4 Frequently Answered Questions about Data Integration Platform

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. 

1. What is Data Integration?

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. 

2. Why is Data Integration Important?

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. 

3. What Are the Challenges of Data Integration?

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.

• Dealing with data in heterogeneous formats: The data gathered from assorted data sources usually are in myriad formats such as JSON, XML, CSV etc. Now, to make these different data types useful, users must convert them into a standardized format, otherwise, it’s of very little use. Companies that rely on legacy integration systems are not able to handle this heterogeneity and deliver value. 
• Extracting value from data: A common complaint of users is that they find it difficult to extract value from data once it has been integrated. Plus, with the addition of new sources, the process of value extraction becomes messy. Legacy systems are incapable of deriving value from this newly added sources as companies scale. 
• Executing business processes and workflows: Users find it hard to manage business processes and workflows while they integrate data. And legacy systems that are heavily coded and rely on manual intervention make it even more difficult. Simply put, in the absence of automation and other transformative technologies such as AI, managing processes and workflows become a cumbersome and tedious task. Since these operations require expertise and technical knowledge, it becomes the responsibility of IT teams to handle them. They have to stay on their toes and handle these operations, and governance and control get compromised. 

4. How Adeptia’s Self-Service Integration Approach Can Help Users Overcome These Challenges?

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.