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What is Data Synchronization? How It Works and Why You Need It?

If you are a car driver, you know the true value of a good GPS navigation app when driving on unfamiliar roads. It automatically collects and communicates information about road situations in real-time. With up-to-the-second accuracy, you get updated on traffic, hazards, police traps, roadblocks, weather conditions and much more. Its algorithm can also calculate and suggest the optimal route. But most importantly, based on the shared real-time information and up-to-date maps, you are able to make better, more informed decisions along the way and even reach your intended destination much faster and with less stress. 

Imagine having the same real-time updates on the important data in your organization? Wouldn’t it be cool to see real-time data about every stage of the customer’s journey on the screens in the company hall? Wouldn’t it help your business get a 360-degree view of your customer without going through multiple product managers and apps?

Well, with the right data synchronization approach and strategies, you can create a tech environment that allows you to do that.

So what exactly is data synchronization?

Well, we all love apps, as they make our lives significantly easier.  And each business collects and manages data through dozens of different apps, which enable them to solve millions of problems and challenges. But it is possible to have too much of a good thing.

The same applies to apps. Let’s say you have accounting and billing software, a lead generation tool, email marketing and customer service apps, CRM, etc., used by different teams. If the apps do not “talk” to each other, their databases get disjointed and disorganized with time. As a result, you can’t generate reliable reports, have aligned goals and get a crystal-clear view of all aspects of the business. In such a case, there is no way your business can move forward and grow. It is like at a concert, where every instrument sounds ok, but the cacophony would be hard to bear when they are not in sync. 

Therefore, to be effective, your business has to rely on synched data that is consistent throughout the data record. And if data is upgraded, changes have to be reflected in other data sets and systems in real-time.

This basically means two things:

  • To be synched, the data has to be consolidated across different sources for the sake of harmony and accuracy
  • And that it’s an ongoing process that applies to both existing and new data.

Data synchronization advantages – why you need to keep data in sync 

It’s obvious that up-to-date data equals better decisions. And synchronization is something that is able to turn your chaotic islands of data into actionable insights your business will benefit from. At the end of the day, clean synced data will result in:

  • Customers getting updates on products and services that meet their needs and expectations
  • Business owners orchestrating work across teams using real-time visibility and up-to-date information
  • Executives making faster and wiser data-driven decisions and mapping out strategies
  • Stockholders staying on top of their business interests
  • Manufacturers accessing the most recent updates for accurate design and production
  • Distributors getting a clear path through the complexity of current product and marketing information.

Conversely, if you do not work out company-wide standards for data entry and maintenance, you’ll inevitably end up at risk of having:

  • Data silos (when teams, intentionally or not, isolate data from the rest of the company)
  • Conflicting information that causes miscommunication
  • Duplicates and, as a result, double effort 
  • Outdated/incorrect/low-quality data that generates blunders and mishaps
  • Too much data, as incremental data collection leads to hoarding of unneeded information, burying valuable data. 

Daunting scenarios, aren’t they?

In such situations, it is impossible to avoid mistakes, make informed decisions, prevent privacy breaches, and communicate transparently. So, data synchronization ensures your business operates smoothly and is able to scale.

Exploring data synchronization methods

The main aim of data synchronization is to ensure that two or more locations contain the same, up-to-date, data. Suppose data is modified in some way (edited or deleted) in one location. In that case, the synchronization process will edit or delete the corresponding data at the other locations, so consistency is maintained. There are many ways in which data can be synchronized but all these techniques can be divided into a few types:

  • File synchronization is most used for home backup external hard drives or updating mobile data on flash drives, Dropbox or similar products. It is much faster and less error-prone than manual copying and prevents duplication of identical files. Some backup software also supports real-time file sync. However, you always have to consider the limit that the synchronized files must physically fit in the portable storage device. 
  • Version control, also known as VCS, allows tracking and managing changes to the codebase over time and storing these modifications in a database. It enables many contributors to modify the same file simultaneously without overwriting or conflicting with each others’ work. It ensures access of every team member to the latest code and a restore option for any previous version of the application. Most hardware and software development teams use version control today.
  • Distributed file systems (DFS) function differently from typical files systems (e.g. NTFS), offering access to the same file data from multiple locations. For example, it is used in a hybrid cloud solution that requires access to the same data. Depending on the protocol’s design, a DFS makes it possible to share information in a controlled and authorized way. It is also believed to be error-proof in case of network breakdowns since the server provides a single central point of access for data requests. Most DFS systems support encrypting data and metadata while it is in transit.
  • Mirror Computing is used to provide the exact copy of a data set just in a different location, whether it is one or several files, a database, a website, or even an entire server. Designed for the sake of backups, mirroring can also be used for planned maintenance, such as upgrading a server or performing software updates that require a restart of the service.

