Category: Data Migration

Moving data from one system to another might sound simple. In reality, it is a very complex process that can easily turn into a nightmare if not done correctly.

Studies on data migration show that over 80% of data migration projects can run over time and budget.

Why does this happen? It’s because of the numerous data migration challenges that can crop up during the move. They can lead to heavy data losses and even complete system shutdowns.

The solution? Using the right data migration services can help you avoid these challenges. But first, you need to know what to look out for.

To help you identify such data migration challenges, I have created this guide. It will help you understand the most common data migration issues that can affect your move.

Excited to learn more? Here is a quick look at the most common challenges.

Quick Look: Common Data Migration Challenges

Challenge	What It Looks Like	How to Avoid It
Data Quality Issues	Duplicates, missing values, inconsistent formats	Clean your data before you move it
Data Loss	Records disappear during transfer	Always back up everything first
Compatibility Problems	Old system formats don’t match the new system	Map fields carefully and test
Downtime	Business stops because migration takes too long	Plan phased migrations during off-hours
Security Risks	Data exposed during transit	Encrypt everything and control access

Common Data Migration Challenges and How You Can Avoid Them

Here are the challenges you are likely to face during your data migration:

• Poor Data Quality 

Most data migration challenges result from unsorted data that is not addressed before migration.

Data migration errors are usually caused by duplicate records and missing phone numbers. When you move such messy data to another system, you are simply transferring your problems.

The Solution

Clean your data thoroughly before migrating it. This means running a full analysis to spot any duplicates or missing fields. Moreover, you need to fix any inconsistent formatting in your data before you move it. 

• Data Loss

Data Loss is probably the scariest data migration issue that you can face today. It is a very common problem that needs smart precautions to avoid fully.

Lack of such precautions can result in the loss of critical records and data. Failing transfers can also affect other records, resulting in a complete loss of data.

The Solution

Make sure that you back up everything before you start migrating. This means taking a full backup of every source file and keeping it safe.

Also, I would recommend running validation checks on your migrated data after completion. This will ensure that nothing was lost or changed during the transit.

• Schema and Compatibility Issues

Different systems may use different methods to sort or format their data. This can lead to problems with your migrated data, causing it to function illogically and yield incorrect results.

For example, your old database might store dates in a “MM/DD/YY” format. But in the new system you are migrating to, this format can be “DD/MM/YYYY”. It is vital that you sync such formats to fit both systems equally.

The Solution

Create a detailed map of every data type and how it will transform during the migration. Make sure to run test migrations in small batches to catch such mismatches early.

Watch for any “schema drift”. This is where the source schema automatically changes during the migration without your notice.

• Extended Downtime

You may think that your data migration will only take 3 Hours to complete. But during your move, you run into some problems. It’s 6 Hours now, and your data hasn’t fully migrated to its destination yet.

It may seem like a nightmare, but it is actually very common. Factors like network slowdowns and failed transformations are just some of the many data migration challenges you may face.

The Solution

Always stay realistic with your timelines. Add extra buffer time for any surprise delays in your timeline.

I recommend considering phased or “trickle” migrations for your needs. This will help you break down your complete migration into small, more manageable chunks.

Also, make sure to run your migrations during low-traffic windows. This includes running them at night when the network is lighter, and your downtime causes the fewest issues.

• Security Breaches

Your data is extremely vulnerable when it’s on the move. During your migration, information travels across networks. This makes it vulnerable to exposure or hacking by a third party that may access it during the migration.

When you factor in regulations like GDPR and HIPAA, it gets trickier. Such regulations prevent moving EU customer data to external servers (like the US) without proper safeguards. Failure to comply can lead to heavy fines and potential lawsuits.

The Solution

Encrypt everything, both during transit and at the endpoints. Make sure that you use secure transfer protocols to avoid any data migration challenges.

Also, include your compliance team during your migration planning. This will allow you to move your data in full compliance with the law.

Conclusion

Data migration is an extremely complex process. It comes with many data migration challenges.

The only way to safeguard yourself against such data migration issues is knowledge and precautions. This can ensure your data migration services can both predict and prevent these vulnerabilities.

