With data volumes growing exponentially and the data stack undergoing rapid innovation in various areas, companies struggle to keep pace. These data architecture trends will enable organizations to revolutionize their data management strategies.
To better manage the time and costs of such complex infrastructures, companies must adopt a fundamentally different approach to their data architectures: a federated and distributed paradigm. Most modern businesses need a robust data architecture that offers flexibility for the future and also meets today‘s requirements and realities in mind.
Here are a few data architecture trends that organizations need to consider in 2023 to optimize their data management:
Given that data movement is one of the most expensive things organizations can do, organizations should focus on moving the processing to the data rather than moving the data to where it can be processed.
No organization has one single platform and therefore, most organizations have many data sources they need to make sense of. Despite the push for decentralization, centralized data warehouses, data lakes, and lakehouses all have their benefits depending on the use case.
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A federated, service-oriented architecture provides the unified control plane needed to leverage these different data stores with high availability while more efficiently managings cost for the organization. As this only becomes more of the norm, data leaders need to showcase the need for this type of architecture and why this should be adopted sooner rather than later.
“On the software side of data management, open source will continue to be critical, as open source has been shown to decrease the total costs of the data stack by up to 40%. The cloud is the center of gravity for data analytics, with many companies embracing cloud or multi-cloud postures. As these innovations continue to arrive in the market, enterprises will need to be keen on these different dynamics and be ahead of how this will impact their business,” says Jess Iandiorio, CMO at Starburst.
A tremendous surge in demand for data democratization forces organizations to revamp their data architecture frameworks. Embracing new data architecture is a constant journey that businesses have to undergo. Companies that aim to have a successful enterprise Data framework must make strategic changes based on technology rather than business needs and objectives.
The impact of best data lakehouses and catalogs is tremendous, and businesses can get the most out of their data gathered. Changing the data architecture of the entire organization cannot be done overnight and needs to be gradually adopted through a trial-and-run approach.
One of the crucial Data Architecture trends in 2023 that DataOps teams need to focus on is making their data more accessible irrespective of where it is at rest. With various options like on-premises, public, hybrid, or multi-cloud environments, organizations do not have to think about data computation and storage costs. Instead, in 2023 DataOps teams can focus on offering more data accessibility, quality, and governance.
With a surge in adopting different automation systems with Artificial Intelligence (AI) and Machine Learning (ML) to evaluate massive data pools, businesses can leverage data fabrics to merge traditional data sources with modern capabilities to get the desired results.
Data fabric is one of the most effective ways that enables organizations to process and evaluate data from multiple sources that are both physically or logically different. Embracing to data fabric model DataOps teams will be able to get a holistic view and usage of data stored on on-premises systems, multiple clouds, social media, and IoT devices on centralized objects. Many Data owners and analysts are concerned about whether the data is set in the proper context.
Data analysts can enhance their data fabric with metadata to better understand their data spread across disparate systems. Metadata adds more context to the data adding more meaning to it. Moreover, it helps to identify the relationship with other data sources enabling organizations to extract more insights from the data. Data fabric is one of the top data architecture trends that DataOps teams must consider in 2023.
Data democratization puts data ownership on the teams that generate the data. Embracing a Data Mesh architecture enables organizations to enforce centralized data governance policies to avoid siloing the data. DataOps teams that want to embrace Data Mesh must understand that it’s a structural change that needs a mind shift trough out the organization to manage data efficiently.
Domain Ownership, Data as a Product, Self-Serv Data Infra, and Federated Governance are the four foundations of data mesh architecture. One of the significant data architecture trends witnessed in 2023 would be Data Mesh.
Also Read: Enterprise Architecture: Top Strategies for Succeeding in Modernization of Enterprise Architecture
Businesses around the globe are generating data exponentially from the internet of things (IoT) and industrial internet of things (IIoT) devices. The traditional data management models cannot manage the vast amount of data generated centrally. Hence organizations that aim to have decentralized data need to implement robust data analytics and business intelligence tools to build edge applications.
This approach helps organizations to evaluate their data in real-time and offers more valuable insights into business decision-making. Businesses with this data management approach can identify data siloes or irregularities in milliseconds. Embracing edge computing allows DataOps teams to expedite the speed of analytics. Organizations can improve their data architecture by enhancing their analytics capabilities.
Embracing these top data architecture trends can help organizations to extract more value from their data generated from all the channels.
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Nikhil Sonawane is a Tech Journalist with OnDot Media. He has 4+ years of technical expertise in drafting content strategies for Blockchain, Supply Chain Management, Artificial Intelligence, and IoT. His Commitment to ongoing learning and improvement helps him to deliver thought-provoking insights and analysis on complex technologies and tools that are revolutionizing modern enterprises. He brings his eye for editorial detail and keen sense of language skills to every article he writes. If he is not working, he will be found on treks, walking in forests, or swimming in the ocean.
