5 Data Fabric Benefits That Will Save You Time, Money, and Headaches

Elizabeth Bell, Content Marketing Manager
December 28, 2022

These days, few people need to be convinced of the value of data. As businesses face pressure to innovate, IT is often overwhelmed with requests for custom data-driven applications.

Benefits of Data Fabric

But the issue is that for many IT teams, data is still more of an obstacle than an enabler. As data sources proliferate, data access becomes a complex puzzle. Data strategies like data warehouses, lakes, or meshes end up being expensive and slow to implement, making it difficult to use them to build real-time applications that deliver a 360-degree view of the business. And as development resources become scarcer, implementing technical data projects is harder than ever.

What if there was a way to easily connect data, without moving it, so that you could use it to build powerful business solutions?

Many teams are turning to a data strategy known as a data fabric to realize this possibility.

The benefits of a data fabric over other data strategies.

When it comes to building real-time applications that can deliver a 360-degree view of your business, a data fabric is the best data strategy to use.

A data fabric doesn’t require moving or transforming data.

Data strategies like data warehouses and data lakes require that data lives in a centralized location. Moving data into a warehouse or a lake is an expensive, time-consuming process that can damage the integrity of the data, and maintaining these systems adds to those costs. Engineers have to spend hours extracting, loading, and transforming data in order to make it usable. Additionally, data warehouses are traditionally used to store historical data, rather than transactional data, because of the difficulty of moving that fresh data in and out quickly.

Rather than migrating data, a data fabric can connect to data sources to pull data while keeping it in its source location. This means data stays fresh and accurate, making a data fabric well-suited for transactional data.

Note: If you have a data lake or a data warehouse, or you plan to build one for a data project, data fabric can easily complement these systems. A data fabric connects and unifies these data sources to help you extract more meaning and context.

A data fabric reduces the complexity of connecting to data.

But another data strategy can also connect to data sources: a data mesh. This is when microservices connect via API integrations and web services. A data mesh maintains data integrity, access to transactional and analytical data, and doesn’t require data migration—but it requires software engineering resources to code and maintain these data connections, as well as subject matter experts to curate the connections. A data mesh is also a decentralized solution, which means IT teams have to actively work to govern and align subject matter experts to coordinate all the connected domains.

A data fabric provides a layer that virtualizes separate data systems into a unified data model, complete with the ability to connect, relate, and extend data. With codeless data modeling, you don’t need to extract, transform, load, or hard-code. You can reuse the data connections you create in any application to support anything from case management to account onboarding to supply chain orchestration and more.

By eliminating the obstacles of other popular data strategies, a data fabric gives IT teams the power to build data-driven solutions.

5 benefits of a data fabric for data management.

Read on to understand the five ways a data fabric de-silos your data, so that you can get it into the hands of business users.

1. Gives you real-time access to data.

Traditionally, data warehouses and lakes have only supported historical data, because the static data has to go through an extract, transform, and load process before it can be used. This means there’s always a delay to getting that data.

With a data fabric, you can easily act on your data, all in one place. The virtualized data layer connects to data in the original data source, creating a unified model of your different data sources. You can also build new relationships between data points and databases in the data fabric, as well as transform and manipulate existing columns into new fields of data. This enriches your data and creates more context and meaning for the data you already had. Real-time access to data means your business gains real-time insights.

2. Enables you to build with speed.

A data fabric gets data-driven applications into the hands of your business leaders faster than other data strategies. Because data stays where it lives, you don’t have to factor in the extensive migration time or the hard-coding of data connections that other solutions require. Instead, you retain full control over the data so that you can increase development speed.

It’s also easier to maintain and faster to build with, once you have the data fabric. See what we mean about building with speed:

  • No/low-code: Data fabrics provide pre-built connectors that don’t require coding to communicate with numerous data sources, systems, and web services. Many also offer APIs and templates for creating custom integrations without any coding needed. You can quickly connect existing sources of data or create new data models for your projects.
  • Automatic performance tuning: A data fabric doesn’t require technical database admins to optimize performance. Complex tuning is automatically taken care of by the fabric, saving you maintenance time and effort.
  • Composable design: Data fabrics enable you to reuse data models you’ve already created across applications. This agile and flexible architecture speeds up development by avoiding duplicate work and ensures data integrity across the enterprise.
  • Faster performance: Once you’ve built a solution on a data fabric, end users will experience faster queries, because data comes straight from the source. In fact, here at Appian, we’ve found our data fabric to be 6x faster at loading reports, 9x faster at sorting, 5x faster at loading dense grids, 2-4x faster search, and 2x faster security than traditional database views at scale.

3. Keeps data secure at every level.

A good data fabric gives you peace of mind that the right people can access the right data by securing data across many joins and nested relationships. With row-level security, you can create precise control by applying filters and business rules based on the data itself.

This has advantages for data analysis, but it also helps you provide access across the organization where needed. For example, if you created a case management application that pulls from a data fabric, you could allow only case submitters, case workers, and regional managers to see a certain case, regardless of what or how many systems the data comes from. Not only does this make security faster to implement, it means no worrying about sensitive data being in the wrong hands.

4. Allows easy updates to data models.

Once you’ve built a solution or an application on the data fabric, making data model changes is easy. Unlike traditional methods, where updates require technical database work, you can quickly add, delete, and relate sources as needed in a data fabric. The virtual data layer sitting on top of the data allows you to bypass complex modeling work and make those changes directly in your data fabric. This is a boon when technical expertise is hard to find.

In a platform with a built-in data fabric like Appian, it’s easy to adjust, add, or nest data relationships. Appian also lets you clearly see the impact of each change. For example, if you deprecate a data field, you can see every application where that field is used before removing it.

5. Provides broader access to data.

A data fabric will help you meet the demands of the business for more data. You’ll also be able to introduce a more collaborative process between those who manage data (you) and those who consume data (business users). How? Since the data fabric abstracts the technicalities of data work away, a data fabric allows less technical users and/or subject matter experts to get involved in the data modeling process. Additionally, with the rapid development enabled by a fabric, you can quickly iterate on your data models as changes are requested.

This broader access to data doesn’t mean giving up important control, though. IT maintains centralized governance with a data fabric, since data relationships come together in one space. Your team sees who can view, update, and delete specific data and make changes as needed to protect data.

A data fabric will make you an IT legend.

A data fabric approach takes away the pressure IT teams have felt for years to eliminate silos by moving data or connecting microservices with APIs. With a fabric, data is no longer a gating factor and cost-multiplier for your business. You now have the means to quickly tap into the data you need, update it with less time and resources, and make data securely available to all who need it.

[ Find out which trends deserve your attention in the Gartner® Top Strategic Technology Trends for 2022: Hyperautomation Report. ]