Data synchronization algorithms

For sure, the complexity of sync and choice of the synchronization method widely depends on the use case. It is always influenced by the amount of data, data changes, synchronous/asynchronous sync, a number of devices, and decision on what kind of client-server or peer-to-peer setup is needed. But whatever way you choose, from manual updates to scripts or to a fully automated sync using an ETL system, in all instances data synchronization follows these steps:

Data synchronization steps

  1. Update event is triggered. Whichever way you choose, either the flag in the table or a script that regularly checks the last modified date, the main idea is still that the data synchronization process will detect a change to one of the data instances. 
  2. Changes are identified and extracted. Synchronization doesn’t equal full replication. Therefore, the next step is to identify where changes have been made. This is done by version comparisons, checking changelogs, and looking for flags that indicate a new value.
  3. Transfer changes. The changes made can be passed from the source to the target source in two ways:
    1. Asynchronously: Changes are applied on a set schedule, for example, once per hour. This approach is more resource-efficient, but errors may occur between updates.
    2. Synchronously: When a change occurs, it starts the synchronization process. Though more resource-intensive, this approach allows for real-time updates.
  1. Parse incoming changes. If the two data instances are not identical, they must pass through transformation processes, such as cleansing and harmonization. 
  2. Apply changes to existing data. In this step, the incoming changes are applied to the other data source. Changes can be addressed one by one in the same order that they initially occurred (Transactional method), in aggregate (Snapshot), or if changes occur on both sides, then the changes are merged (Merge).
  3. Confirm update success. Lastly, the updated system should confirm the successful application of changes. If the update is done by API, for example, it will return a success confirmation message. 

Data synchronization tools

How do you reach synced and harmonized databases? It can be done by a native integration offered by the vendors of the apps you’re already using, custom integrations like an in-house development created for your company’s specific needs, third-party integration platforms, or Integration Platform as a Service (iPaaS) providers.

Native integrations can be great for common automation use cases, but usually, they only work one way. Custom integrations can achieve a bidirectional data sync in real-time, however, in-house development is costly and time-consuming. 

iPaaS, cloud-based solutions, specialize in integrating business tools. Unfortunately, not all of them work best for data synchronization. 

Let’s take a look at one example of an iPaaS solution – It is a no-code sync app supporting Google Sheets, Excel, and BigQuery as destinations for the data. It automates data integrations, allowing users to sync apps on a set schedule for automatic data refreshes. It gives a live feed of raw data in a simple format that allows you to access and share it easily. also supports data stitching. supports both web and Google Sheets add-on versions and offers multiple plans depending on your data needs. Additionally, you can benefit from a data analytics consulting service that is created to satisfy your most sophisticated data management requirements.  

Available Google Sheets integrations include Airtable, Jira, HubSpot, Pipedrive, Shopify, Slack, and many others. In addition, you can leverage to establish Excel integrations and BigQuery integrations

And, of course, this enables further data analysis by connecting your spreadsheet directly to Google Data Studio, Power BI, Zoho Analytics, Qlik, etc., to build live dashboards based on information from your data sources. It is a simple but powerful solution that gives 100% flexibility for reporting. 

Data synchronization best practices

To dive deeper into data synchronization, there are several approaches used when designing an application or system. All of them have their specific application cases, as well as individual pros and cons. 

The answer to the question, “When should an application sync data?” can be of two types.

Types of data synchronization

Synchronous (Request-Reply) is an approach used for rendering information in front of a user in real-time. A common protocol for this exchange is HTTP(S), though other protocols are possible, as well. The intent is to block the user interface while the data sync is occurring in the background. For example, suppose you have an application with a monthly subscription. In that case, it is a good practice to block full access to the functionality of the application until the subscription activity is clarified.

Asynchronous is a type of synchronization where the data does not have to be moved immediately but can be moved later. This means that the system sending a request doesn’t have to wait for a reply to continue operating. 

The advantage of this approach is that the user interface is not blocked during the process and is suitable for syncing large volumes of data. For instance, when syncing data between a CRM and ERP system, when a sales manager enters new information, the CRM system would spot the change and send a request. At a later time, the data will be synced to the ERP system. It doesn’t really matter when the update happens.

To break things down even further, it also matters whether a ‘smart’ server is involved or whether the process is peer-to-peer, with the client apps handling all of the complexities. 

Let’s have a look at a simple grid to understand the differences.

  • Simple to implement
  • First to gain popularity (used by iPods and still used by iTunes)
  • Suitable for large quantities of media transfer
  • Uses fast local networks
  • Grew in popularity when networks improved and cloud services improved (e.g. AWS appeared)
  • Today’s most common approach to syncing
  • It’s ‘always on’ and the client can sync from any location
  • Requires stable network connectivity
  • Processes slowly
  • Asynchronous
  • Still in its infancy and not widespread
  • Each device has a full copy of the data store and those stores are kept in sync by communicating changes between devices via a series of files (transaction logs)
  • The logs are moved to the cloud and from there to other devices by a basic file handling server (e.g. iCloud, Dropbox)
  • It’s the most difficult to implement
  • An API for data storage is adopted which gives access to a local copy of the data
  • Syncing occurs transparently in the background with the application code being informed of changes via a callback mechanism
  • Apps continue to work and have access to the user’s data when the network is unavailable
  • Top data synchronization challenges

