Data Fabric Architecture: Modern Way of Data Management and Integration
In this article, discover more about how a data fabric architecture serves as an integrated layer of data and connecting processes.
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Data Fabric provides a single environment to access data and enable simpler and unified data management by connecting data from disparate sources. Such a data architecture helps businesses to discover unique, business-relevant relationships between the available data points.
Data fabrication is an architecture that is developed to standardize data management practices across multiple environments cloud, on-premises, and edge devices. Data fabric is listed among Gartner’s top 10 Data and Analytics trends. It also allows enterprises to cost-effectively leverage technologies such as artificial intelligence and IoT by reducing time for integration design by 30%, deployment by 30%, and maintenance by 70%. With the increasing scalability and complexity of data from disparate environments in enterprises, a data fabric architecture helps to take the data to the right place and at the right time to make business analysis easy. Thus, it helps to unleash the power of data to meet business demands.
Data Fabric Capabilities
Data fabric architecture ingests data from all sources to provide consistency across all the environments or systems such as SAP, AWS, etc., or technologies leveraged in an enterprise. The data obtained from the varied sources is managed from a data fabric’s rich set of data management capabilities such as data automation, testing, and deployment.
The architecture is capable of collecting and analyzing all forms of metadata to build a graph model for key metrics of metadata. This capability provides unique and business-relevant insights. Data fabric also serves as a broad range of drivers for the following:
The use of data fabric helps to reduce time to get trustworthy insights. It provides a real-time, 360-degree view of any business entities such as customer, order, device, etc. that helps in making informed business decisions.
The automation in data preparation (including data transformation, cleansing, and enrichment tasks) saves the time of the resources, thus, making the data management process more efficient and cost-effective.
It serves as a common language shared between data engineers and data consumers by making the right data accessible at the right time.
Data Fabric Features
In the times when change across business operations and innovation is a new way to drive to have a competitive edge, businesses are aware that only trustworthy data can serve business and customer needs. Increasingly, businesses are trying to get quick and insightful data by adapting different technologies. However, with the prevalence of new technologies like the Internet of Things, more types of data are obtained from various sources, making it much more difficult to manage. Therefore, it is important to build a unified data management architecture.
Improves Data Integration
Integrating data from multiple sources becomes a common pain point for enterprises. Data fabric architecture connects multiple endpoints through numerous techniques of data delivery; for instance: replication, data virtualization, streaming, ETL, etc. Data fabric thus offers robust data integration and improves data management for businesses. The architecture eliminates the data silo situation by handling multiple environments simultaneously, including on-premises, cloud, and hybrid. The simplified data integration and management help businesses to get better insights for business process optimization.
Handles Data Volume and Scalability
Constantly growing data volumes and maintaining control over the volume with increasing data sources becomes a challenge. Therefore, data fabric offers a scalable mechanism to bring together all data under a single platform. A data fabric enables enterprises to mobilize their data effectively to enjoy greater scalability and acclimatize to more applications, rising data volumes, and more data sources. The data scalability management provides a competitive edge.
Provides Centralized Data Security and Governance
Businesses are concerned with the rising rates of cyberattacks and data breaches across industries. Data fabric architecture helps to establish standardized security policies for all connected APIs and ensures homogenized protection across different data end-points. Data fabric enables simple and unified data governance processes by configuring roles for data sanitization or tracing the origin of data to determine the integrity and compliance of data. Data fabric architecture offers centralized data security and governance policies which are implemented consistently across varied environments.
Improves Flexibility and Removes Technology Constraints
Earlier businesses decisions on data storage and management often affect the future use of certain analytics tools and technologies. For instance, integrating an on-premises system with a mix of other environments may prove to be less technologically feasible without putting concrete mediums of interventions. Data fabric architecture is specialized to bring together heterogeneous systems by connecting various infrastructure endpoints to the consolidated and unified data management framework. It establishes a connection between the systems and ensures faster data transfer. Therefore, it offers a single interface that manages and controls the data from all end-points or across multiple assets.
Getting Started With Data Fabric Platform
Selecting the right data fabric solution is a challenging process. Let’s look at some of the top data fabric platforms and their offerings.
- Denodo is a major player in the data virtualization tools marketplace, offers high-performance data integration and abstraction across a range of big data, enterprise, cloud, unstructured, and real-time data services. The focus is on a data virtualization solution that is provisioned as a virtual image on Amazon AWS Marketplace.
- K2View Fabric is a unified platform for data integration, transformation, enrichment, orchestration, and delivery. The platform offers real-time support on queries for each business. K2View uses a unique technology called Digital Entity, wherein fragmented data for each business entity is unified into its own micro-DB to deliver a holistic view. K2View is scalable and can support massive data workloads requiring real-time data integration and movement.
- IBM Cloud Pak for Data is an open, fully integrated data and AI platform. It offers several distinct integration delivery tools and architecture in both on-premises and cloud deployments. It provides a data fabric solution for faster, trusted AI outcomes by connecting trustworthy data from varied sources. It uses unique data governance solutions and methodologies to deliver trusted, business-ready data. It consists of modern integration synchronization and data virtualization solutions as well.
Data-driven insights and decisions bring new business opportunities and grow at an average of more than 30% each year. (Read the Forrester insights-driven Businesses Set the Pace for Global Growth Report to learn more). Thus, a single instance of any one type of data can exist at multiple locations, but it is important to ensure that each instance points to the same resources and that the type of data flowing to the resource is the same. A data fabric architecture serves as an integrated layer of data and connecting processes. It offers a range of business value propositions by addressing the technical challenges of operating and managing data services across environments.
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