If you are planning your own migration, make sure you partner with a dedicated expert to address such challenges. I recommend choosing the talented support teams at Augmented Systems for your needs.

For years, Augmented Systems has helped numerous global companies successfully migrate their data. They are known for doing the heavy lifting and ensuring world-class protocols are integrated for every migration.

Want to achieve data migration that comes without any headaches? Contact Augmented Systems today and receive a free consultation!

FAQs

1. What are the most common data migration challenges?

The most common data migration challenges include poor data quality (duplicates and errors), data loss during transfer, compatibility issues between old and new systems, extended downtime that disrupts business, and security risks during transit. Each of these can derail a migration if not properly addressed.

2. How can I avoid data migration errors?

You can avoid data migration errors by cleaning your data thoroughly before moving it, backing up everything before you start, mapping fields carefully between systems, running multiple test migrations with full data volumes, and validating results after each step. Professional data migration services also help catch issues early.

3. What are the biggest data migration risks?

The biggest data migration risks are data loss (records disappearing permanently) and security breaches that expose sensitive information during transfer. These compliance violations include GDPR violations, performance problems in the new system, and integration failures that disrupt connected applications.

4. How do I prevent data loss during migration?

Prevent data loss by taking complete backups before starting, using checksums to verify data integrity during transfer, running row-count comparisons between the source and destination, testing with production-scale data, and always having a tested rollback plan ready in case something goes wrong.

5. When should I hire professional data migration services?

You should consider professional data migration services when dealing with large, complex datasets, migrating between very different systems, facing strict compliance requirements, minimizing downtime, or when your team lacks experience with previous migrations. Experts help avoid costly mistakes and ensure a smooth transition.

Is the fear of losing your data keeping you from migrating it to a new system? 

Trust me, I have been there. 

Before gaining the experience of successful data migration processes, I too thought it was all about luck! 

In all honesty, data migration is actually all about getting the right strategy. Breaking down the process into simple steps can make data migration a lot more manageable. 

In this guide, I will help you create your own data migration process and its steps. This will help you move your information without losing any sleep or data. 

Let’s first start by learning the basics. 

What is Data Migration? 

Data migration is the process of moving data from one system to another. It may be either a source for a new database or a local-to-the-cloud source.

Isn’t that just another way of taking a data backup? Well, not really! Migration is about transferring your data to a system that you will use as your primary device. 

A good data migration strategy is necessary for success in this process. In the absence of this, you may be prone to serious data loss and business disturbance.

The Data Migration Process: Step by Step

After experiencing and studying multiple successful data migrations, here is what I have learned: 

There is a proven data migration methodology that can ensure data migration with minimal risk and issues. 

Let’s explore the steps experts recommend for an ideal data migration process: 

Step 1: Taking Inventory of Your Data

Before any migration of your data can occur, it is important to understand it. This means familiarizing yourself with your own data and its quantity. 

What You Will Do: 

• Catalog every data source and format you have
• Map the entire database for tables and schemas 
• Understand the apps you use for data management 
• Identify the user patterns and their dependencies
• Find any “hidden” data in your workflows

Why This Matters: 

Many times, companies discover critical data they did not even know existed during the migration. This can lead to complications and even data loss. 

Step 2: Assessment and Planning 

Now that you know your data, it is time to develop the right strategy. This includes your data migration planning. 

Categorise your data using factors like: 

• Data that needs to be migrated vs deleted
• Data structures that need to change after migration
• Applications that should be migrated or replaced 
• Security policies that will require updation
• Sequencing the data migration process 

Step 3: Data Profiling and Cleansing 

Before the data can be moved, it’s important to clean it. This is what is referred to as data profiling and cleansing. 

Things to Check: 

• Any missing fields that have no data 
• Duplicates in your current data records
• Inconsistencies like “NY” instead of “New York”
• Values that don’t really make sense 

Step 4: Data Mapping 

Many data mapping techniques can help your system bridge the gap between old and new formats. For example, “cust_ID” in your old system can be “customer_id” in your new one. 

