Michael Chen | Content Strategist | April 24, 2024
Data synchronization is the process of keeping data consistent and up to date across multiple devices or systems. With successful data synchronization, organizations can be confident that all decision-makers are working with the same—current—information. Without data synchronization, a team may be debating choices informed by inaccurate information, which could feed faulty assumptions that lead to poor outcomes.
The use of cloud data storage has made data synchronization simpler by providing a central, accessible platform for storing and sharing information. But there are still variables to consider.
Data synchronization is different from data integration, though there is a tangential relation between the two. Data integration refers to joining multiple data sources into a single repository for use by various devices and applications such as business intelligence. Data integration focuses on centralization, while data synchronization focuses on a unified view for data consumers. Both processes are about improving data accuracy and utility. When an organization uses both data integration for a central repository and data synchronization for devices, decision-makers get highly accurate and timely information.
There are two ways that data synchronization can be accomplished.
Data synchronization is the process of keeping data consistent among systems, even when it resides in different databases, devices, or storage repositories and is used for different applications. Data synchronization is particularly important when multiple teams or applications need access to the same data and when changes made to that data need to be reflected across all systems in real time. Synchronization efforts work to help ensure data integrity, minimize the risk of data loss or duplication, and help facilitate collaboration and decision-making.
The four main types of data synchronization are as follows:
Data synchronization delivers business benefits. Having all employees work with the most up-to-date data leads to better decision-making and fewer errors. Additionally, data synchronization allows for better collaboration among teams and improves customer experiences by placing accurate and consistent data across all touchpoints.
AI works harder and better for your business when the data it depends on is accurate, timely, and accessible. A data sync strategy can help.
How does data synchronization work?
Data synchronization works by updating data stores across a variety of devices so that they contain the same data. With data synchronization, updates occur automatically, either as new data becomes available or on a regularly scheduled cadence. Examples of data synchronization include updating inventory information or product catalogs across systems that need that data.
Why is data synchronization important?
Data synchronization is important because it seeks to ensure that all systems use the latest, most accurate information. It can help facilitate productive collaboration and communication among different teams and departments, reduce the chances of errors from discrepancies in data, and contribute to effective backup and data recovery.
What types of data synchronization exist?
Data updates may be synchronous or asynchronous, and implementing systems will typically come with version-control mechanisms. Synchronization may happen at the transaction level; file level; or at lower levels within storage systems, such as at the block level.
What are the benefits of data synchronization?
Data synchronization benefits organizations by helping ensure that applications and stakeholders are working with accurate, up-to-date information. It can contribute to organizational trust because all users can count on the accuracy and timeliness of data.