The importance of an organization’s data strategy cannot be understated in today’s world. With the speed at which data is created across the digital landscape, organizations need to be able to harness information from a wide variety of disparate sources at a rapid pace to drive business intelligence and competitive advantage.
That massive amount of data and the incoming velocity create a lot of headaches for enterprises that lack the agility to maneuver it behind the wagon of mainframes and legacy systems that they have acquired over time.
This is where enterprise data integration comes in. The right strategy and tools can dramatically improve your ability to drive actionable insights throughout the organization, optimize business processes, and improve business outcomes.
What is enterprise data integration?
Enterprise data integration is the process of unifying disparate systems of data and information to create a single source of truth for smarter business decisions.
Connecting data across hybrid cloud environments and the variety of data warehouses that many organizations deal with improves business intelligence in a wide variety of use cases. One example is creating a 360-degree view of your customer or centralizing case management information. Enterprise data integration also serves a broader reporting purpose: to help the entire organization be more data-driven through factors including:
- Cleaner data
- Better, real-time dashboards and reports
- Organizational agility with ad hoc data requests
- Greater insight discovery and analysis (your “ah-ha” moments)
[ Learn how a data fabric can transform your organization's data management strategies: Watch the on-demand webinar. ]
Enterprise data fabric’s role in data integration.
Modern data integration tools have drastically improved the speed at which we’re able to unify and get data into the hands of business leaders. Enterprise data fabric is the latest, cutting-edge technology that drastically improves your data integration.
Data fabric technology is a toolset that unifies key systems using a virtualized data layer to connect data from wherever it currently resides. Users interact with the unified view, but the data stays in its source, whether an ERP, CRM system, or an enterprise data warehouse. (It’s worth noting: These applications and systems can reside in both on-premises systems and public clouds.) One of the key benefits of data fabric is the speed at which it lets you build and modify data integrations over time due to the low-code architecture of data fabric technologies.
[ Want to demystify data terms and explain them to others? Read our related article: Data Fabric vs. Data Mesh vs. Data Lake. ]
Low-code architecture’s role.
Low-code data architectures allow developers to build and maintain enterprise data integrations quickly with unified and intuitive data modeling tools that limit the amount of manual coding required to connect systems. This not only allows the data teams to build new integrations between systems quicker but also reduces the technical debt accrued over time as requirements from business units change. That’s one reason why data fabric technology is quickly becoming a major part of many broader process automation initiatives.
5 enterprise data integration best practices.
As we know all too well, data integration is more than just plugging in a new technology to your stack. Let's dive into the key pillars of a successful data integration strategy for enterprises.
1. Strategy and planning.
This is the most essential, yet most overlooked, pillar of success in data integration initiatives. Before you take off, you need deliberate goals and key objectives for your team’s work. Ask yourself questions like:
- What are the underlying business objectives behind this work? (Unified data for faster reporting? Creating a more data-driven culture?) You need a crystal clear answer here.
- What systems are we trying to integrate and why?
- Which business units and/or teams are going to be impacted by these changes?
Once you have a clearer understanding of the business demands behind the initiative and the desired impact, you can scope and plan the work. This includes communicating the plan to stakeholders to provide visibility into timelines and expectations. A cautionary note: There should never be an “end date” to data integration strategies. More on that in pillar 5.
2. Data governance.
Given today’s abundance of digital data, enterprises should always have data security top of mind. When integrating data across systems or into a new one, it’s important to know exactly what that means for data access. An easy acronym to help you think about data governance is CRUD (create, read, update, delete).
You should confidently know which business units and specific users have access to create, read, update, and delete data.
This is another place where data fabric technology shines. With its low-code architecture, data fabric allows development teams to use simple business logic to secure enterprise data across the entire data model.
3. Technology.
This is the pillar that usually takes up the most oxygen in the room. Your team may feel overwhelmed by the number of technologies, including data integration and analytics platforms, that promise to assist you in your journey toward seamless data integrations.
Remember, data fabric and a host of other tools can combine to fit your needs. The key thing to remember is that each technology should serve a specific purpose. You should be able to map each piece of technology to a specific use case in your data flow. You should also consider data integration’s crucial role in a process automation strategy, which involves automating entire business processes from end to end. A process automation platform with data fabric capabilities has powerful potential here.
[ Learn how to successfully implement end-to-end process automation strategies. Get the Process Automation Guide. ]
4. People and processes.
This is where the rubber meets the road with regard to data integration. You can do all the technical digital transformation work you want, but if the actual process stays the same because people don’t buy into the changes—or you fall short when it comes to communication or training—your efforts will have been all for nothing.
Data integrations should make interacting with data more seamless for people—whether that’s more reports, data exploration capabilities, or just seeing information in a unified view. You’re changing how people can and should interact with the data.
Leaders need to communicate and train people on these changes—repeatedly. Change management takes time, hard work, and empathy. Your data integration success depends on it.
5. Continuous improvement.
Rome wasn’t built in a day, and your enterprise data integration strategy won’t be either. Continuous improvement is the goal here, and low-code architecture again plays a key role. Low-code application development tools let you rapidly update data integrations without needing to dive into complex code.
Prioritize iteration in your approach to enterprise data integration and understand that the job is never “done.” There will be changing business and regulatory requirements as long as the digital world continues to evolve.
Why enterprise data integration equals competitive strength.
As we become more reliant on digital technology, enterprise data will grow at exponential rates. The success of large enterprises will depend on their ability to harness the power of all that data and use it to drive better business outcomes.
The data in enterprises is often considered a tangled mess that can never be unraveled (just like the extension cords in my garage . . .). But with a proper enterprise data integration strategy and modern tools like data fabric, you can knock down data silos and provide key insights that will keep your organization competitive for years to come.
Want to learn more about how to solve your data silo problems and speed up innovation? Get the eBook: The Data Fabric Advantage.
