<strong>Data Synchronization: A Primer</strong>

Today data is being generated from almost every corner of the globe. Around 2.5 quintillion bytes of data is generated every day. Because of this, data synchronization is becoming the need of the hour.

Cloud technology has made data management even more complex because of its high storage capacity. Indeed, it is estimated that around 100 zettabytes of data will be in the cloud by 2025. So it is now essential to ensure that data on various devices is consistent, valid, and accurate at all times.

What is Data Synchronization

Data synchronization is simply an operation that ensures data between two or more devices is consistent. So, let’s say you are running a business. Your business will have several teams. The sales team, the finance team, the marketing team, etc.

Each team will use a specific platform to get their data. With data synchronization in place, data across all these platforms will reflect a single state of truth. There won’t be any discrepancies between, say, the sales data and the financial data.

For example, when a new customer buys your product, this information will be reflected across all platforms.

Data Synchronization: A Brief History

In the late 1990s, people used to sync their devices using a USB cable. So, you would simply connect your phone to your PC and sync your files. Later, Wi-Fi and Bluetooth technologies made this process a bit easier.

Then in the late 2000s, the cloud replaced your central PC. Now, whenever you have a network, you can connect to the cloud and sync your files.

But all these methods prevent users from using an app or service while synchronizing. However, data can now sync in the background, and users can keep using their app or service.

Importance of Data Synchronization

Businesses today get data from numerous sources. The teams dealing with this data need to be in sync.

Imagine when a customer buys a product. If data is not synced across teams, then only the sales team might know about this purchase. The finance team may not know about it at all.

This can create a lot of confusion. The finance team may give gloomy projections. But the sales team may provide optimistic forecasts. All of this can lead to delayed decision-making. In the end, the product quality would suffer.

So, to keep things running smoothly, data synchronization is essential.

Common Types of Data Synchronization

Synchronization can be of many types. These are explained below

Synchronous (Request-Reply) and Asynchronous

Synchronous communication (SC) happens when two or more devices communicate directly in real-time to sync data.

Asynchronous communication (AC) is where the user does not get blocked out of the app’s interface. Synchronization happens in the background.

One-way Data Sync

One-way data sync is when you back up your PC files onto a flash drive. The sync happens one way from a source (your pc) to a destination (your flash drive).

Two-way Data Sync

It doesn’t matter if you update the source or destination file with two-way data sync. Changing either one will update both.

How Data Synchronization Streamlines Workflow Collaboration?

Business leaders should focus on building a collaborative culture between teams. Integrating different data platforms can achieve this. Doing so will prevent team silos where each team is working on its own.

For example, an e-commerce business can have multiple functional departments such as procurement, sales, marketing, etc. Each team’s data should be consistent. Otherwise, businesses can lose almost 20% of revenue due to low-quality data.

Imagine what would happen if the monthly sales projections of the sales team versus the marketing team are not in sync. What if the marketing team sends an optimistic report to procurement, which might book large orders? 

Such disasters can be avoided if there is proper coordination among teams and each team’s analysis is shared with others in time. The data systems of each team should be integrated well enough to ensure real-time updates. 

Also, there should be inter-dependency between teams to prevent one from becoming a jack-of-all-trades. 

On a more systematic level, systems can be synchronized through native integration - which is a one-way data sync.  So, whatever updates happen in system 1 will be reflected in system 2, but not vice versa.

Unlike native integration, custom integration can do two-way data sync. But building a custom integration utility can be challenging.

Lastly, you can use a third-party API. This is usually called Integration Platform as a Service (iPaaS). iPaaS provides a simple way of integrating your apps to ensure data synchronization.

Be as it may, all types of methods have some common steps.

Steps

Firstly, the synchronization system detects a change in a data store. This can be through a timestamp or some other technique.

Next, the change is identified by checking things like changelogs, versions, etc.

These changes are then transferred to other systems. Here, the transfer can be synchronous or asynchronous.

If the data in other systems does not match the incoming change, the changed data object is parsed and cleaned.

The existing data is then updated. The changes can be applied in a transactional manner. Or changes in different systems can be merged altogether. Alternatively, they can be used in aggregate in a snapshot.

Finally, a confirmation is sent to ensure that all the data sources have been successfully updated.

Sync SQL Workflows with Sherloq

Data synchronization is very important. But with big data, the analysis across teams can differ from one another. So, it’s not just data that needs to be in sync; the analysis and insights should also align.

But data analysis is usually done with SQL queries. When these queries get large and complex, it can be challenging to reproduce the results. And this is where Sherloq’s Query Synchronization tool comes in.

With this tool, you can easily save and share snippets of queries and also view a query’s usage history. All of this ensures that teams are well-coordinated and productive.

In addition, you can define a standard glossary of data terms and concepts to build a consistent taxonomy. This helps with searchability and establishes relationships between different data sources. 

Finally, you get a bird’s eye view of all the queries used by your team members, which helps analyze data more efficiently.

Contact us to learn more about Sherloq, or try it yourself for free!