Data integration is a process of combining data from different sources into a single, unified view. It begins with data ingestion, and includes essential steps like data cleansing, mapping, and transformation. The ultimate goal of data integration is to produce actionable intelligence that helps businesses make successful business decisions.
For better understanding, we’ve prepared a list of most frequently asked questions about data integration along with their answers. Take a look.
Data integration involves a process of consolidating different types of data (unstructured and structured) garnered from disparate sources into a single data set with the ultimate goal of offering users with centralized access and delivery of data and to meet data needs of myriad applications as well as business processes. It is one of the primary components in the overall data management process that has become indispensable with the rise of big data and the growing need to integrate it.
Enterprises that wish to gain a competitive edge are embracing data integration. Not only do these cutting-edge technologies support queries in these enormous datasets but also enable business intelligence and customer data analytics to data enrichment and real-time information delivery.
Data integration plays a significant role in helping businesses manage business and customer data for delivering value. Enterprise data integration solutions ingest data into data lakes and data warehouses to support faster decision-making.
Integrating customer data in a unified dataset enables business users get a complete picture of key performance indicators (KPIs), financial risks, customers, regulatory compliance efforts, manufacturing and supply chain operations, and other aspects of business processes. This helps them analyze and process data effectively to stay ahead of the competition.
Data integration is of great use in the healthcare industry. When medical centers and units integrate data from myriad patient records, they can use the cohesive data to streamline diagnosis. In other words, data integration creates a unified view of useful information that can be accessed to extract insights into patient’s conditions or diseases. Effective data integration improves claims processing accuracy for medical insurers to boot.
Gathering data from several data sources and turning them into a unified set imposes many challenges. As more business users embark on the journey for building out integration solutions, they are jam-packed with operational tasks of creating pre-built processes for streamlined data movement. Though this helps businesses save time and costs in the long-term, implementation can be hindered by numerous obstacles.
Self-service integration platform by Adeptia allows companies empower their users ingest, map, transform, and integrate data and make it suitable for analysis without IT support. With features like pre-built connectors, shared templates and more, users can onboard and integrate complex customer data feeds in minutes. This means that users can carry out all the operational tasks from mapping to transformation without IT intervention. And IT teams become free to take up the governance role for driving innovation and growth.