Yes, in the new era of big data and data science. It is critical for enterprises to have a centralized data architecture. It is aligned with business processes that scale with business growth and thrive with technological advances.
Data architecture is relatively new compared to information, system, and software architecture.
A successful data architecture clarifies every aspect of data, enabling data scientists to work with reliable data efficiently and solve complex business problems.
It also prepares an organization to quickly take advantage of new business opportunities. In our post this time, we will discuss data architecture and why it is essential in a business in more detail and thoroughly.
What is Data Architecture
Then, what is meant by data architecture? Yes, as we have explained above, this is better known as data architecture in global terms. This is a set of rules, policies, and standards governing data collection based on our conclusions referring to the Technopedia Site.
Data architecture is used by data architects. This involves mapping and visualizing data models in an easy-to-understand way.
The goal of architects is to manage that flow by creating a series of interconnected, two-way data pipelines that serve multiple business needs.
The pipes are constructed using data objects from data snapshots, data enhancements, data views, reference data, master data, and flat tables, which are subject-oriented.
Data objects or data objects serve as building blocks that are continuously reused, reused, and refilled to ensure a stream of relevant, high-quality, high-quality data to the business.
Who is Data Architect?
Then, there is also the term data architecture or data architect. This individual is responsible for designing, creating, deploying, and managing an organization’s data architecture.
The data architect defines how data will be stored, consumed, integrated, and managed by different data entities and Information Technology (IT) systems and any applications that use or process the data in some way.
A data architect ensures that an organization follows formal data standards and that its data assets align with the specified data architecture or business goals.
Typically, a data architect by profession maintains a metadata registry, oversees data management, and optimizes databases, all data sources, and the like.
Data architects or data architects are typically skilled in logical data modeling, physical data modeling, data policy development, data strategy, data warehousing, data query languages, and identifying and selecting the best systems to handle data storage, retrieval and management.
Data Architecture Function
A solid data architecture or architecture is a blueprint that helps align your company’s data with its business strategy.
Data architecture guides how data is collected, integrated, enhanced, stored, and delivered to the businesses that use it to do their jobs.
This helps make data available, accurate and complete so that it can be used for business decision-making.
Then regarding its function, you need to know that all kinds of business fields use data architecture to:
- Prepare organizations strategically to rapidly expand and take advantage of the business opportunities inherent in emerging technologies.
- Translate business requirements into data and system requirements.
- Facilitating the alignment of information technology and business systems.
- Manage the delivery of complex data and information across the enterprise.
- Act as an agent for the transformation of change.
- Describes the flow of information between people (users) and processes in a business.
How Does Data Architecture Work?
In discussing the meaning of data architecture, of course, this must be distinct from how the principles and their processing work, right?
As we’ve explained above, data architecture is a broad term that refers to all processes and methodologies. It deals with data at rest, data in motion, and data sets and how these relate to the methods and applications that depend on data.
This includes the primary data entities, types, and sources that are important to an organization’s data sources and management needs.
In the process of how it works, the data architecture (data architecture) is usually designed, created, used, and managed by an architect or data architect.
Data architecture in an organization or company consists of 3 (three) layers or processes that differ in how they work, namely:
1. Conceptual model (business); Includes all data entities and provides a conceptual or semantic data model.
2. Logical model (system); That is, it defines how data entities are linked and provide a logical data model.
3. The physical model (technology); This Is to provide data mechanisms for specific processes and functionality, or how the actual data architecture is implemented in the underlying technology infrastructure.
Data Architecture Technical Thing
When discussing Data Architecture, one must answer which is better: On-Premise or Cloud? Before arriving at the answer to this question. It’s a good idea to first discuss what On-premise and Cloud are.
On-Premise is internal infrastructure management, starting from hardware, software, network, and so on.
The advantage of on-premise is the flexibility in managing the security of the infrastructure, how data is stored, organized, and so on. Since the server is internal, you also don’t have to continue to need an internet network because the server can be accessed via a local network or intranet.
The downside is that it requires a significant investment. Starting from the physical things that are prepared but also need experts who can manage the infrastructure.
For companies whose IT implementation still needs to be mature (they need more human resources, hardware, or even room to store servers), the consequence is that at the beginning of implementation, we have to invest everything needed so that it can run well.
While the Cloud here is one of the models of cloud computing or cloud computing, an internet-based data storage service.
In terms of the advantages of using the Cloud, compared to data storage centers that are on-premise, it offers several benefits. Using the Cloud allows companies to cut significant investments.
Even though, from a budget point of view, Cloud is more profitable, one thing that needs to be considered from this implementation pattern is that we still need qualified human resources for the required software configuration, security issues, etc. In addition, one must also consider whether this implementation will work optimally when it has to manage large amounts of data.