You can map your data by doing things like: 

• Matching every field between its source and target
• Accurately defining data transformation rules
• Handling conversions like text to numbers
• Making sure every mapping decision is documented 

Step 5: Migration Execution

Done with the basic checks? Let’s get started on the core migration process! 

For any secure data migration, it’s important to move your data in chunks. 

Follow principles like: 

• Testing your data migration first 
• Minor the move closely 
• Ensure you have a data rollback plan ready 
• Communicate with your users clearly 

Here are the Data Migration approaches you can use: 

Approach	How It Works	Best For
Big Bang	Move everything at once	Small systems, planned downtime
Trickle	Move in phases over time	Large systems, minimal downtime
Parallel Run	Both systems run together	Critical systems, zero tolerance for error

Step 6: Validation and Testing 

Done with your data migration process? Now, it’s time to check if everything worked properly. 

Validate your data by: 

• Recording and matching data counts between systems
• Ensuring key fields contain the right values 
• Making sure relationships between data remain the same 
• Checking if applications work the same with the new data 
• Rechecking if users can access the data they need

Step 7: Cutover and Decommissioning 

Once you have properly validated your data, it is time to switch over to the new system. 

This also means stopping and formatting your old system (only after taking a full backup). 

Here are the cutover steps: 

• Syncing your data for any last-minute changes
• Updating the configuration of your applications
• Redirecting users to the new system 
• Monitoring the new system for errors
• Celebrating your successful move! 

Step 8: Optimization

Completing your data migration does not mean the work has ended. You now need to make sure the migration was actually worth it! 

To get the most out of your new system, make sure that you optimize it. 

Optimization includes focusing on areas like: 

• Performance tuning
• Optimizing your costs 
• Training and supporting users
• Improvements in the system processes 

Conclusion 

If done using the right data migration strategy, the entire data migration process becomes very easy. Just make sure that you don’t skip any steps! 

Remember, the goal is not just to move your data. It is about ending up with a cleaner system that works better than before. 

For any major data migration, you will require an expert by your side. They can ensure that every step is followed and utilized to its utmost potential. 

My recommendation? Collaborate with the professionals at Augmented Systems. They will ensure that your data migration is as easy as possible with minimal downtime and data loss.

Having years of experience in the field, the experts at Augmented are already aware of what to expect in a data migration process. This enables them to protect their partners (such as yourself) against any problems.

Contact the team at Augmented Systems today to move your data without any risks or stress! 

FAQs 

1. What are the key steps in the data migration process?

The main data migration steps include discovery and inventory, assessment and planning, data profiling and cleansing, data mapping, execution, validation, cutover, and optimization. Following this structured data migration methodology ensures a smooth transition with minimal risk.

2. Why is data profiling and cleansing important?

Data profiling and cleansing help you identify and fix errors like duplicates, missing values, and inconsistencies before migration. Without it, you’ll transfer dirty data to your new system, creating more problems down the road.

3. What are common data mapping techniques?

Data mapping techniques involve matching source fields to target fields, defining transformation rules, and handling type conversions. Good mapping ensures that data ends up in the right place, with the right format, in your new system.

4. When should a business hire a data migration consultant?

You should hire a data migration consultant when you’re dealing with complex systems, large data volumes, or limited internal expertise. A consultant brings proven data migration strategy experience to avoid costly mistakes.

5. How long does data migration planning take?

Data migration planning typically accounts for 30-40% of your project timeline. Rushing this phase leads to problems later. Proper planning includes discovery, risk assessment, and the creation of detailed migration specifications.

Moving data may sound very boring, but in a way, I am glad when it is! Anything “exciting” about data migration usually comes when you face issues or challenges. 

Such challenges can easily disrupt your database migration or even cause data loss. 

So how can you protect yourself against such problems? 

The answer is in choosing the right data strategy for your database migration. This requires a complete understanding of the major types of data migration available. 

To help you plan your data migration strategy, I have created this detailed guide. It will help you keep everything running smoothly. 

Ready to make your data migration less stressful? Let’s discuss the four main types of data migration you can use, in the easiest way possible! 

