Data is everywhere: We’ve left the days of terabytes behind, generating petabytes of data every day. And that’s good news, because data is one of the most valuable assets an organization can have, especially when embarking on a digital transformation. Any successful transformation provides actionable insights, and for that to happen, organizations need to optimize their voluminous data.
As Gartner says in Why Data And Analytics Are Key to Digital Transformation, “Leading organizations in every industry are wielding data and analytics as competitive weapons…. By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.”
The huge significance of data presents complex challenges: Organizations need to integrate multiple data sources, use data wisely, and govern the data, regardless of its location and format. A new data architectural approach, known as data fabric, is instrumental in meeting these challenges.
What is a data fabric?
A data fabric is an architecture and a set of data services that give consistent capabilities to data residing in a hybrid (on premise and multi-cloud) environment. A data fabric facilitates a seamless digital transformation by integrating data that is siloed across multiple endpoints and providing data visibility, control and insights.
Data residing in hybrid environment needs to be consistent. Thus, you need data fabric now more than ever. Here is how to leverage the technology.
The core elements of a data fabric
- Data integration: Defined rules integrate and orchestrate all data residing in silos. Data flow is well coordinated and easy to manage.
- Active metadata: Moving from passive to active metadata is key to a data fabric. Passive metadata is technical only—schemas, data types, models, and the like. Active metadata includes technical data, but it also encompasses business, operational and relational metadata.
- Knowledge graphs: One of the most important elements while dealing with discrete, multiple, organization-wide data sources, knowledge graphs help establish relationships among data sets and support seamless integration of data sources.
- Data governance: A successful data fabric demands centralized governance to ensure that all data sources comply with global corporate policies.
Data fabric in a multi-cloud ecosystem
To reap all the benefits of performance and cost optimization, at least 66 percent of all large enterprise IT organizations employ a hybrid cloud or multi-cloud infrastructure. However, these infrastructures make operations much more complex. Typical challenges of a multi-cloud ecosystem are data silos, data latency and data portability.
A multi-cloud infrastructure requires new data management design, new policies and, most importantly, a new data architecture that enables seamless integration and pollination of data while managing data sovereignty.
Data fabric: turning concept into reality
In any organization’s digital journey, a data fabric is a powerful engine of modernization and innovation. In other words, it turns the concept of a seamless IT environment into reality. In addition to simplifying and integrating data, it couples data on multiple clouds for consumption by multiple applications on a single orchestration layer. It reduces the number of boundaries in multi-cloud ecosystems, catalogs data into logical groups, normalizes data in a consistent format for easy consumption and standardizes data management to allow multiple end users to gain agile access.
Let’s look at a specific scenario. Imagine a multi-cloud ecosystem with two hybrid clouds—Azure and AWS. Azure provides data consumption and transformation, AWS provides data ingestion and a BI tool (say, Tableau) provides analytics. In this scenario, a data fabric can enable multiple applications to access data from the cloud and seamlessly create a unified view of data.
Benefits of data fabric in a multi-cloud ecosystem
Operational benefits of a data fabric include:
- Data management: Drives business agility by managing multiple complex data ecosystems simultaneously across on-premise, cloud and hybrid environments
- Data orchestration: Integrates multiple clouds for external databases, business logic, masking, parsing and streaming
- Rapid data privacy compliance: Configures, manages and audits data subject access requests (DSARs) associated with GDPR and other data privacy regulations
- Comprehensive data governance: Manages data quality and reliability in accordance with policies and activities that established the infrastructure
Data fabrics optimize business transformation
In hybrid and multi-cloud operating environments, which are gaining increasingly more favor at many organizations, a data fabric can optimize data more efficiently than other architectures. It generates business insights by analyzing all data without being hindered by boundaries between multiple cloud infrastructures and platforms. Data fabric principles allow full leverage and governance of data across the enterprise, increasing productivity and profitability.
That’s business transformation at its best.