Behind every business decision, there’s underlying data that informs business leaders’ actions. As the market landscape across verticals from financial services to healthcare and manufacturing grows increasingly competitive, those decisions need to happen ever faster and to make them, businesses need to rely on data to reveal insights quickly, as near-real-time as possible. Delivering the most business value possible is directly linked to those decisions and the data and insights that inform them.
It’s not enough for businesses to implement and maintain a data architecture. The unpredictability of market shifts and the evolving use of new technologies means businesses need more data they can trust than ever to stay agile and make the right decisions. To tackle that goal, data and analytics leaders need to adopt modern data architectures that deliver greater flexibility and visibility and serve as a blueprint for accelerating the process of gathering insights and value from data.
Modern Data Architectures are Ready for the Future
There is an important distinction between data architecture and modern data architecture. Data architecture is what defines the structures and systems within an organization responsible for collecting, storing, and accessing data, along with the policies and processes that dictate how data is governed. When we talk about modern data architecture, there are several unique benefits to this kind of approach. A modern data architecture simplifies data access across organizations and unlocks data from their silos, making it easier to know and understand that data. This ensures that the right, trusted data is able to be used to feed AI and analytics effectively.
Modern data architectures deliver key functionality in terms of flexibility and scalability of data management. This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses. They also incorporate functionalities like data processing, data integration, and data governance as part of the overall structure for data systems.
Making the Leap from Data Architecture to Modern Data Architecture
There are a multitude of paths businesses can take to successfully implement a modern data architecture. Among those paths to implementation, here are three key approaches to strengthening and modernizing data architecture:
Data Lakehouses: This offers businesses a combined approach, bringing together key pieces of data lakes and data warehouses to deliver the flexibility of a data lake with the performance of a data warehouse. A data lakehouse eliminates the need for data duplication and synchronization, helping keep costs down while building trust with a single source of truth.
In particular, open data lakehouses are well-suited for a modern data architecture, delivering self-service access to analytics that help organizations generate insights quickly and manage data on public or private cloud.
Data Fabric: This is a type of data architecture intended to help automate the unlocking of data sources at scale while also providing self-service access to the data that still adheres to both governance and data access rules. In a hybrid cloud environment, data fabric helps organizations bring all of that disparate data together into one single source and gives businesses a single point of access for data stored in multiple systems without exposing data to undue compliance risk.
Data Mesh: A data mesh involves decentralization of data and analytics where each domain is fed by its own data fabric and has its own data lakehouse. The idea is to create a “mesh” of data products connected to various parts of an organization versus having a central repository of data and analytics controlled by an individual IT team that is responsible for the needs of multiple domains.
The visibility, accessibility, and insights that derive from a modern data architecture feed directly into a business’s ability to adapt quickly, handle change, and make well-informed decisions based on real-time data—all of which play an important part in future-proofing data infrastructure for the long term.
Learn more about how Cloudera can help you achieve a modern data architecture.
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