 

Quick Overview: Four Main Types of Data Migration

 

Get a brief understanding of the main data migration types using the table below

Migration Type	What Moves	Common Reasons
Storage Migration	Files and blocks	Hardware upgrades, cost savings
Database Migration	Structured data, schemas	Platform changes, performance upgrades
Application Migration	Whole apps with their data	Modernization, cloud moves
Cloud Migration	Anything to the cloud	Scalability, cost, innovation

 

Main Types of Data Migration

Here is a more detailed look at the four major types of data migration available

    1 . Storage Migration

Among all available options, storage migration is considered the simplest way to perform database migration. It mainly refers to physically moving your data from one location to another. 

In most cases, this involves manually copying your data into a new storage. 

Useful For: 

• Upgrading old hard drives to much faster solid–state drives (SSDs)
• Moving your direct-attached storage to a flexible storage area network
• Migrating your data to a more cost-effective storage option 

Potential Challenges

You may experience disruptions to your data access during this transfer. This means users lose their connections and the company incurs significant downtime. 

To avoid such issues, plan ahead for any big data migration.

 

    2 . Database Migration

A database migration involves moving structured data from one system to another. Customer records, transactions, and even product descriptions are normally found in such structured data. 

Because such data needs to be rearranged in the target system as well, complications may arise.

Useful For: 

• Moving from Oracle to PostgreSQL
• Upgrading an old SQL Server
• Moving off of on-premise data storage to a cloud-based solution.

Potential Challenges

All databases have specific relationships between the data points involved. Losing these relationships (or links) between them can break the entire structure. 

During migration, it is important to reserve and replicate these connections. 

Moreover, you may also face inconsistencies like: 

• Compatibility in your schema 
• Conversions between data types 
• Maintaining the same performance

The solution? Make sure that you use specialized database migration tools that can handle your structured data. This will automate your migration and will protect against human error.

3 . Application Migration

If you thought moving structured data posed challenges, wait till you try to move an entire application! 

In application migration, you need to move an entire software application and its data to another system. This means moving everything from code, configurations, and dependencies in your data migration. 

Useful For:

• Upgrading legacy CRM systems to a modern version 
• Transferring your ERP system to a new infrastructure
• Migrating your custom applications to new servers 

Potential Challenges

Moving an entire application comes with its own set of problems. Even a minor error or missing file can render the entire application unusable. 

To avoid this, experts recommend using a framework called “6 R’s”. It includes the following application migration strategies: 

Strategy	What It Means	When to Use
Rehost	Lift and shift (move as-is)	Quick moves, minimal changes needed
Replatform	Lift, tinker, shift (minor tweaks)	Need some cloud benefits without a full rebuild
Refactor	Modify code for the new environment	Want better performance, scalability
Rebuild	Rewrite from scratch	The old app can’t meet the new needs
Retire	Shut it down	No longer needed
Retain	Keep it where it is	Too risky or costly to move

 

4 . Cloud Migration

Cloud migration has become a very generic term. You can use it for most of the data migration types mentioned above

The only defining factor of a cloud migration is moving your data to the cloud

Useful For

• Better scalability to grow without the need for hardware
• Higher cost savings to pay only what you require 
• Access to innovations like AI and other modern tools
• Easier backup and recovery systems for better protection

One of the most popular methods of company data migration today is on-premises-to-cloud migration. This entails transferring information from your data centers to cloud service providers such as AWS or Azure.

Potential Challenges

This method has similar challenges and risks as the other methods above. 

 

How to Choose the Right
Migration Type

 

Confused about which option will best suit your needs. To help you decide, ask yourself the following questions

Question	Likely Migration Type
Are you just upgrading hardware?	Storage migration
Are you changing database platforms?	Database migration
Are you moving whole applications?	Application migration
Is the destination a cloud provider?	Cloud migration (could be any of the above)

 

 

Conclusion 

The key to designing a successful migration strategy is to gain a better comprehension of the different types of data migration.

It will help you decide on the right type of data migration to perform. But only deciding the right strategy is not enough to protect your data. 

