Data integration is the process of combining or consolidating large volumes of data, in different formats, from different sources, into a single, unified view. By accessing the resulting single source of truth, business users across myriad teams can leverage the intelligence to provide the best possible service and care.
In other words, data integration provides a holistic view of the customers’ interactions with the business. Subsequently, the knowledge gathered can be harnessed to create more effective business relationships and delightful experiences for customers.
Data integration begins with the ingestion process and includes steps such as cleansing, ETL mapping, and transformation. It ultimately enables businesses produce effective, actionable business intelligence in order to keep business in motion and grow revenues.
Even though there is no universal approach to customer data integration, it typically involves a few common elements, including a network of data sources, a master server, and users accessing data from the master server. However, the way this is done actually determines the efficiency of the process.
Say, for example, organizations rely on API or EDI-based mechanisms to facilitate customer data integration and exchange between different channels and tracking them in somewhat more sophisticated databases.
Related White Paper: Reimagine your Customer Data Integration
These solutions, though useful when companies are supposed to handle limited data volumes, are almost ineffective in dealing large volumes of data. IT teams struggle with delivering value to customers owing to the resulting fragile data exchange architecture. As a result, organizations can experience friction during streamlining EDI or API-like exchanges, impacting collaboration and agility. To add, these mechanisms put a lot of burden on the IT teams to harness the true potential of customer data, consuming their time that could be used for more high-value tasks.
So, simply put, while EDI and API-based integration technologies can prove useful in dealing with low-volume data, they are not of much use when the volume or complexity increases. In which case, self-service proves to be the best solution.
Now, that we can see some data integration solutions have limited capacity, it’s time to explore self-service and discover how they can enable business users execute customer data integrations without complexity and delay.
Self-service integration solutions can give the power of creating data integrations into the hands of every business user, across myriad teams.
Related Datasheet: Employ Self-Service to Expedite Data Integrations
As organizations employ these solutions, they can leverage the information gathered from different data sources for driving business opportunities.
The intelligence can be used by the business people in the respective value chain to drive value without needing IT to interfere. They can take a look at the data streams and customer entities through dashboards and make data onboarding connections through easy screens.
Since the power is in hands of the business users aka citizen integrators, this gives a breathing space to IT teams and allows them to only control or govern the processes. As a result, IT becomes more productive and they can focus on more important, strategic tasks. They no longer have to get involved in tedious and thankless API coding and EDI mapping to integrate customer data.
Additionally, with technological advances in artificial intelligence and security protocols, these users can rapidly understand and define data semantics, and then make data connections following those data rules within minutes.
Adeptia’s self-service-powered customer data integration solution allows organizations transform the way they do business and deliver valuable experiences to customers.