We live in an era when the speed of business and innovation is unprecedented. Innovation, however, cannot be realized without a solid data management strategy.
Data is a platform through which businesses gain a competitive advantage and succeed and thrive, but to meet customer and business needs, it is imperative that data is delivered quickly (in near-real-time). With the prevalence of Internet of Things (IoT), smartphones and cloud, the volume of data is incredibly high and continues to rise; types and sources of data are aplenty too, making data management more challenging than ever.
Companies today have their data in multiple on-premise sites and public/private clouds as they move into a hybrid environment. Data is structured and unstructured and is held in different formats (relational databases, SaaS applications, file systems, data lakes, data stores, to name a few). Further, myriad technologies—changed data capture (CDC), real-time streaming, batch ETL or ELT processing, to name a few—are required to process the data. With more than 70 percent of companies leveraging data integration tools, they find it challenging to quickly ingest, integrate, analyze, and share the data.
As a consequence, data professionals, an IDC study finds, spend 75% of the time on tasks other than data analysis, hampering companies from gaining maximum value from their data in timely fashion.
Data fabric is one way for organizations to manage the collection, integration, governance and sharing of data.
A common question is: What is a data fabric?
It is a distributed data management platform with the main objective of combining data access, storage, preparation, security, and analytics tools in a compliant way to ensure data management tasks are easier and efficient. The data fabric stack includes the data collection and storage layer, data services layer, transformation layer and analytics layer.
Following are some of the key benefits of data fabric:
It used to be that organizations wanted all their data in a single data warehouse, but data has become increasingly distributed. Data fabric is purposely created to address the siloed data, enabling easy access and integration of data.
It is essential that a data fabric has the following attributes for enterprises to gain the maximum value from their data.
Full visibility: Companies must be able to measure the responsiveness of data, data availability, data reliability and the risks associated with it in a unified workspace
Data semantics: Data fabric should enable consumers of data to define business value and identify the single source of truth irrespective of structure, deployment platform and database technology for consistent analytics experience
Zero data movement: Intelligent data virtualization provides a logical data layer for representation of data from multiple, varied sources without the need to copy or transfer data
Platform and application-agnostic: Data fabric must be able to quickly integrate with a data platform or business intelligence (BI)/machine learning application as per the choice of data consumers and managers alike
Data engineering: Data fabric should be able to identify scenarios and have the speed of thought to anticipate and adapt to a data consumer’s needs, while reducing the complexities associated with data management
Data fabrics have emerged as the need of the hour as the support for operational data management and integration becomes complex for databases.
In fact, data fabric is the layer which supports key business applications, particularly those running artificial intelligence (AI) and machine learning (ML) workloads. It means, for organizations that aim to reap the benefits of implementing AI, leveraging a data fabric will help accelerate the ability to adopt AI products.
Digital transformation leads the strategic agenda for most companies and IT leaders. Data is a critical part of a successful digital transformation journey as it helps create new business propositions, enable new customer touchpoints, optimize operates and more. Data fabric is the enabler for organizations to achieve these with its advanced data integration and analytical capabilities, and by providing connectors for hybrid systems.
As organizations aim to stay updated on emerging technologies and trends to gain a competitive edge, the demand for data fabric will only get stronger.
By Uma Raj
By Uma Raj
By Abishek Balakumar
Suhith Kumar is a digital marketer working with Indium Software. Suhith writes and is an active participant in conversations on technology. When he’s not writing, he’s exploring the latest developments in the tech world.