Data Fabric: Build Foundation For A Resilient and Agile Data Management

The term Data Fabric has joined the lexicon of analytics and data management buzzwords a few months ago. Recently Gartner identified “Data Fabric'' as one of the top Ten Data and Analytics Technology Trends. But why has it become a trend that is being leveraged by companies? In the current scenario, the complexities of modern data management are increasing rapidly as new techs, new types of data, and new platforms are introduced. As such, transforming data management methods with each technological shift is complex and disruptive. With technological innovations accelerating, the traditional approach to data management has become unsustainable. A data fabric can diminish disruption by curating a highly adaptable data management strategy with augmented data management and integration.

In simplest terms, it is a single environment consisting of unified services and architecture or technologies that assist enterprises to manage their data. The eventual goal of data fabric is to maximize the value of data and accelerate digital transformation.

A data fabric is agnostic to data processing methods, deployment platforms, data delivery methods, locations, and architectural approaches. It facilitates the utilization of data as a strategic asset by abstracting issues. A data fabric makes sure that any data on any platform from any geography can be successfully accessed, combined, shared, and governed efficiently and effectively.

Succeeding in the current environment and becoming a data-driven company is not easy. There are multiple roadblocks on the way to becoming a digital leader. As enterprises use multiple apps, their data becomes increasingly inaccessible and siloed beyond its initial scope. While legacy systems and infrastructures only exacerbate the problem, data can become siloed when migrating to the cloud.

A typical organization today has data in multiple on-premises locations and numerous public or private clouds. And it can be tricky to share data between data residing on different public clouds (e.g., Azure and AWS) or between a public cloud and on-premises data center, or storing it all in a cloud data warehouse. The data is stored as unstructured, semi-structured & structured and is being maintained in various formats – file systems, relational databases, SaaS applications, etc. As such the processing of that data spans across many technologies, from batch ETL or ELT processing to changed data capture (CDC) to real-time streaming. With almost three-quarters of organizations (74%) using six or more data integration tools, it becomes complicated for organizations to be agile and quickly ingest, integrate, analyze, and share their data and incorporate new data sources.

As the amount and data sources continue to increase, the problem only gets worse. As a result, data professionals spend 75% of their time on tasks other than analysis of data. Not only does this considerably inhibit the capability of companies to get the most out of their data promptly, but it is also a grossly wasteful and unproductive use of your data professionals’ time.

Additionally, the roadblocks preventing organizations from having rapid access to data, many issues make it difficult for the data itself to be trustworthy. Almost half of the enterprise data has integrity issues. And it is ten times more costly to get any work done that relies on data if the underlying data has flaws.

Implementing a data fabric to manage the governance, collection, integration, and sharing of data can assist companies to meet these challenges and become digital leaders. It is not specific to data management or integration issues. It is a scalable and permanent solution to manage data under an amalgamated environment. Ultimately, implementing a data fabric can assist an enterprise in meeting its data management issues and becoming digital sound by

• Offering a single layer of architecture for collecting and accessing all data, no matter how it’s stored – eliminating data silos and no matter where it’s located.
• Enabling unified and simpler data management, including data integration, governance, quality, and sharing, by eliminating numerous tools and offering faster access to healthier and building more trust in data.
• Implementing greater scalability that can adapt to increasing data sources, data volumes, and apps.
• Making it easy to leverage the cloud by supporting hybrid, multi-cloud, and on-premise environments and faster migration.
• Decreasing reliance on legacy solutions and infrastructures.
• Future-proofing the DM infrastructure as new data sources and endpoints, along with new techs, can be added into the data fabric without disrupting existing deployments or connections.

Mentioned below are ways in which data fabrics can help several enterprises effectively manage data

1. Overcoming Data Movement and Data Silos

One of the most complex challenges for proper data management remains data silos. Isolated and contextless data sources always tend to fail when providing an appropriate picture for big data management. Moreover, all the siloed data might have all the same information stored in various databases, threatening the integrity of data. In the case of proper traditional management of data architecture, the data movement will copy all the data provided in a particular storage system to transfer it into another with the help of intermediary servers. The core challenge with this method is that the process tends to be pretty time-consuming. Having data fabric in place can solve all the data movement and isolation challenges by consuming less time.

2. Quicker Reactions to Different Changes in Data Volumes and Sources

Since business enterprises tend to consume, store, and generate the data for a very long time, there is always a need to control the volume requirements and the increasing sources of data, which can become a challenge. However, using data fabrics, enterprises tend to enjoy a proper and scalable mechanism that is a permanent method for bringing all the data sources in a singular platform. Therefore, with the help of data fabric, the enterprises can adequately enjoy greater scalability as well as the acclimatization of more and more applications, data sources, and rising volumes of data.

3. Supporting End-to-end Comprehensive Management of Data

Data fabrics ought to accelerate all the business use cases relevant to any particular enterprise, including customer intelligence and risk analytics, amongst many others. To improve data management, the scope of data fabrics should have different aspects such as data catalog, data ingestion, preparation, integration, and security. Solutions of data fabrics that properly fit the business will provide great value.

4. Acceleration and Optimization of data pipelines

Queries on databases with millions of records can take time to return. With a data fabric, organizations can minimize the time and effort invested into data preparation, resulting in quick time-to-insight, which is appreciated in a present fast business environment. Data pipelines can be tested, configured, and set up for reuse to pace the data preparation. It can also be automated to automatically carry out data transformations, cleansing, masking, and other operations to improve data preparation quality.

5. Robust data integration

Data integration problems are a common pain point in data projects. The utilization of data fabrics can alleviate this pain point by being compatible with numerous data delivery techniques—for instance, replication, streaming, ETL, and data virtualization among others. Data fabrics offer robust data integration and also improve data management efficiency by supporting all types of users, often business users and IT users. Furthermore, through ecosystem integration, enterprise stands to deliver better business value and outcomes due to business process optimization and greater flexibility.

Effective utilization of data fabrics can improve the approach to proper data management. These points mentioned above are proof of the point. That could be an important reason why companies and enterprises use data fabrics as their design method for data management.

Given the velocity and scale of the present enterprise data landscape, no single solution is best for every data problem. A revolution in data fabric is reshaping how companies unify, collect, manage, and utilize data. It can help your organization create more compelling customer experiences. To know more, you can converse with our experts at Polestar Solutions. Here we deliver robust, scalable, and secure on-premises, cloud, or hybrid data management services aligned with your business objectives. Book a session today!