Your employees often view the same set of data across different applications.
Your marketers might view leads in a marketing automation platform while your sales reps view them in a CRM; your HR team might track employee information in an HRIS while IT tracks it in an ITSM; your finance team might review sales orders in an ERP system while your customer-facing employees review them in a CRM—and the list of examples go on.
Having the same record types appear across applications is clearly essential, but the process of manually re-entering data in applications leaves employees prone to errors that create data discrepancies between systems.
This results in misalignment and friction among functions, individual teams being misled into making poor decisions, and business-critical reports becoming inaccurate. Given these consequences, it’s perhaps little surprise that poor data quality costs organizations millions of dollars every year.
Data synchronization neatly addresses this issue, as it all but ensures that the data across your apps is consistent and accurate—assuming you’re working with error-free source systems.
To help you fully understand data synchronization, we’ll go on to define it, review common examples, explore its benefits, and share how it can be implemented.
Implement data syncs with ease by using Workato
Workato, the leader in enterprise automation, lets you implement data syncs without having to write a single line of code.
Data synchronization definition
Data synchronization, or data sync, is the continual process of keeping a record type identical between two or more systems. This can be done in real time, in near real time, or in batches.
Types of data synchronization
Your synchronization process can work in one of two ways:
One-way data sync
A one-way sync is simply when changes in the source system lead to changes in downstream systems, but not the other way around.
To help illustrate this definition, let’s use an example. Say you use a CRM as the source system and an ITSM tool as the downstream system, and you decide to synchronize the record types below. As a result, when a customer record, issue summary, or case number get modified in the CRM, the information in the corresponding ITSM records change accordingly. The inverse scenario—where changes occur in the ITSM tool’s records—however, doesn’t affect the CRM’s records.
Two-way data sync
A two-way sync is when changes in either the source system or a downstream system lead to changes in the other systems.
Now, let’s use the same example from before but in the context of a two-way synchronization. In this scenario, it doesn’t matter which serves as the source and which serves as the downstream system. Whenever a synchronized record changes in either the CRM or ITSM tool, the corresponding record in the other system changes accordingly.
Finally, while it’s hard to generalize, the type of data that’s synchronized typically lives in a master data set. It’s also data that usually changes less frequently and that gets managed through a lifecycle.
With this data synchronization definition out of the way, let’s explore some common use cases.
Note: Information synchronization is often used interchangeably with data synchronization. For all intents and purposes, they share the same meaning.
Common data synchronizations
We’ll illustrate the points above by walking through a few real-word examples:
1. Syncing employee data
The process of adding a new hire into your systems typically starts by adding them into an HRIS; where information like the employee’s first and last name, their email address, job title, and hiring manager get added.
Let’s say that a CRM is one of the downstream apps that needs employee information. You can build a one-way data sync where any time employee data changes in the data source (your HRIS), the corresponding changes take place in the CRM. Conversely, you can build a two-way data sync that behaves like the above AND allows for changes in your CRM to also lead to corresponding changes in your HRIS.
Related: What is integration middleware?
2. Syncing incident data
When two companies have a product that’s closely intertwined, they’ll likely want to track issues in their respective incident management platform; that way, the teams at each organization can keep tabs on any issue and, when appropriate, work to resolve any.
You can create a data sync that allows each company’s ITSM tool to be in line with the other. More specifically, you can build a two-way data sync where any time one company creates an incident in their tool, the other company’s tool also receives it. This allows the two teams to coordinate and work on resolving the issue faster.
3. Syncing customer data
Once a new client and their info gets added to your CRM, that data will likely need to be made available in a variety of other apps. These include customer success apps, reporting and analytics tools, marketing platforms, finance systems, etc.
Though it often depends on the company and situation, customer data is often better suited for a two-way sync. Why? Because a variety of functions that perform activities in apps outside of a CRM might uncover information or run into issues that require visibility from those that work in their CRM.
For example, an employee in finance might have trouble with invoicing a client. Using a two-way sync, they’d be able to create a case in their ERP system (highlighting the issue) and have the case also populate in the CRM. There, the sales rep can become aware of the invoicing issue and take action quickly.
Related: What is an ETL tool? And how is it different from an iPaaS?
Benefits of synchronizing data
Given these use cases, among countless others, it’s perhaps little surprise that synchronized data brings a wealth of benefits to the business.
Data silos are removed
Now that employees can access the data they need in the apps they work in, they can avoid the tedious process of requesting access to it—or worse, being unaware that the data even exists.
Extensive data entry can be prevented
The process of inputting data manually isn’t just unpleasant for employees. It can also lead to human errors that impact data quality, whether that means employees input incorrect information or forget to input it at all. In response, employees are forced to perform a substantial amount of rework, which takes them away from other business-critical tasks.
Data synchronization ensures that employees don’t have to re-enter data across apps, and in doing so, it allows them to avoid the negative consequences highlighted above.
Several data operations can be performed
These include creating records, updating them, and deleting any.
By leveraging a combination of these operations across your apps, your data syncs can drive even greater value to your employees and the business.
Data can be synced in near real-time
While syncing data in batches might suffice for certain situations, near real-time synchronization is often invaluable for executing business processes successfully.
Real-time data synchronization allows sales and finance teams to collaborate more effectively in managing deals, it empowers product and customer support to resolve issues faster, etc.
Related: What is reverse ETL?
Data synchronization challenges
Common challenges of data synchronization include scalability issues, security risks, and performance limitations.
Let’s take a closer look at each issue:
Scalability issues
As we’ll cover further in the following section, many of the approaches for implementing and maintaining data syncs are resource-intensive. They require your developers to get involved and invest a significant amount of time—when, instead, they need to be focused on core product initiatives.
