Without a doubt, businesses, either big or small, want to streamline and optimize business processes to get valuable and relevant data from different databases. Data integration is that exact solution that helps to collect data from disparate sources and combine it into a consolidated and valuable dataset providing the users with consistent access to information they need. But with rapid shifts in customer expectations and product demand, enterprises need to step ahead of their competitors looking for upgraded solutions. Often they assume that real-time data integration will be their holy grail; however, it is not always the best decision. Why? We will dive deeper later, but first, let’s define what real-time data integration means. So, this is a data integration process where data processing and transfer are carried out instantly, almost with zero time consumption.
The next question is: are you sure you need real-time data integration? Yeah, having timely information is critical nowadays, but you need to estimate the real value of real-time data before trying to achieve it. Maybe, you will get more benefits from batch processing or, perhaps, there are other near-real-time approaches that you haven’t heard before. Interested? In order to understand which data integration strategy will suit your business, you need to determine your goals and requirements. Keep reading, and we will reveal the main secrets of data integration approaches and alternative solutions to be ahead of the competition.
Real-Time Data Integration vs. Batch-Based Data Processing
Batch processing means that the data is processed as a group of transactions until a certain amount of data is collected over a period of time and organized in one transaction file, and then the batch of data is transferred. This approach is more efficient for high volumes of data, and when businesses scale.
Some organizations need real-time data integration when acting within seconds matters a lot. During real-time data integration, each piece of information is processed and transferred immediately after it is collected.
Pros and Cons of Real-Time Data Integration
Some real-time data integration is an instant, continuous, and constantly updated cycle of information, which means that when the data is changed in one system, it is immediately updated in other systems. It is perfect for organizations who need immediate data transfers. However, the source systems can be significantly overloaded. Let’s see what benefits this approach brings and how it can be challenging at the same time.
- Better business decisions and improved business performance. With real-time dashboards, salespeople get a 360-degree view of customers and a constant flow of insight, which is beneficial for more accurate predictions and efficient decision-making.
- Enhanced customer engagement. For example, once a person has performed a purchase on an e-commerce website, they get a quick thank you email.
- Elimination of double data entries. This, in turn, will significantly reduce manual errors.
- High employees’ efficiency. When you have up-to-date and valuable data, your staff can trust it and improve business performance. Moreover, there is no need to look for certain data in various systems thanks to integrated processes.
It is worth mentioning that if your data transfers are not time-sensitive, all these above mentioned benefits can be achieved even without real-time integration. For this purpose, there are many data integration tools that offer different levels of transfer frequency.
- The complex process adds load to the source and destination systems.
- This solution is expensive due to the need for IT infrastructure to be upgraded.
- Due to the large data volumes, companies need upgraded data management leading to high costs.
- For smooth data integration, data must be of high quality; otherwise, the real-time data processing will be complicated.
It is obvious how valuable real-time data integration can be, but it’s also crucial for businesses to estimate this value since instant synchronization of data sources is not obligatory for obtaining the desired results.
Near-Real-Time Data Integration Solutions as a Cost-Effective Alternative
Considering the fact that real-time integration adds load to the integrated systems, it is worth thinking of transferring not all the data, but, for example, updated or a new data. Just imagine you have the possibility to determine by yourself which data you want to transfer and the transfer frequency.
In this case, near-real-time data integration solutions like Rapidionline allow “almost” instant synchronization by using defined schedules. Being a flexible and robust solution, such data integration platforms can ensure results that will be close to real-time, thus not overloading your systems and without additional expenses. But even if you have the necessity for immediate data transfers, such data integration solutions offer a web service that will move your critical requirements for transfers in front of the queue. In a nutshell, near-real-time solutions have a combination of triggered transfers that can satisfy your specific goals and optimize your business process fully.
Nowadays a certain level of real-time data integration approach is essential for the business to stay ahead of the competition. However, true real-time integrations solutions should not always be the best solution for your bottom line. Whenever your business can afford real-time data integration and if you truly need it, it would be wise to do it. But keep in mind that this approach leads to other challenges to your business such as high costs, overloading the systems, advanced data management, and others. Fortunately, there are alternative data integration platforms that are flexible and cost-effective. The decision on which data integration approach to choose depends on your business requirements and goals, strategy, data volume, etc.