Data is an integral part of organizations as it helps them drive innovative insights, discover trends, and create new strategies. From customer details, survey reports, financial records, and social media information, valuable data is scattered in multiple forms across diverse platforms.
However, with rapidly expanding data, businesses might face issues like inconsistencies, inaccuracies, and data silos. To deal with such problems, you can leverage data synchronization. It allows you to remove data discrepancies, errors, or silos, ensuring your data remains accurate and consistent.
Let’s delve deeper into what is data synchronization, its various types, benefits, examples, and different tools you can use.
What is Data Synchronization?
Data synchronization is the process of syncing data between multiple systems and constantly updating changes between them to ensure consistency. It is the process of concurrently updating data at different locations to maintain data accuracy, reliability, and compliance.
With synchronized data, you can see every facet of your enterprise data with clarity. You are able to gain actionable insights, verify facts and figures, and arrive at a plausible conclusion. This, in turn, empowers you to collaborate effectively with your team, thereby making informed business decisions.
Types of Data Synchronization
There are primarily two types of data synchronization that you can employ based on your business requirements, and they are:
One-Way Data Synchronization
One-way sync, also known as uni-directional synchronization, facilitates the transfer of data from the source to the destination without impacting the source dataset. This method ensures that the data stored in the target system or database is up-to-date and consistent with the data source.
Some of the benefits of using the one-way sync method are:
- Using this method of synchronization is cost-effective as compared to two-way sync as it requires less computational resources. This makes it a preferred choice if you have a small or medium-sized enterprise.
- Since data movement takes place in one direction only, it eliminates the risk of source data being corrupted or manipulated. This, in turn, ensures that data integrity is maintained throughout its lifecycle.
Two-Way Data Synchronization
Two-way sync, also known as bidirectional data synchronization, aims to modify and update data in both source and target systems. You can choose to edit, insert, or delete information in either system, and it will be reflected in both sources.
Some of the benefits of using the two-way sync method are:
- Two-way synchronization facilitates maintaining data consistency across all platforms by allowing you to update data in source and destination systems.
- This method of synchronization enables you to gain a comprehensive view of your customer data, thereby empowering you to create customized solutions, increase customer satisfaction, and improve overall experience.
Benefits of Data Synchronization
Data synchronization offers several benefits that can significantly improve your data management practices. Let’s discuss them in detail:
Effective Data Management
Data synchronization helps significantly increase your organization's data management efficiency. It automatically syncs data stored across multiple platforms within the enterprise, allowing you to spend less time fixing errors or bugs and more time analyzing them.
Reliable Decision Making
If the data stored in your systems is not updated or synchronized, you might end up using incorrect or old information, thereby leading to inaccurate decisions. However, with data synchronization, you can leverage the flexibility of making data-driven decisions as it provides real/near-real-time data for analysis.
Near or Real-Time Data Sync
One major advantage of synchronizing data is that you can access near-real-time updates. You can use incremental sync to continuously update your data between source and destination systems. This, in turn, allows you to collaborate effectively with your team and draw actionable insights in real time.
Data Synchronization Examples
Some of the most common examples of data synchronization are:
1. Sync in Distributed Computing Systems
Data synchronization is significant for distributed systems if your data is stored in multiple locations. This ensures that your data is synced and you have access to the most recent version of your data across systems.
For instance, if you work on cloud devices like OneDrive or DropBox, you can create projects on one device, save them in the cloud, and open them on a different browser or application. The cloud server ensures data updates on all the linked devices and captures and stores any modifications made to your data.
2. Employee Data Sync
YYou can leverage data synchronization to sync the data of newly inducted employees as they move through the candidate journey. When hiring a new candidate for your enterprise, you must store their information in HRIS, such as name, address, email ID, job title, and department. You can employ unidirectional data sync to store this information and share it across the organization.
3. Sync for Supporting Data Harmonization
The primary aim of data synchronization is to facilitate data sync between source and destination systems to maintain consistency. For instance, for an e-commerce platform, it is essential to have updated customer information stored in its database and other applications.
This is where data synchronization can help your team to ensure that whatever data customer updates are reflected in other applications, enabling smooth operations.
Data Synchronization Tools
In this section, you will learn about some of the best tools you can use for data synchronization:
Airbyte
Airbyte is a cloud-native data integration and replication platform. It allows you to effortlessly extract data from disparate sources such as flat files, databases, and SaaS applications. Once this data is collected, you can it into the destination systems of your choice, such as a data lake, database, or warehouse.