For the best results, you will also need a dedicated partner to help execute your data migration flawlessly. This means connecting with an expert who specializes in all types of data migration. 

At Augmented Systems, we have a team of experts who can guide you in your data migration. Our team has years of experience assisting businesses with the intricate issues that arise during data migration.

With our support, you will be able to migrate your data using proper security guidelines. Using these proven methods ensures that your data never falls into the wrong hands.

Ready to strategise your next data migration? Contact Augmented Systems today to receive a free consultation! 

FAQs 

1. What are the main types of data migration?

The four main types of data migration are storage migration (moving files), database migration (moving structured data), application migration (moving entire software systems), and cloud migration (moving anything to the cloud). Each type requires different strategies and tools.

2. What is database migration?

Database migration is the process of moving structured data from one database platform to another. This could mean switching from Oracle to PostgreSQL, upgrading SQL Server versions, or moving on-premise databases to cloud-managed services like Amazon RDS.

3. What is involved in application migration?

Application migration means moving an entire software application—including its code, configurations, dependencies, and associated data—to a new environment. Common approaches include rehosting (lift-and-shift), replatforming (minor tweaks), or refactoring to improve cloud performance.

4. What is on-premises to cloud migration?

On-premises-to-cloud migration is the process of moving workloads from local data centers to public cloud providers such as AWS, Azure, or Google Cloud. Benefits include better scalability, cost savings, and access to modern AI and analytics tools.

5. When should a company hire a data migration consultant?

You should hire a data migration consultant when dealing with complex migrations, massive datasets, critical systems where downtime is costly, or when previous migration attempts have failed. A consultant brings proven methodology and experience to avoid common pitfalls.

“Moving data” is a pretty simple-sounding process, isn’t it? 

Well, in a nutshell, it’s all about copying and pasting data from one place to another.

But in real life, it’s a whole different ball game.

For an enterprise, data migration is one of the most dangerous projects it may undertake in its entire lifetime. If something goes wrong in the data migration process, they may lose customer data and even experience complete data loss.

How to avoid these problems? It’s simple!! Just select a proper data migration strategy before you migrate data. This can lead to better technology utilization and cost savings.

Through this guide, you will get to know everything about data migration.

Let’s start with a basic overview of data migration!

What Exactly is Data Migration?

Let’s start with an easy definition of data migration.

Data migration involves moving data from one system to another. This could be either

• from an old database to a new one or
• from local to the cloud.

“Moving” your data is different from creating a backup. You are not just copying data; you are moving it to a new system. This system will then become your primary access point.

Any successful migration requires the following factors:

• Accuracy: All data values need to be extremely accurate 
• Completeness: The entire data must be moved to the new system
• Continuity: Businesses should continue to run during the move

Comparing Data Migration vs. Data Integration

You might be confused about the difference between data migration and integration.

Here is how you can differentiate between them:

• Data Migration

This is a one-time process that requires moving your entire data. Once the data is moved, your old system will be wiped.

• Data Integration

This refers to an ongoing process. It involved connecting systems that sync data.

The process usually operates in real time and requires both systems to run in parallel.

Main Types of Data Migration

A deeper understanding of the types of data migration is beneficial. It can help you plan your data migration strategy more effectively.

• Storage Migration

This process involves moving data between different storage systems. It usually uses hard drives or SSDs to achieve this data transfer.

It truly is the simplest way to migrate data for your system.

• Database Migration

A more advanced process, which involves moving your database files to a new platform. Migration of data from Oracle to PostgreSQL, or from SQL to Azure, will fall under this.

The success rate of database migration depends on the data you have stored. Depending on its complexity, advanced procedures or conversions will be required.

• Application Migration

In application migration, you are moving an entire application to a new environment. This means migrating all related app data to a new or different platform.

The process involves migrating both the database and the app’s storage at the same time.

• Cloud Migration

Moving your data from on-premises to the cloud is quite common.

Companies usually do this to reduce costs and improve their scalability.

Today, on-premises-to-cloud migration is also underway to make AI data tools more easily accessible.

