With the onset of the pandemic, global businesses began to realize the power of operational efficiency, scalability, and growth. With this realization came the crucial need to shift their data centers to managed service ecosystems – cloud platforms in all their variations. However, locating a suitable data center partner on the cloud has not been an easy task for most businesses, especially for medium-sized or smaller organizations with severely restricted budgets. The safety and sustainability of your business depends on the quality of service your business receives from the service provider. Below, let’s review the dominant Data Architecture trends to expect this year.
The cloud has been a game changer for the Data Management business, especially during the pandemic. With more and more organizations swiftly moving to remote working and work-from-home models, the need for distributed and managed data centers, and secure but democratic data access became paramount. With digital business models rapidly gaining popularity, it is estimated that “60% of mainstream organizations will elect a composable enterprise as a strategic objective.”
Other innovations such as DataOps, data security, and more are likely to accelerate digital transformation of global businesses in 2023. A major trend this year is the widespread adoption of multi-cloud data infrastructure. Another major trend is a “standardized data stack” to reduce the diversity of technologies and tools. While organizations favor data democratization, they are also concerned about Data Quality, and hence the move is toward automated Data Governance.
For those businesses still on the lookout for an ideal data center partner, here is a handy guide to technology trends to help you make a decision. Next, with the wide proliferation of 5G networks, edge computing is here to stay and rule the IoT data. Edge has many benefits – faster processing, lower costs, accurate results, and continuous insights. Edge computing will continue to rise at least till 2025 and likely beyond.
Data Architecture for Decentralized Data
The rising demand for “democratized data” is forcing enterprises to reinvent their Data Architecture frameworks. According to industry expert Donna Burbank, Data Architecture forms a “core component of overall Enterprise Architecture.”
As author Eric Carr explains, “Implementing new data architecture is not a linear progression but an ongoing experiment with surprises, failures, and problems to solve.” He believes that for an enterprise Data Architecture to succeed, architecture-related decisions should not be driven by technology but rather by “business objectives and needs.”
Data Architecture impacts Data Management to such an extent that it leaves far-reaching consequences on the human beneficiaries. Architectural changes cannot be brought overnight – they have to be gradually adopted and implemented through trial-and-error exercises involving human staff.
The central focus in Data Architecture in 2023 will be “data access,” regardless of where the data resides – on-premises, public, hybrid, or multi-cloud. Businesses are no longer worried about data computation and storage costs, but they are still worried about the speed of data access, Data Quality, and Data Governance.
Top Data Architecture Trends for 2023
Though many of the Data Architecture trends mentioned below began to surface in 2022, they will mature and dominate this year’s business landscape:
- All data architectures will be designed for cloud platforms in 2023 – especially hybrid and multi-cloud environments. This trend will directly benefit businesses looking to drastically reduce their infrastructure costs while leveraging big data analytics for competitive intelligence.
- The need for superfast networks will necessitate reengineered Data Governance architectures in 2023. The focus of Data Architecture frameworks will shift from compute and storage issues to data security and governance issues.
- The growing demand for decentralized data access will favor the ongoing shift toward data mesh and data fabric from traditional data lakes and warehouses. This trend may experience a spike in 2023.
- The year 2023 will witness more collaborations between domain and data (IT) teams spinning out business-friendly data architecture solutions.
- As Data Management becomes more democratic, data access governance (data observability) will take the center stage in Data Management systems.
- Data catalogs will continue to reign throughout 2023 to enable discovery of new data products and services in data meshes.
- The data architectures developed in 2023 will be AI-ready in the sense that a lot of critical activities within the architecture framework will be semi- or fully automated with AI and ML tools.
- With IoT data devices on the rise, large volumes of streaming data will certainly become a hot topic for data architectures in 2023.
- With domain teams taking charge along with their IT colleagues, data-powered business decisions will arrive faster and with more accuracy.
- The data engineer will become an important member of the data architecture team. The role of the data engineer will catapult into a data steward / Data Quality assurance role in the data democratic, no-code data environment.
Data Architecture Reinvented
The cloud platform being easily accessible, secure, and managed, it is the obvious choice for any business for Data Management operations. So in 2023 and hopefully later, data architectures will be designed with the cloud in mind. As the cloud technology revolution gains momentum, more organizations of all shapes and sizes will move their data centers to the cloud.
Managed data centers offer a lot of benefits to business clients – enhanced compute and storage, access to many tools, real-time analytics, streaming data processing, and self-service data visualization. In the near future, the growth of web, SaaS, and mobile applications will only enhance the business interest in streaming data.
While augmented Data Management and embedded analytics will remain crucial, in-demand features of a managed data center, all Data Architecture teams will have to keep these in mind while designing the architecture blueprint. For example, with embedded, real-time analytics in a data fabric, organizations will have access to instant insights and decisions, and that too, at a significantly low cost. This will open up tremendous opportunities for consumer behavior analytics for improved marketing performance.
Fuente: www.dataversity.net