In addition to integration capabilities, Airbyte also provides different ways to keep your data in synchronization. You can leverage incremental sync to replicate data that have been updated in the source system since the last synchronization. This functionality empowers you to keep track of your data and ensure consistency across systems.
In contrast, it also supports full refresh, which aims to replicate the entire data from the source system. This enables you to retrieve all the data from the source and copy it into the target system, irrespective of whether the data was previously synchronized or not.
Some of the unique features of Airbyte are:
- Connectors Catalog: Airbyte provides a rich library of 350+ pre-built connectors to automate your creation of data pipelines. If you cannot find a suitable connector in this catalog, you can build customized ones using CDK.
- Developer-Friendly UI: With Airbyte’s newly developed open-source Python library, PyAirbyte, you can enhance pipeline development capabilities. It allows you to extract data from various sources using Aibryte connectors programmatically.
- Advanced Transformation: Integrating with dbt enables you to execute complex transformations and make your data analytics-ready. Airbyte allows you to leverage dbt to perform SQL-based transformations on the data stored in the destination system.
- Security Features: Airbyte offers multiple security features to safeguard your data from unauthorized access. These measures include audit logs, access control, encryption in transit, credential management, and authentication mechanisms.
- Vibrant Community: Being an open-source platform, Airbyte supports a large and vibrant community of 15000+ members, constituting developers and engineers. You can engage within the community to discuss best integration practices, resolve queries, and share articles or resources.
Fivetran
Created in 2012, Fivetran is a cloud-based data integration, replication, and governance platform. It enables you to leverage the ELT method to gather data from multiple sources into a central system. Fivetran also offers an extensive library of over 500 pre-built connectors to automate data pipelines.
With Fivetran, you can simplify your data syncing between systems. It employs a log-based CDC that allows you to capture changes in the source and replicate them in the target system via a simple setup.
Skyvia
Introduced in 2014, Skyvia is a cloud-native data integration and synchronization platform that uses a no-code methodology to move data. You can perform different integration processes such as ETL, ELT, or Reverse ETL for migrating data from the several sources to the destination.
With Skyvia, you can create a synchronization package for bi-directional data sync between relational databases and cloud applications. It also allows you to synchronize data with different structures, protect all data relations during transfer, and support robust mapping settings to configure your entire operation.
Hevo Data
Hevo Data is a cloud-based data movement platform that was developed in 2017. It lets you collect data from more than 150 data sources like databases or SaaS applications and transfer them to 15+ destinations. You can easily build data pipelines using its no-code methodology to facilitate efficient data integration.
In addition to integration, Hevo Data supports data replication features such as Change Data Capture. You can employ CDC functionality to effortlessly track data changes from your source file and copy them into the target system.
Data Replication vs Data Synchronization
Till now, you have understood the importance of data synchronization and how its implementation can streamline your business workflows. But when implementing this process, you might often get confused between data replication vs data synchronization.
Though these terms are related to each other, their end goal is different. While data replication can be performed independently, to achieve data synchronization, you have to perform seamless replication.
Final Words
This article has comprehensively covered the concept of data synchronization, its benefits, examples, and some of the popular data sync tools. Implementing a robust data synchronization process within your enterprise can empower you to make data-driven decisions and improve business workflow.
As your business expands, the volume of data will increase drastically. Therefore, it is advisable to incorporate data sync tools and techniques to leverage your datasets. This helps you gain better insights, identify trends, design customized solutions, and deliver streamlined services.
Frequently Asked Questions
Why is data synchronization important?
Data synchronization is imperative for your organization as it ensures that accurate, updated, and consistent data is available across all the systems. This empowers your team to access present data and work collaboratively.
What are data synchronization tools?
Data synchronization tools are an integral part of your sync process as they enable you to identify and update changes in your dataset. This, in turn, allows you to work efficiently with your data and perform seamless analytics.
What is incremental sync?
Incremental sync is a method in which you can update the data from the source to the destination since the last sync.
What is the difference between data synchronization and data integration?
The data synchronization method is used to update data in a dataset to ensure its consistency in multi-device environments. Data integration, on the other hand, allows you to consolidate data from several sources into a single destination.