Real-Time Data Integration Best Practices

According to a recent report, the average enterprise has 464 custom applications deployed today. And the number of custom applications they use to interact with their customers, employees and partners increases every month. From data silos to legacy code and skills shortages, the modern enterprise faces persistent data integration automation demands that threaten to undermine its digital transformation initiatives. According to a Deloitte survey of IT managers, organizations  today have only 28%  applications integrated.

It is perhaps, for this reason, business leaders are looking into  embedding API strategies focused on improving data integration.  They recognize that combining API strategies with automation might be the best data integration solutions. They may offer the best chance of delivering better customer experiences for their employees, customers, and partners.

What Is Real-Time Data Integration?

Real-time data integration refers to capturing data the moment it is generated and ensuring it is available in the target system(s) for processing as soon as possible. This data can come from various sources, including websites, social media, sensors, and devices.

Challenges in Data Integration

Here are some of the most common data integration automation challenges enterprises face today:

1. Disparate data sources and formats

2. Lack of data governance

3. Poor data quality

4. Lack of real-time visibility into data

5. Lack of integration between legacy systems and new applications

6. Silos of information making it difficult to share data across the organization

7. Lack of standardization

8. IT skills shortage

9. Not enough resources set aside for data integration

Real-Time Data Integration Best Practices and Architecture

To overcome these challenges, enterprises must follow best practices and implement a working real-time data integration architecture. Here’s a simplified process  organizations can use to get started:

1. Define the business need for real-time data integration

2. Identify the data sources

3. Clean and prepare the data

4. Choose the right architecture

5. Design for fault tolerance and scalability

6. Test and deploy

7. Monitor and optimize.

The Takeaway

Integrating data in real-time is essential for enterprises that want to stay competitive in today’s digital world. By following best practices and putting in place a working real-time data integration architecture, organizations  can overcome data integration challenges and improve their digital transformation initiatives.

The Put It Forward data integration solution helps to integrate on-premises and cloud-based data sources and applications without any coding. With its help, organizations can access hundreds of pre-built connectors and auto builders to go faster, combine data and access the up-to-date data in a single working platform.

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