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The Complete Data Synchronization Guide and Why It is Important

Organizations are constantly collecting, analyzing, and storing data daily, and the cloud has become a conduit for that unprecedented data supply. Hence, the need for data consistency, accuracy, and privacy. Unfortunately, things that may look like minor errors or glitches can significantly negatively impact decision-making, sales, customer retention, and other daily operations.

Sorting through stored data is hard enough without syncing it with existing databases and parsing it out regularly while maintaining data integrity. That’s why data synchronization is now one of the most valuable tools organizations use to manage data.

The process assures accurate, secure, and updated data with improved teamwork and customer experiences. Once organizations synchronize everything, they get cleaned, improved, and updated data with no inconsistencies, errors, duplications, and other bugs.

Imagine listening to a jazz concert where the musicians and instruments are not synchronized. You end up listening to disparate sounds that don’t make sense or entertain. Similarly, clocks also need synchronization to prevent chaos because we rely on them to run and coordinate all aspects of our lives.

These same principles apply in the business world. An organization needs its departments, goals, employees, and software applications synchronized to operate and grow. However, while all companies know the essence of aligning goals and departments, many often overlook the importance of synchronizing their data.

This guide discusses everything to do with data synchronization, implementing it, and why it’s important.

What is Data Synchronization?

It’s the process organizations use to consolidate data across different and disparate sources and software applications to ensure the data within those systems is consistent. It’s a continuous process that applies to new and existing data.

The sheer quantity of data the cloud stores and affords presents challenges to organizations. However, it also provides a solution for big data. Current data solutions offer easy and quick tools to bypass monotonous tasks and create data harmony throughout the system.

Synchronization ensures accurate, compliant, and secure data with a successful team and customer experience. Additionally, it assures congruence between data sources and different endpoints. So as data comes in, there are tools to clean it while others check it for errors, duplication, and consistency before putting it to use or storing it.

Remote synchronization occurs over a mobile network, while local synchronization involves computers, devices, and systems next to each other. An efficient system ensures all organizational data is consistent throughout the data record. Therefore, the changes must upgrade and reflect through every system in real-time if any modifications occur. It prevents mistakes and privacy breaches and ensures the availability of up-to-date data.

Finally, synchronization requires two things to happen:

  • Data consolidation across different sources and endpoints to ensure accuracy and harmony
  • An ongoing process applicable to new and existing data

What is Database Synchronization?

Database synchronization establishes data consistency between databases and automatically copies changes back and forth. Data harmonization over time occurs continuously, and the most trivial case is pulling data from the source database to the destination. It means changes made to the source (master) database should apply to the target database.

Each table should have a primary key in database sync to identify one row alone. It significantly simplifies the process of data maintenance while speeding up synchronization.

Below are the different types of database synchronization:

  • Insert Synchronization: The process copies new source table records to the target table to ensure matching records with primary key values. In addition, the database sync process inserts missing rows into the target tables.
  • Update Synchronization: Any changes made to the source table must also apply to the target database. Therefore, the synchronizer tracks the table row values and replaces the changed records in the target tables to make the two tables identical. Update synchronization constantly updates all the data in the source and destination databases.
  • Drop Synchronization: The drop sync process removes corresponding records from the destination database when they are removed from the source. It drops all obsolete records from the target if they are missing or don’t exist at the source.
  • Mixed Synchronization: It ensures the target and source databases are synchronized by updating, adding, and deleting records in the target database. Therefore, the admin must check all the “insert sync,” “drop sync,” and “update sync” options for identical source and target databases.

How Data Synchronization Works

The different ways to synchronize data include manual database updates, python scripts triggered by source database changes, and fully automated data pipelines using ETL. In all the instances, the process follows the following steps:

1.    An Update Event is Triggered

The data sync process detects a change made to the data on a target database using several ways, such as setting a flag within the table or a script that regularly checks the last modified file date.