• Legacy System Migration

In a legacy system migration, your data migrates from an outdated platform to a modern one.

This either means upgrading your entire system or moving to a modern platform.

The Data Migration Process: Step by Step

Here is how a successful data migration methodology should take place:

Step 1: Discovery and Assessment of Data

In this step, you need to understand your data and sort it. 

Profiling your data helps make your migration easier and error-free.

Step 2: Planning and Designing Your Strategy

Now that you know your data, it’s time to create a data migration strategy.

This means choosing the right approach and listing the tools you require.

The common approaches used for data migration are:

• Big Bang: Move everything at once with a planned downtime
• Phased (Trickle): Migrate your data incrementally alongside the older system
• Parallel Run: Running both systems together for verified data migration

Step 3: Data Profiling and Cleansing 

Before you move anything, ensure that your data is clean. This means removing any duplicates and fixing any formatting issues.

Any data migration done on unclean data will also corrupt your new system.

Step 4: Pilot Testing Your Strategy

Make sure that you run a test migration before copying your entire data.

This can help you recognise any issues. It will also help you resolve them quickly.

Step 5: Execution of the Data Migration

Make sure that you execute your data migration according to your plan.

Monitor closely for any errors and keep everyone informed about the progress.

Step 6: Validation of the Migrated Data

After the migration is complete, verify everything. Check key data and run user acceptance tests.

If any numbers don’t match, investigate and solve before you declare success.

Step 7: Cutover and Decommissioning

Once your data is validated, you can shut down your old system.

Just make sure you divert all users to the new one before you do so.

Top Data Migration Tools

Here are the right data migration tools you can use during the process:

Tool Category	Examples	Best For
Cloud Migration Tools	AWS Migration Tools, Azure Migrate	Moving to cloud platforms
Database Migration Tools	AWS DMS, Azure Database Migration Service	Database platform changes
Big Data Migration	IBM Big Replicate	Moving large datasets, petabyte-scale
Data Integration Platforms	Various ETL/ELT tools	Ongoing data movement and transformation

Data Migration Best Practices

Make sure that you follow these data migration best practices during the process: 

• Ensure that you back up your data 
• Define your requirements clearly before starting the process 
• Assemble a team of specialists that can handle the migration 
• Clean your data and remove any data inconsistencies
• Test your data after the migration ends 
• Ensure security and privacy during the migration

Conclusion

Data migration should not be risky or terrifying. It is a common practice that companies regularly carry out.

The problems arise when data migration is done without using the right strategy. This leads to data corruption and loss during the transfer.

For any major migration, you should consider joining hands with Augmented Systems. They are a software consulting firm known to market leaders for their reliability and success.

Augmented’s team can provide expert data migration services and years of experience. With their help, you can easily avoid the risks associated with this process.

Aiming to move your confidential data properly? Make sure that you contact Augmented today to receive a free consultation!

FAQs 

1. What is data migration in simple terms?

What is data migration? In simple terms, it’s the process of moving data from one system to another. This could mean transferring files to new storage, switching database platforms, or moving entire applications to the cloud. The goal is to make the new system your primary system.

2. What is the difference between data migration and data integration?

Data migration vs data integration comes down to permanence. Migration is a one-time process in which you transfer data and stop using the old system. Integration is ongoing, with the systems continuing to sync data between them in real-time or near real-time.

3. Can you share some data migration examples?

Common data migration examples include moving from on-premises servers to the cloud (cloud migration), switching from Oracle to PostgreSQL (database migration), upgrading from legacy hard drives to new storage arrays (storage migration), or migrating from legacy CRM to Salesforce (application migration).

4. What are the best data migration best practices?

Key data migration best practices include backing up everything before starting, cleaning your data before moving it (e.g., removing duplicates, fixing inconsistencies), testing continuously in staging environments, protecting data with encryption, and keeping stakeholders informed throughout the process.

5. When should a company hire professional data migration services?

Consider professional data migration services when you’re dealing with complex legacy systems, massive data volumes, critical systems where downtime costs money, or when previous migration attempts have failed. A specialist brings proven methodology and experience to avoid common pitfalls.