Delivering the promised value to customers. Eliminating data thefts or breaches in financial services. Increasing productivity and optimizing supply chains in manufacturing. Improving patient care and other healthcare outcomes. The common thread in all of these efforts is data integration.
Over the past decade, data integration solutions have turned out to be a top priority across industries: 90 percent of organizations understand its value, and a lot of them have started to leverage data integration solutions in place, with an eye toward scaling use cases.
To date, on the contrary, the majority of companies have not been able to unlock the full potential of data integration owing to two main reasons: the rapid proliferation of data and overburdened IT teams.
The big data revolution has caused multiple challenges. Companies find it difficult to align their teams to integrate and analyze this data with precision, thus turning difficult to do business with. Along with that, IT or technical teams grapple to consolidate complex, bi-directional data streams on time, thus impacting productivity to a large extent.
Many companies have pointed to self-service integration as the remedy. Self-service integration enables companies to unlock the true potential of big data and handle its complexities with ease and speed. It also reduces the burden on IT by empowering non-technical business users to create data connections and integrate new customers at the speed of business. In other words, it enables companies to gain more value from their data and improve productivity.
Overcoming Barriers to Data Integration
There are several barriers to successful data integration:
- 1.Gathering big data from different sources and integrating it into a data lake can take a lot of time.
- 2.Mapping various data fields with the target ones is a complex task as IT teams need to write long hours of coding and execute complex EDI mapping routines.
- 3.As IT is responsible for building integrations, they fail to focus on governance and more-high value tasks.
In an effort to overcome these barriers and more, companies typically implement data lakes. But data lakes are not documented and therefore not scalable, and the testing of models is handled manually, significantly lengthening the process.
Companies seeking to address these challenges won’t make progress by taking a piecemeal approach. Instead, they must empower every business user to become a data integrator and drive data-driven operations, while enabling IT to handle governance and focus on more high-value tasks.
Self-service to the Rescue
Self-service integration enables non-technical business users to create data connections and manage transactions – securely and easily. They can utilize pre-built application connectors, shared templates, dashboards, intuitive screens, AI data mapping and more to monitor and integrate complex data streams in minutes instead of months. By enabling anyone to be a data integrator, it helps them delight more customers and drive value. At the same time, it enables IT to take up the role of governance and focus on more strategic activities, thus driving innovation and growth.
This way, companies across all sectors can quickly integrate and analyze their data streams to speed up insights delivery and ultimately decision-making. Plus, the productivity jump will be on another level. So, it’s wise to say that companies that rely on self-service integration can reimagine outcomes: deliver valuable experiences and improve productivity.