Types of data synchronization
There are different types of data synchronization that can ensure the information you collect is consistent across multiple platforms. A few examples include:
- Two-way data synchronization: This refers to synchronization that takes place between mobile devices and personal computers. If you make a change on your mobile device, the change should automatically happen on your personal computer as well.
- Server-alerted synchronization: If there is a change made to the data on your server, you may automatically get an alert. Then, you can execute the computer command to synchronize your data.
- Server-initiated synchronization: This type of data integration occurs when the server detects changes in the data set. When the server detects the change, it will automatically send out a signal to all other connected devices and make the change in the data accordingly.
- Client-initiated synchronization: Finally, some data synchronization methods take place entirely through the client. When the client makes a change, they may execute a command to automatically refresh the information across all programs.
With access to an automated workflow, you can shorten the time it takes to synchronize your data across multiple platforms and devices. Having an automatic synchronization tool saves time and energy, and it allows multiple users to work on different computers because they'll all have access to the same real-time data.
Why is real-time data synchronization important?
Real-time data synchronization is important because you need to know when changes are made to the information you use daily. Numerous platforms can be used to track and store data in real time. A few examples include personal computers, mobile devices, websites, and even mobile apps.
If changes are made to the data on any of these platforms, that needs to be immediately reflected. That way, you know you are working with the most recent and accurate data set.
If you don't have access to clean, consistent data across all your platforms, how can you know which set of data is accurate and up to date? With data syncing, you can maintain data integrity across various formats.
Data integration is also important for regulatory issues. Both security and regulatory compliance hinge on the accuracy and consistency of your data. For this reason, data synchronization in the cloud is crucial for data security purposes.
Common challenges of business processes
As you learn more about how to synchronize data, you will come across a few common challenges. Some of the biggest challenges related to data synchronization include:
Lack of consistency in data
Without a doubt, one of the biggest challenges related to data synchronization is a lack of consistency in how data is entered and stored. You may have a lot of people responsible for entering data into various databases, but do you have a uniform process regarding how people should store their data?
If the data is not consistent, you may have a difficult time extracting any meaningful insights from that specific data set. You need to ensure that everyone on the team enters data in the same way. This will make it easier for you to synchronize that information with other platforms.
Inefficient data management
Your data has to be organized, managed, and integrated in real-time to ensure it is accurate. If you do not have effective data management, you could have rejected records due to formatting errors.
For example, your customers might call or email you, asking for information related to the estimated delivery date of their orders. But the only way you can tell your customers the exact delivery date is if your data is synchronized in real-time. If your data is not managed efficiently, you will have difficulty meeting customer expectations.
Inaccurate decision making
Finally, inaccurate decision-making is also a very big issue related to business processes. If your data is not accurate, the decisions you make will not be accurate either.
You need to make sure that decisions are made based on accurate data, and that is why data synchronization is important. If you do not synchronize your data, your team will not be able to make decisions based on accurate information, putting you at a disadvantage.