Data occupations are growing in importance and popularity across the globe, owing to the fact that “data” has become the new currency of the data economy. The Pandemic provided the impetus for global enterprises to expedite their digital transformation, and now, the major market differentiation is an enterprise’s data infrastructure readiness. This data infrastructure consists of systems, procedures, tools, and appropriately skilled personnel. Both data architects and data engineers are in greater demand than data scientists in today’s industry.
Together, the data architect and data engineer conceptualise, visualise, and then design an Enterprise Data Management Framework. The data architect visualises the entire framework and develops the blueprint upon which the data engineer builds the “digital framework.”
Data engineering is a relatively new subject that originated from traditional software engineering. Recent Enterprise Data Management trials have established beyond a shadow of a doubt that these data-centric software engineers are require to collaborate with data architects in order to construct a solid Data Architecture. Between 2018 and 2020, data engineers increased by approximately 122% in response to a significant data industry need.
Two Complementary Job Titles
Data architects have the ability to “organise the chaos of data.” Without this, massive amounts of business data are meaningless. The “blueprint” for an organization’s data management is create by data architects. Each Data Science team requires a data architect to visualise, design, and prepare data in a way that data scientists, engineers, and analysts can use it. Frequently, these specialists hold academic degrees in a computer-related field, have years of experience developing systems or applications, and possess extensive knowledge of information management.
Typically, an entry-level data professional must endure several years of arduous data design, data management, and data storage labour before being consider for a data architect post. According to Payscale.com, data architects earn a median annual pay of $111,139.
On the other hand, data engineers work alongside data architects to create a framework for data search and retrieval that scientists and analysts can use in the future. In most situations, data engineers gain their credentials through one of the several certificate courses offered by professional training suppliers. These highly qualified engineers are responsible for developing and testing maintainable Enterprise Data Architectures in the Big Data environment. The median annual income for data engineers is $90,286.
Together, data architects and data engineers implement a usable Data Architecture for the enterprise’s Data Management teams. Despite their complementary positions in the realm of Data Science, these two professions’ daily job functions might be extremely different.
Updates to the Skills Required of a Data Architect vs. a Data Engineer in 2021
The following are some actions that a prospective data architect can take in 2021 to become a data architect:
1. Earn a bachelor’s degree in computer science, engineering, or a closely related field.
2. Acquire some of the technical abilities listed below:
Exploration of data
Automated learning
Visualization of data
Predictive modelling, natural language processing, and text analysis
Software for the user interface and enquiry (e.g. IBM DB2)
Software for application servers (e.g. Oracle)
Refer to How to Be a Data Architect in 2021 for a comprehensive list of essential technical skills.
The following are some critical business abilities for data architects:
Ability to solve problems
Proficiency in communicating
Skills in team development and management
Industry expertise
3. Optional certificates for advancement in data-related careers:
Professional Certified in Data Management (CDMP): These qualifications, developed by the Data Management Association International (DAMA), lend legitimacy to any data architect’s résumé. The CDMP is available at four different levels. Details are available at the aforementioned link.
Big Data IBM Certified Data Architect
The following are some actions that a prospective data engineer can take in 2021 to become a data engineer:
Although many data engineers enter the field with an undergraduate degree in science, mathematics, or business, an ambitious professional will need to take additional measures to flourish and grow in data engineering. Several of these steps are list below:
Acquire expertise in computer engineering, data analysis, and big data.
Additional certifications in engineering or big data may be obtain.
Consider pursuing additional education in computer science, computer engineering, applied mathematics, physics, or a similar discipline.
Contrasting Workdays of a Data Architect and a Data Engineer
Data architects frequently apply their hands-on expertise in a range of Data Administration domains, including data modelling, data warehousing, database management, and ETL tools. Certain programmes need qualified applicants to demonstrate knowledge in particular areas, such as data lineage or data replication.
The data architect’s function has altered somewhat over time. The introduction of the data engineer has enabled the architect to shift focus away from data framework construction and toward data visualisation. Due to extensive understanding of database design and query languages like as Spark or NoSQL, the data architect has grown into a “visionary” in recent years.
The distinction between Data Analyst, Data Engineer, and Data Scientist implies that a data architect is simply a more experienced data engineer. The data engineer utilises the data architect’s corporate data blueprint to collect, store, and prepare data in a framework from which the data scientist and analyst may work. This strategy frees the data scientist or data analyst from time-consuming data preparation tasks. This is allowing them to focus on data exploration and analysis.
While the data architect and data engineer may develop similar or identical competence in database architecture over time, they employ this expertise differently. While data architects provide expertise and direction on how to manage diverse data sources from disparate databases. Data engineers take the architect’s vision and create and maintain the enterprise data professionals’ Data Architecture.
A fascinating contrast between the two positions depicts the data architect as someone who, through extensive database experience, can anticipate how changes in data acquisitions will affect data utilisation. In comparison, the data engineer, who possesses extensive knowledge in software engineering, can design and maintain a data system that compensates for those changes.
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