Even though technology transformation is enabling accelerated progress in data engineering, analytics deployment, and predictive modeling to drive business value, deploying a data strategy across cloud systems remains inefficient and cumbersome for CIOs.

One of the key obstacles is data access. All too often, enterprise data is siloed across various business systems, SaaS systems, and enterprise data warehouses, leading to shadow IT and “BI breadlines”—a long queue of BI requests that can keep getting longer, compounding unresolved requests for data engineering services.

It’s much easier said than done to break down data silos and to make processes more agile and nimble across a variety of stakeholder groups—mainly because each respective organization is centrally managed, but also because of the era we are in.

“The size, complexity, and distributed nature of data, speed of action, and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down,” said Donald Feinberg, a vice president and distinguished analyst in the Gartner ITL Data and Analytics group.

Data silos are often exacerbated by multiple cloud environments configured and partitioned for each line of business. This makes it even more difficult to integrate data from each group, as each of these environments is rigid, shaped as they are by their own domain knowledge, schema, or data dictionaries.

For enterprises to achieve efficiencies and better position themselves to respond to a constant rate of change, it’s important for CIOs to install a more-nimble-yet-unified data fabric.

What is a data fabric?

A data fabric is an increasingly popular and important term in the digitally transforming world. In fact, Dan DeMers, CEO of enterprise data collaboration platform provider Cinchy, has gone so far as to call it “the first real evolution of data since the relational database appeared in the 1970s.”

The phrase, according to EM360Tech, refers to a specific architecture that aligns a set of data services and streams within an organization. Using a data fabric solution, you can essentially stitch together various data tools to include a consistent set of capabilities and functionality.

Such an offering can also simplify and integrate data management on a massive scale—whether that data lives on premises or in cloud environments—and be used to develop an enterprise-wide data modeling process.

Ideally, CIOs and data practitioners get the full functionality of a unified BI architecture without having to move any data out of a cloud data warehouse (CDW).

Through a connected architecture and a robust collection of APIs—from no-code data pipelines to SQL and Java command-line tools—data fabrics can be used to bring data into a customer-owned and -managed CDW while letting you control which cloud or warehouse incoming data can be written to.

With a strong data fabric, CIOs can enable all of the following components that sit across multiple cloud environments:

• Rich charting and data-driven dashboards
• Alerts and data science workflows
• Augmented capabilities
• Powerful business apps
• Enhanced data access with stronger access controls and improved security

Why a multi-cloud solution is key

A multi-cloud data fabric solution offers a number of benefits. For one, it gives IT warehouse managers the freedom and flexibility needed to orchestrate workflows and drive business impact much faster. For another, it enables business users to access warehouse data in a highly governed way. What’s more, it provides the ability to:

• Integrate dark data with your CDW
• Integrate your SaaS data and non-traditional sources into your CDW
• Eliminate the need for shadow data without removing systems
• Leverage CDW data without moving it or compromising security
• Maximize your CDW investments
• Eliminate tech debt and IT backlog from business user data requests
• Drive total cost of ownership

Using data transformation tools to build robust data pipelines—from intuitive ETL tools to scriptable transformations that work natively on the customer’s own data warehouse—a multi-cloud solution delivers more technically intensive workflows to more business-oriented users.

A multi-cloud solution can power data transformations and pipelines across clouds that result in data being written to a target cloud warehouse. This makes data from a customer’s warehouse distributable to its own customers or partners in a controlled, governed manner.

The bottom line

Creating a data fabric is an essential component to any modern data architecture, and is a promising vision for driving business value in the future.

A data fabric not only enables users with self-service Bl to deliver real-time insights across the entire business with live visualizations and automated alerts that signal the need for action, it enables IT to maintain control. As well, you can:

• Build intelligent applications for individual teams’ processes and use cases to enable faster action on CDW data
• Share data experiences securely with customers and partners through embedded analytics—an activity that typically reveals data monetization opportunities
• Use a consistent mechanism for governing data that resides in CDWs—or data in any designated environment that needs to be made custom for analytics

To learn more about how today’s CIOs can develop and use a data fabric to overcome mounting challenges as enterprise ecosystems become more complex, click here.