2.    Changes Identified and Extracted

Since synchronization does not mean full replication, the process only needs to identify instances where changes are made by comparing versions, checking changelogs, or looking for flags indicating new values.

3.    Changes Made to Other Sources

The sync process schedules the movement of data after identifying and extracting changes using one of two ways:

  • Asynchronous: Transmits changes according to a set schedule, for example, once an hour or once a day. It’s a resource-efficient method but could mean discrepancies may arise between scheduled updates.
  • Synchronous: The synchronization process runs after every change. It’s a more resource-intensive method but allows for real-time data updates.

The data transfer process might occur through a web or file transfer process. When synchronization uses ETL platforms, it processes automatic background updates without manual intervention.

4.    Incoming Changes Parsed

When two data instances are not identical, the incoming data passes through a transformation layer that includes cleansing and harmonization.

5.    Changes Applied to Existing Data

The sync process writes incoming changes to the target data using one of several ways, including:

  • Transactional: Applies changes one-by-one in the order they occurred and ensures every data instance has a similar local change history.
  • Snapshot: Applies changes in aggregate to ensure all data is identical but only the original version retains the full change history.
  • Merge: Merges changes if they occur on both sides without marking either version as the definitive. Instead, it updates both data instances to reflect all changes.

The goal is to update each data instance without any loss.

6.    Successful Updates Confirmed

The updated system confirms the updates’ success using one of several ways. For example, if the application programming interface (API) handles the update, it will return a message confirming its success. Failure to send this confirmation message will see the process either attempt to restart the update or return an error message.

Data Synchronization Methods

There are several data synchronization methods available, as discussed below:

  • File Synchronization: It’s used for home backups, updating portable data using a flash drive, or in external hard drives. It’s faster and more error-proof than manual copying techniques and ensures separate locations share the same data. In addition, it prevents the duplication of identical files and occurs automatically.
  • Version Control: It provides sync solutions for files that multiple users can alter simultaneously.
  • Distributed File Systems (DFS): It only works on connected devices containing multiple file versions. Some systems allow devices to disconnect for a short time so long as the process implements data reconciliation before synchronizing.
  • Mirror Computing: It provides different sources with exact data set copies. It’s useful for backups because it only provides an identical copy to one location.

File synchronization and version control tools can change several file copies at a time, while DFS and mirror tools have more specific uses.

Differentiating between Data Synchronization, Integration, Pushes, and Replication

Below are the definitions and differences between synchronization, integration, replication, and data pushes:

  • Data synchronization: It’s a type of integration that keeps data consistent between databases. It’s an ongoing process that keeps databases in constant communication and applies changes between the source and target to ensure they are identical.
  • Data Integration: It means combining pieces of software or data from different sources into a unified view or single dataset. While data sync is a type of integration, not all integration processes lead to proper data synchronization.
  • Data Pushes: It’s another type of integration that achieves different results. The process takes data from a designated point ‘’A” to point “B” immediately after its creation. It prevents the manual creation of the same data in point B after its creation in point A. Instead, point B automatically receives the data from point A. Unlike synchronization, which can work two ways, a data push only works one way.
  • Data Replication: It’s a process that stores similar data in several locations to improve its availability and accessibility and prevent its loss. The process is unidirectional and fully mirrors, backs up, or replicates source data to another instance such as a storage device or server.

Why is Data Synchronization Important?

Organizations collect and handle data through numerous applications and software programs, with some running operations with over 100 software tools. As a result, employees view the same data set across different applications. For example:

  • Marketers view leads in marketing automation platforms while the sales representatives view them in a customer relationship management (CRM) platform.
  • Human resource (HR) teams view employee information in a human resource information system (HRIS) while the IT team tracks it in IT service management (ITSM).
  • The finance team reviews sales orders on the enterprise resource planning (ERP) system while customer-facing employees see them in a CRM.

The result is a lot of information coming in from disparate sources, making it easy for databases to become disorganized and disjointed if they don’t talk to one another.

