Data fabric is an emerging data management concept that brings multiple data delivery technologies together to craft flexible data pipelines, services, and semantics that are centrally governed. Modern enterprises leverage data fabric to define how the data flows by linking information silos. The objective is to enable employees to access context-rich data on demand.
Data fabric is designed to help organizations solve complex data problems by enabling frictionless access and data sharing in an untidy data environment. It aims to unite data access and make your tech stack more manageable, gaining valuable insights. A correctly assembled data fabric reduces the time taken to access, ingest, integrate, share, and act on data thereby creating new opportunities in the process.
Implementation of Data Fabric
In the data fabric architecture, any user can take the raw data and use it to drive multiple conclusions, helping organizations to leverage their data in order to grow, adapt and improve.
Successful implementation of a data fabric requires:
- Application and services: This includes necessary infrastructure such as development of apps and graphical user interfaces (GUIs).
- Ecosystem development and integration: Creating the necessary ecosystem for gathering, managing, and storing the data which then needs to be transferred to storage systems thereby avoiding data loss.
- Security: The data collected from various sources must be managed using proper security techniques.
- Storage management: Data is stored in an accessible and efficient manner, allowing scalability whenever required.
- Transport: Building the necessary infrastructure for accessing the data from anywhere across a company’s geographic locations.
- Endpoints: Developing the software-defined infrastructure offering end-to-end solutions.
Why is data fabric important now?
Challenges such as lack of data access and the complexity of data integration prevent organizations from leveraging their data completely while maximizing its value.
Earlier, software development teams went with their own implementation for data storage and retrieval making data spread across rigid and isolated data silos thereby creating issues for modern businesses. Given the huge amounts of data available these days, traditional data integration is unable to meet business requirements such as universal transformations, real-time connectivity, etc. Most organizations, therefore, face the challenges of integrating, processing, and transforming organizational data from multiple sources.
Data fabric empowers organizations to use their existing data architectures more efficiently with comprehensive data access in real-time that can be visualized across locations. Data fabric can be implemented to simplify data governance and data management in multi-cloud data landscapes. For instance, today’s apps store data in a wide range of formats, even if they are using the same data. Taking data to the right application at the right time is imperative, but it’s a tough nut to crack. That’s where a data fabric architecture can solve your problem. With a data fabric, you can build a global and agile data environment that can track and govern data across applications, environments, and users.
Data Fabric Examples
A data fabric architecture can work with data warehouses and data lakes as well as any other data sources, thus making it flexible for organizations. Some of the data fabric examples that you can consider for improving your organization’s processes include:
Enhancing machine learning (ML) models: ML algorithms can monitor data pipelines, and identify and recommend appropriate connections and relationships with data while gathering information from data fabric. Getting the data ready is one of the most time-consuming elements of training an ML model. A data architecture, therefore, helps to use ML modes by decreasing the time taken to prepare the data. It also enhances the usability of this data across applications while also providing controlled access to secure data.
Building a holistic customer view: A data fabric can help organizations gather data from customer activities and understand how interacting with this data can offer additional value. Some of this data may include consolidating real-time data of different sales activities, the time taken to onboard customers, and customer satisfaction KPIs.
Data Fabric Benefits
Here are some of the operational benefits data fabric provides to enterprises:
- Simplified data orchestration: Integrating operators for external databases, business logic, masking, parsing, and streaming.
- Automated test data management: Generating data from production systems to provide high-quality data for testing purposes.
- Quick data privacy compliance: Configuring, managing, and auditing data access requests linked with data privacy regulations.
- Comprehensive data administration: Configuring, monitoring, and administering data using management tools.
- Optimized cost of ownership: Reliance on the in-memory performance of commodity hardware, complete linear scalability, and risk-free integration.
Why Use Data Fabric?
Data fabric helps organizations leverage the power of their accumulated data across a local, hybrid cloud and/or multi-cloud environment. A data fabric helps create an efficient environment for business, management, and organizational practices by modernizing storage and data management.
Business Efficiencies: Data is processed quickly and efficiently with automated pipeline management resulting in time savings. Users can gain a holistic, real-time view of their data with access to every data point. Data fabric also lowers TCO i.e. total cost of ownership to scale and maintain legacy systems by reducing the cost.
Data Management Efficiencies: Data processing, cleaning, transformation, and enrichment is a tedious and repetitive process. By automating this data, much of the burden and time can be reduced. A well-designed architecture allows organizations to store data, making it scalable, efficient, and cost-effective.
Organizational Efficiencies: A data fabric creates a semantic abstraction layer that helps in translating data complexities into a simple and easy-to-comprehend business language. This type of data is of great utility to those without deep data training and experience.
Implementing a Data Fabric Strategy
Data fabric provides a holistic view of data, reducing the time required to discover, query, and deploy innovative strategies. It also provides deeper data analysis that creates better business intelligence using real-time data. By deploying a data fabric layer, organizations can overcome the challenges of bringing together various data sources in a diverse data ecosystem. Using data fabric, users can unify and access data virtually whether it lives on-prem, in the cloud, or in hybrid or multi-cloud platforms.
For more information, watch this webinar on data fabric, presented by Claudia Imhoff!
Idera, Inc., WhereScape’s parent company, has a set of tools that can fully implement your data fabric architecture. Click here to learn more!