies, as well as the basics of columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics.
  • Data mining, visualization, and Machine Learning skills
  • Knowledge of programming languages Python, C/C++, Java, and Perl

Besides, a data architect needs to coordinate and collaborate with users, system designers, and developers in their day-to-day functions. As such, soft skills like effective communication, team management, problem-solving, and leadership are highly desirable traits of a data architect. 

How to Become a Data Architect?

To be a Data Architect, the bare minimum qualification requirement is a bachelor's degree in either computer science, computer engineering, or a related field. The coursework should cover data management, programming, application design, big data developments, systems analysis, and technology architectures. 

If you are a fresh graduate aspiring to be a Data Architect, you can jumpstart with internships that offer exposure to network management and application design and proceed towards the role of Database Administrators. Working on your skills related to database management, data modeling, and data warehousing, you can gradually progress your career to a Data Architect's profile. 

Companies usually prefer a Master's Degree with several years of experience in data design, management, and storage work for senior positions.

While each of the technical skills required by a Data Architect is not taught in one single course, it makes sense to pick up relevant skills while on-job. Alternately, you can also take up additional certifications to equip yourself. 

Choose the Right Program

Program Name DS Master's Post Graduate Program In Data Science Post Graduate Program In Data Science
Geo All Geos All Geos IN/ROW
University Simplilearn Purdue Caltech
Course Duration 11 Months 11 Months 11 Months
Coding Experience Required Basic Basic No
Skills You Will Learn 10+ skills including data structure, data manipulation, NumPy, Scikit-Learn, Tableau and more 8+ skills including
Exploratory Data Analysis, Descriptive Statistics, Inferential Statistics, and more
8+ skills including
Supervised & Unsupervised Learning
Deep Learning
Data Visualization, and more
Additional Benefits Applied Learning via Capstone and 25+ Data Science Projects Purdue Alumni Association Membership
Free IIMJobs Pro-Membership of 6 months
Resume Building Assistance
Upto 14 CEU Credits Caltech CTME Circle Membership
Cost $$ $$$$ $$$$
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Gear up for one of the hottest jobs in the tech market currently - Data Architect or Big Data Architect. Join the next level Big Data certification courses and acquire competitive skills with Simplilearn's Data Science Certification Program. The program, designed and delivered in collaboration with IBM, will not only prepare you to ride the Big Data wave with in-depth knowledge of the Hadoop Ecosystem, big data engineering tools but will also give you hands-on experience in data modeling, ingestion, replication, and sharing, using trending technologies.

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