Blog > Big Data > Streaming Data Integration 101: Opportunities and Challenges

Streaming Data Integration 101: Opportunities and Challenges

Authors Photo Rachel Levy Sarfin | March 5, 2020

Raise your hand if this situation sounds familiar: you need to make a decision right away based on the most accurate, up-to-date information. However, the information resides in a number of different places across the company. So, how do you ensure that you get the data you need when you need it? The answer is streaming data integration.

Read on to learn what it is as well as the challenges and opportunities it brings with it.

What is streaming data integration?

Streaming data integration refers to integrating data sources in real time to provide up-to-the-minute information. The need for streaming data integration has emerged due to the increase in information sources – we have access to unprecedented amounts of data from mobile devices, IoT sensors, social media, and other databases that simply didn’t exist a decade or two ago. 

This form of data integration makes use of data streaming, which allows organizations to collect and analyze information in real-time. There are a number of real-time data processing technologies which enable streaming data integration.

What are its challenges?

While streaming data integration represents a leap forward in terms of technology, it’s not without its challenges. What barriers does it create? 

For a start, synchronizing information and ensuring it is consistent is challenging. In traditional data integration, data is transferred to a staging area, where it is synchronized as information sets and processed for loading into the target system. During the real-time data integration process, there is no staging area – information is brought together instantly, so there isn’t a method to ensure it’s synchronized.

Another challenge is making sure that all of the pieces are working: what ingestion to use for data streams; what to use for stream processing; what to use for delivery, alerting, and visualization; and what coding “glue” must tie all of these pieces together so that they function properly. 

Read our eBook

Streaming Legacy Data for Real-Time Insights

Learn how Precisely can help your business stream real-time application data from legacy systems, such as mainframes, to mission critical business applications and analytics platforms that demand the most up-to-date information for accurate insights.

What are its opportunities? 

Although there are challenges, there are ways to overcome those challenges and to seize the enormous opportunities that this technology represents. 

A real-time batching approach can collect information in a virtual holding pen, similar to the staging area in traditional data integration. Then, you can coordinate information migration to target systems in accordance with predefined synchronization rules.

How do you overcome the second challenge? It’s about using the right platforms and software. You need technology that allows you to run queries based on very limited information (such as the name of the database, the server on which it runs, and the tables where the relevant data is located). That way, you can get access to all of the information you need, when you need it. 

Real-time data integration is vital in today’s enterprise, and integrating legacy data brings its own challenges. See how Precisely Connect can help your business stream real-time application data from legacy systems, such as mainframes, to mission critical business applications and analytics platforms that demand the most up-to-date information for accurate insights.

Read our eBook: Streaming Legacy Data for Real-Time Insights