Having the same data appear across different applications is essential for individual teams. Still, without cohesion and synchronization, manually re-entering updated data in apps leaves employees overwhelmed and prone to errors leading to further discrepancies.

When data is not in sync, it leads to many adverse effects, such as:

  • Data silos
  • Applications with conflicting and duplicate data
  • Misalignment and friction among functions
  • Low quality and outdated data
  • Presence of too much data with parts that don’t make sense or are not useful
  • Poor communication and collaboration among teams
  • Poor customer support with representatives failing to access the entire customer history, leading to inaccuracies and repetitions
  • It makes it hard to build accurate, understandable, and actionable reports from data-driven insights due to scattered data across different tools
  • Poor decision-making process

These problems above are why poor data quality and management costs organizations millions of dollars annually.

Synchronized data allows organizations to get a crystal-clear view of every aspect of the business, communicate transparently, and produce actionable and reliable reports. It also enables the alignment of departments towards common goals, teamwork, and making informed decisions.

Data Synchronization is the Key to Trusted Data

The essence of data synchronization grows with increased access to cloud-based data and mobile devices. Mobile devices have permeated all organizations, leading to many new problems and solutions. These devices use data for their basic operations and personal information for websites, email, and apps.

Therefore, updates to the information users generate and the end target must be constant and secure. In addition, the synchronization process requires clean, consistent, and updated data for product and service competence and data governance issues such as security and regulatory compliance.

Conflicting data can result in low data quality and errors, leading to a lack of trust down the line. Proper implementation of data synchronization across the system ensures the organization sees an improvement in performance in many areas, such as:

  • Business systems
  • Logistics and transportation
  • Order management
  • Sales team productivity
  • Cost efficiency
  • Invoice accuracy
  • Reputational management
  • Customer support

Furthermore, data availability and timely error resolution save time and emphasize critical business development processes like new product development, strategic decision making, and marketing. Everyone benefits from synced data:

  • Executives receive the latest data to help make critical strategy decisions
  • Stockholders stay on top of their interests in the organization
  • Distributors get access to recent product and marketing information
  • Customers receive product information and services that meet their specific needs
  • Employees interact with all departments using up-to-date and real-time information
  • Manufacturers access recent changes and updates for accurate design and production
  • The IT department quickly and efficiently sends program and security updates and patches

All in all, data synchronization ensures organizations operate smoothly and can scale.

Data Synchronization Use Cases

Data sync is helpful in numerous situations, including the following:

1.    Data Harmonization

Synchronization helps maintain consistency between two or more data sources. So updates in one source are mirrored on all the others. For example, customer addresses might appear in several places and applications on a database, such as the CRM, billing system, customer’s e-commerce account, and order fulfillment system.

So if the customer changes their address in their e-commerce account, the change should reflect in all other systems using a synchronization process.

2.    Distributed Computing

Synchronization is essential in cloud computing and distributed systems because data can exist in several places. It ensures users can always access the most recent data versions and guarantees their updates are saved.

For example, when using cloud services such as DropBox or OneDrive, users can create documents on one device, save them in the cloud, and open them on another application, web browser, or device. The cloud server reflects and stores any changes they make and forces an update on all the connected devices to replace older versions with the latest copies.

Synchronization also helps with hybrid integration where data is stored on-premises and in cloud services such as Microsoft Azure, AWS, or Google Cloud Platforms. Processes like AWS data synchronization or Azure data sync handle data enrichment, filtration, transformation, and aggregation before transferring and storing it, and vice versa. This occurs in real-time while maintaining data accuracy and consistency and without interrupting business operations.

3.    Storage and Analysis

Data replication is used when storing data in repositories like data warehouses. However, updating the data requires real-time synchronization. For example, during a disaster recovery scenario, an organization will need an up-to-date data snapshot, so if it regularly syncs its backups, it will avoid substantial data loss.

4.    Distribute Updates

Synchronization can include significant changes, such as amending the structure of a relational database. Therefore, the process can add and drop tables and rename columns. For example, when GDPR introduced the requirement to ask users about cookie preferences, affected organizations had to introduce a new database column and sometimes an entirely new table to store the added information. These changes must reflect across the network to all database instances.

