![]() ![]() According to Dataversity, good data architects have a solid understanding of the cloud, databases, and the applications and programs used by those databases. Most data architects hold degrees in information technology, computer science, computer engineering, or related fields. Typically, data architects learn on the job as data engineers, data scientists, or solutions architects and work their way to data architect with years of experience in data design, data management, and data storage work. How to become a data architectĭata architect is an evolving role and there is no industry-standard certification or training program for data architects. ![]() Data scientists are experts in applying computer science, mathematics, and statistics to building models. Data engineers assist data architects in building the working framework for data search and retrieval.Īccording to Dataversity, t he data architect and data scientist roles are related, but data architects focus on translating business requirements into technology requirements, defining data standards and principles, and building the model-development frameworks for data scientists to use. According to Dataversity, data architects visualize, design, and prepare data in a framework that can be used by data scientists, data engineers, or data analysts. The data architect is responsible for visualizing the “blueprint” of the complete framework that data engineers then build. Data architects and data engineers work together to visualize and build the enterprise data management framework. In some ways, the data architect is an advanced data engineer. The data architect and data engineer roles are closely related. Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors.Defining data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition. ![]()
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