    Data synchronization doesn’t sound like rocket science, but maintaining healthy data across all on-premises and cloud systems is not easy. Anyone, company-wide, who is responsible for synchronization would face many challenges. Let’s consider the most common ones:


    Security and confidentiality in regard to data syncs are non-negotiable issues. With remote work becoming the ‘new normal’ and businesses demanding even more flexibility, it gets particularly challenging to ensure that there are no data breaches or leaks. So, your synchronization tool should ensure that data updates and transfer meets the regulatory standards based on your specific security needs. Access permissions should be set with correct policies, controls, and parameters, while data encryption methods must be compliant and consistent within each system. 

    If overlooked, weak security can lead to misuse of information and, as a result, loss of reputation and customers.

    Data quality

    Multiple apps used by multiple teams make it mission-impossible to cooperate effectively without a solid sync solution. If you sell smartphones, for example, you probably have purchasing and inventory systems, customer support, and marketing tools. Without a seamless synchronization system in place to reflect up-to-the-minute accuracy of your smartphone selling there are bound to be breakdowns. Consumers would be disappointed, and you will not see the real picture of the health of your business. Regular synchronization of sources and targets frequently improves the value of your data and, therefore, validates your decisions.

    Data complexity and compatibility

    The more data, the more complexity. Data amount grows simultaneously with the business, as well as data formats change and increase with the addition of new employees, vendors, customers, and products. This may cause an issue when trying to appropriately interface data in new situations with old systems. 

    Real time updates

    You would feel disappointed if, with modern tech opportunities, you are not able to check the status of your order, track your international delivery, or learn your current account balance in real-time. Real-time automated data synchronization is not an advantage anymore, it is an unchallenged feature without which your sync solution would be useless.

    The main challenge of real-time data synchronization is to work with systems that do not provide any API to identify the changes. In such a case, special attention should be paid to performance.


    Data synchronization involves a high frequency of data extracting, transforming, and loading. So, capacity should be planned properly, especially for large data volumes, to avoid a negative impact on the system at peak times.


    Like with any other process, the synchronization process needs to be tracked and managed properly to ensure it is running as scheduled and properly handling errors. 

    How offline data synchronization works

    One more challenge with data synchronization, which deserves special consideration, is the issue of an offline mode. The complexity of modern applications, such as geodata for maps or speech and image recognition, makes it virtually impossible to use them without reliable network coverage. Besides, many businesses need their employees to be able to use data offline. But what if constant online access is unavailable? 

    For example, Notion is often criticized for the absence of an offline mode. Trello, conversely, listened to its users and implemented this most-asked-for feature in 2017. All this makes offline data synchronization a critical feature for many apps and a definite competitive advantage if you develop GPS navigation, medical or banking solutions. 

    As usual, there are many strategies but no one-size-fits-all solution. For offline data syncs, it is essential to consider:

    1. Frequency of data synchronization. If the business requires syncing geodata for large regions or thousands of work orders, it is important to consider data the frequency of data synchronization. If synchronization happens too often, the device battery can run out; if too seldom, users can miss some essential updates. So it is vital to find an effective middle ground for update frequency depending on the situation. Analytics and user behaviour research on the frequency of access to a reliable Internet connection and users’ typical working time slots can come in handy for this purpose. 
    2. Data synchronization cycles and time. Some data should be updated every hour while other data requires only monthly updates. All business rules should rely on the specific needs of the business .
    3. Managing changes in shared data. In offline mode, users modify data without seeing modifications initiated by other users, so it is necessary to set rules on how to handle such cases. For example, deciding that the first update takes precedent and ignoring any other updates to the same data set.
    4. Handling sensitive data. It is important to pay attention to the security of user sensitive data, for example, credit card details.
    5. Patterns of syncing. It is also necessary to decide which method of syncing is most appropriate for you (synchronous/asynchronous, automatic/manual, client to server/peer-to-peer).

    The true value of synchronization of data

    $150 is how much your personal data cost 10 years ago,” claims cryptographer Dr. Maria Dubovitskaya in her TED speech. For comparison, now it is worth less than a dollar. And this applies not only to personal information. Data, in its essence, is getting cheaper. What makes data valuable is not merely its availability but its quality, accuracy, and ability to be analyzed in the future. Only such data can become a precious business asset and navigate you through decision making, ensuring it’s really data-driven. A solid synchronization system can ensure your business data is being used to the fullest for the benefit of your company. With your tools and systems “talking” to each other you’ll:

    1. Gain operational efficiency through transparency
    2. Make better use of resources with automation
    3. Reach new audiences with segmentation and customization
    4. Improve customer satisfaction with customer 360-degree view
    5. Innovate through augmented research and development 

    Bright prospects, aren’t they?

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