The name itself sums it up: real-time data integration refers to near instantaneous processing of data as itโs collected. Data integration architecture facilitates gathering and combining information from various sources and unifying it into a consolidated view. Doing this in real-time means organizations can extract the most value possible by gaining insights from events as they occur.
The Benefits of Change Data Capture
In the digital-first world we live in, data availability is seemingly endless. While this can lead to insight overload, there is a unique opportunity for organizations to parse information and use the resulting data insights to make better business decisions, fine-tune strategies, and improve customer experience.
Yet, timing is everything. To truly make data an ally, organizations must be able to learn from and act upon information swiftly. That is the importance of real-time data integration: moving at the speed of business.
Of course, not all data requires real-time processing. Batch processing is still viable for processes that donโt require immediate transfers and analysis. Yet, processing all data using batch processing methods requires resources for collecting, storing, and processing on a cadence and, in some cases, manually. Real-time digital data integration frees up expensive storage space and eliminates the need for manual intervention.
The Benefits of Change Data Capture
Event-driven architecture delivering real-time data integration methods has many advantages to departments and organizations that rely on data insights. Yet, there are some disadvantages to real-time processing to be aware of.
Setting up a data integration hub requires hardware and software built for the purpose and can increase complexity and cost for organizations at the onset. Processing data can also place a heavy load on systems and networks as real-time methods require real-time data transfers. Improperly managed, this can lead to challenges in real-time data integration performance, including delays, processing lags, and potential system crashes.
Data and security concerns go hand-in-hand, particularly when cybercrime is rising at unprecedented rates. Security and privacy concerns should be front of mind when designing and implementing a real-time data integration solution to mitigate risk, prevent data breaches, and control access effectively.
Due to the rapidity of processing, real-time methods carry a higher risk of errors. While some data types may be more forgiving or less dependent on highly-detailed outcomes, this risk is particularly notable in industries such as healthcare and stock or currency trading.