Since your organization likely needs to implement and maintain dozens, and, eventually, hundreds of data syncs, this may prove difficult, if not impossible.
Security risks
The applications you’re connecting and the data synchronization flows you build likely have sensitive, business-critical information.
If the 3rd-party or in-house solution you’re using to connect these systems and implement these syncs fail to provide sufficient security and governance controls, sensitive data can easily fall into the wrong hands and be used in ways that compromise your business.
Performance limitations
While data synchronizations are, clearly, valuable, they only streamline the process of sharing information between applications. They also don’t provide the prescriptive guidance your employees need to take action off of the data.
For example, if you’re syncing cases in your CRM with incidents in your ITSM tool, your support team (using the latter) might not know how to immediately respond to these issues. And even if they do, their responses might require them to take additional steps that are manually-intensive, which prevents them from providing a speedy resolution.
How to synchronize data
Once you’re bought into synchronizing your data, you’ll need to think through the different solutions that can help you implement any sync.
Here’s a breakdown of each solution:
1. Custom coding
This approach relies on your developers using custom code to sync data.
This method is helpful in that it allows you to avoid working with and relying on third-parties. However, your engineers will have to dedicate a significant amount of time on implementing and maintaining these data syncs, taking them away from other business-critical work that they’re uniquely suited to perform.
2. Native integrations
This involves using an application’s pre-built integration and data flow with another application.
This can be cost-effective, as the app vendor that provides the integration may offer it at a low price-point or even include it within your subscription. Also, depending on the data sync you’re looking to build, it may meet your requirements.
That said, there’s a good chance the vendor doesn’t offer out-of-the-box connectivity with all of the applications you’re looking to connect. And even if they do, these integrations may not connect to the endpoints you need.
3. Robotic process automation (RPA) software
RPA software lets you sync data by, essentially, using software scripts, or “bots”, to copy and paste data between applications on the UI level.
This can meet your requirements in the short run, but it’s likely to present issues over time. For example, something as simple as changing the name of a particular field or object can be enough to break the integration. Even moving a field or object to a different location within the UI can cause the data sync to break. In addition, the “bots” require technical expertise to implement and maintain. Similar to custom coding, this makes RPA software difficult to scale.
4. Integration platform as a service (iPaaS)
An iPaaS can help you implement data syncs by integrating applications at the API-level. This provides greater stability than UI-based integration, as changes to one of the application’s UIs won’t cause the data sync to break. Moreover, an iPaaS offers high performance, as APIs allow you to to implement data syncs that work in, or near, real-time.
An iPaaS solution also typically provides a wide range of application connectors and automation templates, which can help your team implement integrations quickly and without having to involve developers.
It’s worth noting that iPaaS vendors can vary greatly across dimensions like ease of use, the use cases they address, and the quality of support they provide, which means you’ll need to evaluate your options carefully.
Use Workato to sync data at scale
Workato, the leader in enterprise automation, offers a low-code/no-code platform that allows your team to implement data syncs without the use of developer resources, giving them bandwidth to focus on other critical areas.
In addition, our platform can perform the syncs via triggers that use webhooks or polling; where the former allows you to perform syncs in real time when the trigger event takes place, while the latter allows you to perform it in near real time at predefined time cadences (e.g. every 5 minutes).
Implement data syncs with ease by using Workato
Workato, the leader in enterprise automation, lets you implement data syncs without having to write a single line of code.
Data synchronization FAQ
Data synchronization can elicit a range of questions. In case you still have any left unanswered, we’ll address a few more below.
What’s the difference between real-time and near real-time synchronization?
These definitions are often subjective, but generally speaking, real time involves synchronizing data between systems within milliseconds or single digit seconds, while near real time can be measured in seconds or in single digit minutes. Batch synchronization, meanwhile, can be performed over a longer range of minutes (e.g. every 30 minutes), or in hours or days.
What is the difference between data synchronization and data backup?
Data backup involves taking snapshots of data on a specific cadence (e.g. daily snapshots), allowing you to restore it to the form it took in a specific period. Data synchronization, meanwhile, doesn’t perform data backups as its goal is to keep systems in sync.
How does data integration relate to data synchronization?
The definition of data integration fundamentally differs from data synchronization’s.
Data integration involves taking data from a variety of sources, validating it (to remove redundancies and inaccuracies), transforming it (to fit the data model used by the data warehouse), and then loading it into the data warehouse.
Once the data lives in the warehouse, it can be synced with downstream systems in real time, in near real time, or by using the batch method.
Do data synchronization and data replication mean the same thing?
Data synchronization and data replication are often incorrectly treated as one and the same. However, unlike data syncing, data replication is often used to backup a full dataset, with the intention of maintaining a high level of data availability.
What kinds of data synchronization tools exist?
There are a range of data synchronization solutions to choose from. This includes an integration platform as a service, which connects applications through their application programming interfaces (APIs); RPA software, which uses bots to mimic human tasks at the UI-level; and (as introduced earlier) an enterprise automation platform, which can integrate your apps via APIs and automate your workflows end-to-end.
What is out of sync data?
It’s simply when the record type in one system has information that looks different than the same record type in another system.
This can be caused by an absence of synchronization between the systems’ record types. More likely, however, is that the synchronization cadence doesn’t accommodate to changes soon after they take place. For example, once a customer record adjusts in a CRM, that same customer record in an ERP system is now an outdated version and may not get updated for a few weeks (or whenever the next synchronization process runs). Cases like these highlight the need for real time, or near real time, syncs.
What is database synchronization?
Database synchronization follows the definition of data synchronization, except it applies to databases only. In other words, it’s the continual process keeping record types identical between two or more databases.
