A data fabric applies continuous analytics to existing, discoverable, and inferred metadata assets to help design, deploy, and use integrated and reusable data across all environments, including hybrid and multi-cloud platforms. This blog aims to help you to understand the basic framework and best practices of a data fabric strategy along with some interesting use cases. Let’s dive in.
What Is a Data Fabric?
A data fabric is a unified architecture that uses data to provide consistent capabilities across endpoints in a hybrid multi-cloud environment. A data fabric improves visibility, access, and control by establishing standardized data management practices. Most importantly, it creates consistency, allowing data to be used and shared throughout your environment.
Data from various sources and types are combined to form a comprehensive single virtual basis. A data fabric architecture enables frictionless access and data sharing across a distributed infrastructure regardless of the application, platform, or storage location.
Data fabric architecture simplifies analysis, particularly when combined with AI and machine learning, and has become a primary tool for many organizations in converting raw data into usable business intelligence. Gartner named data fabric the top strategic technology trend for 2022, claiming that it can reduce data management efforts by up to 70%.
Advantages of Using Data Fabric
The following are three notable advantages of data fabric:
- A self-service data source that is unified
- Governance and security automation
- Data integration that is automated
A self-service data source that is unified
Data fabric combines data from multiple sources into a single unified source, making it easier to discover, process, and use data. It democratizes data by making it available to users who require it. Data is accessible to anyone who has been granted access based on access policies and controls. According to the 2021 Forrester Total Economic Impact, commissioned by IBM, the potential ROI of using a data fabric for a unified, self-service data source is more than 450%, providing a $5.8 million benefit to enterprise organizations.
Governance and security automation
Localized governance and security can continue to exist. Companies can stay in compliance and reduce the risk of data exposure by implementing automated data governance and security rules. This enables you to enforce specific governance and security policies regardless of where data is accessed. At the same time, you can develop comprehensive data management policies for enterprise-wide governance and security.
Data integration that is automated
Data scientists and engineers can significantly reduce manual workloads by automating (and augmenting) data integration tasks. Optimized data integration speeds up data delivery and occurs in real-time, ensuring that data is always in sync.
Read more on, Making Something Big Out of Big Data
The value proposition of data fabric in a multi-cloud environment
Data Fabric architecture is instrumental in IT environments with dynamic data workloads distributed across geographically dispersed infrastructure systems.
Run a true hybrid cloud
When businesses invest in cloud storage and infrastructure, they consider cost, security, availability, scalability, and service requirements. These specifications change over time, forcing them to:
- Change vendors
- Investigate various cloud models as viable alternatives.
Data Fabric enables organizations to overcome technical challenges in managing diverse data storage and infrastructure deployment portfolios. Customers can take advantage of the flexibility to run mission-critical data-driven IT services, apps, storage, and access to various hybrid IT infrastructure resources based on changing technical and business requirements. On the other hand, cloud vendors tend to lock customers into their service, making data migration an expensive and challenging task for their customers.
Cloud computing transitions that are seamless
Data Fabric is intended to reduce disruptions caused by switching between cloud vendors and compute resources to process data stored in different locations. As a result, Data Fabric significantly reduces time to insights. Organizations can benefit from faster insights in the following ways:
- Identify patterns within the data
- Understand trends
- Make decisions proactively
Better decisions enabled by improved computational performance across all data channels would allow businesses to outperform their competitors while making the most of their data investments.
Future-proofing and the ability to evolve
Data Fabric enables organizations to adapt their infrastructure in response to changing technological needs. This helps your company to facilitate the connection of disparate infrastructure endpoints to a consolidated and unified data management framework. Organizations do not need to be concerned about the exact location of data. Suppose a startup invests in a low-cost cloud storage solution until the company gains traction and requires highly available storage capacity later. In that case, it can use the flexibility that Data Fabric provides to choose infrastructure environments that best fit the nature of data and the organization’s business requirements on an ongoing basis. The data management functionality will be available across all infrastructure deployments, allowing organizations to future-proof their data investments.
Why Use Data Fabric?
Data fabric enables businesses to maximize the value of their accumulated data across a local, hybrid cloud, and multi-cloud environment. A data fabric improves business, management, and organizational practices by modernizing storage and data management.
Automated pipeline management processes data quickly and efficiently, resulting in significant time savings. Users can also gain a real-time, 360-degree view of their data with automated pipeline management. A data fabric, for example, provides a holistic view with access to every data point, whether users want to understand their customers or supply chains better. Data fabric also saves money by lowering the total cost of ownership (TCO) of scaling and maintaining legacy systems rather than incrementally modernizing them.
Data Management Efficiencies
Data processing, cleaning, transformation, and enrichment are all time-consuming and repetitive tasks. Much of this burden is alleviated by automating data preparation. A well-designed architecture enables organizations to store data in the most efficient and cost-effective location while maintaining access. Because data can be stored on-premises, in multi-cloud, or hybrid environments, a well-designed data fabric architecture can also support significant scale.
Read more, Power BI Dashboards: Eight Practices Every Enterprise Should Know
A data fabric creates a semantic abstraction layer capable of translating data complexity into simple business language. Data is more useful to those who have little data training and experience.
Data Fabric Strategy in Action: Use Cases
A data fabric’s most common use case is creating a virtual centralized business management database. Distributed data sources remain accessible for local or regional use and are accessible to larger organizations. Organizations with a distributed workforce or regional segmentation frequently choose this approach, which allows for centralized data access, coordination, and management. Another everyday use case is when there is a merger or acquisition. A data fabric strategy can unify disparate sources by bringing information from the acquired company into the virtual data store without replacing legacy architecture. While creating unified and harmonized data always requires effort, a data fabric will enable seamless and centralized data access within and across the enterprise.
Artificial Intelligence and Machine Learning
AI is based on robust and high-integrity data, but models are only as good as the data fed to the algorithms. A data fabric architecture provides data scientists with the comprehensive and integrated data they require for efficient data delivery. Because so much of machine learning revolves around data logistics, a data fabric is the best solution for managing data complexity.
Putting a Data Fabric Strategy in Place
A complex and diverse data ecosystem emerges as remote work, distributed workforces, and digital business channels expand. Add in IoT, sensors, and evolving technology that generates data at an alarming rate, and you have a recipe for an unmanageable data mess. You can overcome these challenges by incorporating a data fabric layer on top of everything to connect disparate data sources across cloud and location boundaries.
Payoda has helped organizations modernize without disrupting or replacing legacy systems by implementing a data fabric strategy. Our expertise in Data fabrics provides a comprehensive view of data, including real-time data, reducing the time required to discover, query, and deploy innovative strategies while providing deeper data analysis for improved business intelligence. You can virtually unify and access your data, whether on-premises, in the cloud, or on hybrid or multi-cloud platforms.
Consult our experts and innovation advisors to solve critical enterprise challenges.