5.    Other Use Cases

Other synchronization use cases include:

  • Maintaining data availability
  • Consolidation of disparate business units
  • Allows the creation of a 360 view of business processes

Benefits of Data Synchronization

Below are the benefits of synchronizing data:

  • Removes Data Silos: Employees get data access in their applications, so they don’t have to request access every time. They also become aware of the data’s existence and any changes made.
  • Prevents Extensive Data Entry: It avoids the tedious and monotonous process of manually entering data and all changes made. Instead, employees can focus on other critical tasks.
  • Allows the Performance of Several Data Operations: It makes it easier to create records, update them, and delete them, adding value to the business and employees.
  • Allows Real-Time Data Syncing: The Process of syncing data in batches might help in certain instances, but near real-time data syncing is invaluable for executing organizational processes successfully.
  • Prevents Data Loss: Continuous syncing ensures up-to-date data after the initial data backup.

Data Synchronization Challenges

While data synchronization is not rocket science, maintaining healthy, up-to-date data across cloud and on-premises systems is challenging. Below are some of these challenges:

  • Security: Data sync security and confidentially are non-negotiable issues. Remote work and mobile devices at work (BYOD) are now the new normal, so businesses demanding more flexibility find it challenging to protect against data leaks, breaches, and losses. Still, synchronization tools must meet the regulatory standards, or the organization risks issues like fines, loss of data, customer churn, and poor reputation.
  • Data Quality: It’s nearly impossible to cooperate without a reliable sync solution due to multiple apps. Therefore, organizations need a seamless sync system in place or risk breakdowns.
  • Data complexity and compatibility: More data means more complexity. Since data grows with organization growth, data formats also constantly increase and change with the addition and removal of employees, customers, vendors, and products. The challenge occurs when organizations try to interface new data with old systems.
  • Real-Time Updates: Real-time data automation is no longer an advantage but a going requirement, and its absence renders available sync solutions almost useless.
  • Performance: Data synchronization involves data extraction, transformation, and loading, which require proper capacity planning. Otherwise, real-time syncing of large data volumes negatively impacts the system at peak times.
  • Maintenance: The synchronization process require regular maintenance and proper management to ensure it runs as scheduled.

Data Synchronization Tools

There are many types of data synchronization solutions available. They include:

  • An integration platform as a service (iPaaS) that connects apps through their APIs
  • RPA software with bots that mimic human tasks
  • Enterprise automation platform that can integrate apps via APIs while automating workflows end-to-end.

Data Synchronization with Veritas?

Veritas provides NetBackup data synchronization through SyncNetBackupData. It calls in the API whenever an asset gets flagged for synchronization. The System Update then picks up the marked asset. The process imports the images and protection before recalculating traffic light status.

By default, it processes batches of 100 assets in five minutes or until there are no more assets marked for importing. Additionally, it prioritizes assets added first unless a Backup Now request marks specific assets as a high priority.

If a sync fails, the system locks it for some time to process other assets and prevent a backlog.

The Bottom Line

There are plenty of choices for data synchronization solutions, so organizations need a clear strategy that answers the following questions:

  • What type of data do they want to sync?
  • What kind of apps do they want to integrate?
  • How do they want their data to flow between the different apps
  • What data volumes are they anticipating?
  • Do they have the resources for real-time syncing, or are they okay with syncing in batches?

Sometimes organizations get applications with native integration tools that solve their operational challenges. For example, NetBackup provides the safest, easiest, and more intuitive way to synchronize data. Otherwise, they may need one or more iPaaS solutions that work for them.

Veritas customers include 98% of the Fortune 100, and NetBackup™ is the #1 choice for enterprises looking to back up large amounts of data.

Learn how Veritas keeps your data fully protected across virtual, physical, cloud and legacy workloads with Data Protection Services for Enterprise Businesses.