Data management in the modern enterprise requires skill and stamina. With the mountainous rise in data volume and the complexity of managing disparate data sources across a wide variety of legacy systems and hybrid cloud environments, it can seem virtually impossible to successfully climb past enterprise data obstacles to success. However, data fabric technology eliminates some of those obstacles. Is it the answer for your data strategy? Let’s examine some key questions about when to use data fabric.
First, how does data fabric work? Data fabric creates a virtualized layer of data across any system connected to it, unifying all of your enterprise data in a single environment. This solves data silo problems and creates a single source of truth for real-time insights.
What problems do data fabrics solve?
What makes a data fabric solution different from previous data management architectures is that your data stays in its source systems, whether on-premises or in a cloud service. With a data fabric architecture, you leave data where it is and create, read, update, and delete directly from the fabric. This unified architecture combines a variety of integration tools for consistent capabilities across all your data.
You are also able to provide frictionless data access to business users dealing with constantly changing customer needs and market shifts.
[ How does data fabric differ from older technologies and what benefits does it deliver? Read What is Data Fabric? and Data Fabric vs. Data Mesh vs. Data Lake. ]
Data fabrics can solve a wide variety of enterprise problems related to data access, data governance, insights discovery, and overall data management.
Data access: While data democratization includes both data access and data literacy initiatives, data fabric can really allow you to unleash digital innovation with real-time data to a wide spectrum of business users.
Data governance: Having data stored in a single platform gives you the governance capabilities needed to secure data and mitigate compliance risks (especially when dealing with customer data).
Insights discovery: The unified environment of a data fabric provides a 360-degree view of enterprise data that can surface previously hidden insights.
Data management: Low-code/no-code features give you lightning fast business agility to discover and update data models while keeping data optimized data for any digital need.
When data fabric fits: 4 criteria.
1. What is the organization’s end goal?
A simple yet all too often overlooked question: what are you trying to do here?
Spend the time upfront to define your organization's needs and get specific with what you are trying to accomplish with a data fabric architecture. What specific data management challenges are you facing right now? For example, are you struggling to manage and provide access to data in legacy architectures, or are you jostling with a hybrid cloud environment? Are you trying to speed application development? Strengthen security and compliance? Mash up data sets in new ways? These answers will help you determine the key outcomes you will want to achieve with a data fabric.
2. What data sources do we need and what’s hiding in silos?
Survey and evaluate your current data architecture. Every enterprise has a complex architecture with multiple data silos. Identify what data sources the business needs right now and in the future. If you are building a new application, where are all of the data sources coming from? Are they in different systems in a public cloud? Or are there nuances to the current landscape, such as edge devices?
Mapping these sources will also help you tell an impactful story to showcase the power of your data integration tools.
[ Discover how you can eliminate data silos with an integrated data fabric: Watch our on-demand webinar. ]
3. How strong is our data governance?
This one can uncover scary truths, but enterprises need to understand their current data security setup and policies across the data landscape. You should be asking your organization questions about how they are or want to audit data throughout an application. Are there additional compliance requirements that they need to be following? What’s on the horizon in terms of regulatory and compliance demands?
4. When does the data fabric need to go live?
This not only sets expectations but also helps everyone understand the implementation process. In enterprise data management, complex data issues can take time to untangle. Getting a clear understanding of any dependencies and risks of not hitting deadlines (e.g., compliance requirements) will help teams to prioritize the work.
While we all want to get to an MVP as soon as possible, it’s also worth mapping out the long-term strategy. Are there additional pools of metadata that business teams want to connect? Getting this information now will help with scoping for the future.
Data fabric success factors
Data fabric architecture offers a promising solution to unify data and create a single source of truth for a variety of business use cases. By democratizing access to data and providing real-time insights, data fabric architectures can provide your business teams with a competitive edge.
However, it's important to ask critical questions and understand your organization's needs and goals before implementing a data fabric architecture. By identifying your data management challenges, evaluating your current data architecture and data security, and understanding the implementation process, you can successfully leverage this new data integration tool to drive organizational success in the digital world.
Want to learn more about how to solve your data silo problems and speed up innovation? Get the eBook: The Data Fabric Advantage.
