What does a “data architect” do?
In terms of handling and structuring a company’s data, the responsibility of creating the plans lies with a data architect.
With their expertise in setting up the technical and regulatory framework necessary for the company to make the most of its data, data architects function as a bridge between the business operations and IT.
In order to excel in their industry, data architects must have a thorough comprehension of both business and technology. They must evaluate a company’s data architecture, data governance, and data technology to identify opportunities for improvement and design and implement plans to tackle them.
In addition, they must possess exceptional communication abilities, which will allow them to establish a mutual understanding between business and IT, articulate strategic demands, and promote the utilization of data within the organization.
The key responsibilities of a data architect include:
- Converting business needs into technical requirements
- Establishing policies and procedures for organization-wide data storage, consumption, integration, and management
- Developing Data Models
- Creating standards and guidelines for data definition
- Setting up Architectural Standards
- Defining and Managing Data Flow
- Collaborating with diverse industries, stakeholders, and partners
- Promoting a data-driven culture through internal communication and advocacy
Analysis and Modeling of Data
The process of evaluating and defining the data sets and their relationships within your organization’s data infrastructure.
To establish an efficient analytics and business intelligence strategy, it is imperative to have a dependable data modelling base. Defining all data and their relationships in advance can significantly streamline the data analysis process.
In order to fulfill their responsibilities, a data architect must have expertise in the latest modelling techniques or be capable of acquiring such skills rapidly through exposure to relevant case studies. Familiarity with PowerDesigner, Enterprise Architect, and Erwin, which are among the most prominent modelling tools, is also advantageous.
It is imperative to have a solid grasp of SQL coding and database management. Candidates should also possess expertise in NoSQL databases, data visualization, working with unstructured data, as well as traditional data management techniques.
Your data will be managed within a framework of data governance that you have established. This framework includes international data standards, processes, procedures, roles, and responsibilities, and provides a structure to support the development of data excellence.
Effective data governance involves the participation of various stakeholders, including the data architect. Therefore, candidates for the position of data architect should exhibit proficiency in the three fundamental components of data governance: people, process, and technology. Examples include:
People:topics related to team composition, skills, data ownership, accountability, and communication
Process:operational structure, informational standards, privacy, and performance measurement
Technology:Infrastructure, data software, and cloud computing
If you have high aspirations for your data architecture, having familiarity with contemporary data governance methods that prioritize federated approaches instead of conventional, highly centralized governance strategies could be beneficial.
In today’s landscape, being conscious of all relevant legal and compliance obligations is essential as nonconformity could lead to severe repercussions.
Having a solid grasp of the interdependent relationship among various governance systems in an organization and how data governance fits into the broader context is crucial.
Analysis of the Numbers
The effectiveness of a data framework is determined by its capability to analyse data and derive actionable insights from it.
A competent data architect should have expertise in common analytics methods and be well-versed in popular software tools like Microsoft Power BI and Tableau. In addition, it is crucial for them to possess robust technical data skills, including proficiency in database languages (such as SQL) and statistical programming languages (like R or Python), as well as a thorough grasp of statistics.
Candidates must exhibit a deep understanding of the System Development Life Cycle, possess practical experience in implementing project management strategies, and have a lucid comprehension of requirements, design, and testing methodologies.
Progressing Technology with Data Innovation
In the digital era, data lies at the heart of all technological advancements. It has emerged as a key distinguishing factor in the market for many organizations that are grappling with declining profits and mounting costs.
The ideal candidate for the Data Architect position must have a profound understanding of data’s importance to contemporary innovation and possess the ability to formulate a data infrastructure that fosters creativity rooted in data.
In order to stimulate prompt innovation, techniques such as DataOps and Product Thinking, along with new technological frameworks like the Data Mesh, prove to be advantageous.
Data standards aim to maintain uniformity in the use of information across multiple platforms and applications.
Data standards play a pivotal role in facilitating information sharing within an organization. A Data Architect should devise a custom set of data standards consisting of elements like data type, identifiers, schemas, vocabulary, formats, etc.
Additionally, they must comprehend the significant data regulations such as GDPR, HIPAA and PCI DSS that your standards must adhere to.
They must be capable of promoting excellence in data standards through workshops and awareness programs across the organization, since this is vital to the success of any data projects.
The Data Architect will aid in the development of metadata standards that facilitate the organization-wide access, searchability and shareability of data. This position will serve as the connecting element that unifies the company’s data architecture.
To understand the diverse applications and end-users of metadata, they must possess extensive knowledge of the entire data lifecycle.
The team must have the ability to gather and classify metadata in accordance with global standards, employing metadata management systems like Alation, Oracle, SAP, and subsequently implement the strategy throughout the organization.
Proficiency in Business
Embracing a Business Point of View and a Case-Based Method
A data architect’s principal duty is to reconcile contrasting business and technological requirements.
It is crucial for the staff to have an extensive comprehension of the company’s standards and protocols. Neglecting to do so may cause the formation of data architectures that are not customized to the business’ needs, instead of acting as innovative solutions.
It is effortless to focus solely on the execution of data technologies, without initially assessing how they can aid in accomplishing business objectives. As a data architect, it is imperative to give priority to the desired outcomes above all else and to utilize technical proficiency merely as a means of achieving these objectives.
Data architecture plans must be customized to meet particular business requirements, in order to minimize inefficiency and produce tangible business outcomes.
Data architecture designed to Meet Business Requirements
The selected candidate will work in close collaboration with significant stakeholders from both the business and the technology sectors, in order to comprehend the company’s demands and successfully convert those necessities into data architecture, covering areas such as data streams, integrations, transformations, databases, and data warehouses.
For optimal outcomes, it is advisable to employ Agile methodologies to incrementally perfect designs and make adaptations to guarantee that they fulfill both the company’s and the end-users’ requirements.
Acquiring a practical understanding of Design Thinking and/or Product Thinking would be advantageous, as they perceive data as a service to be delivered to internal customers and enhanced based on their responses. These methods are helpful in coordinating technology life cycles with business demands.
Data Architects can be immensely beneficial to both information systems and businesses. It is imperative to elucidate concepts concisely and with clarity, to derive the maximum benefit from these services.
On one hand, it is incumbent on them to clarify to the business what is feasible and what is not feasible, concerning the organization’s technological capabilities.
Additionally, they must be capable of comprehending and conveying business demands to technical teams in a manner that guarantees their work supports the company’s overall objectives.
Applicants should exhibit superb presentation abilities, the skill to advocate persuasively for the significance of data to stakeholders, and the proficiency to effortlessly communicate between technical and non-technical stakeholders.
An excellent data architect strikes a fine balance between business acumen, interpersonal and teamwork skills, and technological expertise.
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