Master data management is crucial within this era of digital transformation. Being able to not only garner insights from data sources but maintain formatting for both on-premises and cloud technology is pivotal to making better business decisions. This starts with data integration, bringing in the viable information from across your business spectrum into a system that makes for the best data pipeline possible. Here is what you need to know about integration and how your business can upgrade how it brings new information into the fold.
What is data integration?
Data integration is the process of bringing data from various sources together to give business users a unified view of this information. Data integration tools are designed to make data more freely available. When done right, this technology reduces IT costs, improves data quality, and fosters innovation without having to make sweeping changes to existing data structures or applications. Companies with mature data integration capabilities have significant advantages over the rest of their competitors, as they can increase operational efficiency by reducing the need to manually transform and combine data sets.
Digital businesses are built around data and the algorithms that process those data sources. Analysts are able to extract the maximum value from those information assets across a business ecosystem. Within a digital business, data sources and related services flow unimpeded, but securely, through a structural landscape. With data integration, users given access will have a full view of the insights and information that are flowing through their organization. With evolutions in this architecture, it’s become easier than ever to take even historical data and turn it into real-time analytics.
How does data integration work?
Accessing data and making sense of it is a tremendous challenge for businesses within the digital environment. While businesses are doing more to get their data management in order, there is still a need to be able to bring relevant data together wherever it resides for the purposes of supporting organization reporting and business processes. Required data is often distributed across various applications and databases to make sure that its capabilities can be handled on-premises, in the cloud, or on IoT devices and even provided to third parties.
Organizations no longer maintain data in just one database. The traditional approach to data integration is known as physical integration, which involves physical movement from a source system to a staging area where data goes through cleansing, mapping, and transformation to deliver it to a targeted system. This approach involves the use of a data virtualization layer to connect to physical data stores. Unlike physical data integration, virtualization involves the creation of views of the underlying physical environment without the need for the physical movement of data.
How can business users improve their integration processes?
Data integration is the first step toward real-time access to all data sources. Businesses can choose an integration solution that lets them create a catalog of formats for reuse, especially nonfunctional processes. The ability to test any integration logic dramatically reduces the time needed for implementation and maintenance. Data integration processes are configured to connect applications and systems. These configurations need to reflect any change immediately, ensuring that the right systems are being utilized to propagate change across various environments.
Testing is at the core of data integration developments. Verifying data integration technology helps developers create and update logic across all data types. This avoids delays in the integration process that can end up hurting workflow and delaying business decisions. This increases development duration and costs. That’s why it’s important to invest in the right data services now for the sake of integration of any type of data and to bring businesses into this era of the digital revolution.
