A Guide to Data Migration: types, strategies, and process

We’re all well familiar with the concept of data migration. Yes, most of us recorded CDs with songs or movies to exchange them with friends back in the times where there was no Wi-fi in all public places, as it is nowadays. Yes, recording a CD is an easily understandable example of data migration but, probably, on a very small scale.

‍During the past 2 decades, the world has seen unprecedented technological advancement in all spheres. And so did the data migration process. Based on the observations of Gordon Moore, scientists concluded that there is a significant technological boost every two years. Systematic increase of computing power and internet connection bandwidth is related to Moore's Law. In this article, we will try to prove that data migration does not have to be a necessity but also technological development.

What data migration is

Data migration is the process of moving data from one location to another, one format to another, or one application to another. Generally, it is the result of introducing a new system or changing the location of data storage. A business factor is typically an application migration or consolidation where older systems are replaced or extended by new applications that will share the same dataset.

Nowadays, data migrations often start when companies move from infrastructure and on-premises applications to cloud storage and applications to optimize processes or transform their business.

The data migration process is very risky. If, after the process, we think that the data has been fully transferred and we stop using the original environment completely, then it turns out that something has gone missing somewhere, we will register its loss.

Kamil Hudaszek, SoftwareSupp Data Analytics Freelancer

Moving important or sensitive data can be viewed as a 7-step process:

1. Pre-migration planning.

2. Project start. Identification of key stakeholders.

3. Definition of the quality policy and presentation of the project objectives. Establish a robust data quality policy management process and inform the company of project goals, including shutting down legacy systems.

4. Solution design. Defining what data to transfer and the quality of that data before and after the transfer.

5. Construction and testing. Code your migration logic and test the migration as a mirror image of your production environment.

6. Execution and approval. Demonstration that the migration is compliant and that the transferred data is fit for business use.

7. Decommissioning and monitoring. Shut down old systems.

In the 21st century, companies and businesses do not only move workloads to new or upgraded physical storage systems or servers. Cloud computing allows storing any information online, which has plenty of benefits. For instance, you can access data from any device anywhere in the world. No wonder that more and more companies shift to SaaS (Software as a Service) and PaaS (Platform as a Service) models.

In addition, more and more businesses shift to an online model with employees working from different countries around the world. Thus, it’s much more convenient to store all data on the cloud rather than keep all the servers in one place. The same goes for companies and businesses physically located in one country but sell their services and products in other countries and markets. Modern cloud implementation tools make the data migration process fast and efficient, with almost no risks of losing any information.

Only 10 years ago, the percentage of cloud workloads of total data center workloads was 30%. In 2021, this number has risen to 94%.

Why do you need data migration

Data migration happens for a variety of reasons. It can be modernization or expansion of the existing applications and storage systems or introducing new software. If the company decides to implement a centralized database, it will also need to transfer all the current information to new storage. The same goes for moving IT infrastructure to a cloud. No matter, it is happening on the internal system level or the external one - all these changes cause data migration. One more common reason for migrating data is merging and acquisition. It appears when one business merges into another one- their data should be transferred to the mutual storage system. Moreover, increasing data security has also been recognized as a good cause for data migration.

CRM (Customer Relationship Management) system implementation is a classic example of data migration

‍CRM systems allow storing and tracking customer data, such as lead information, customer interactions, purchases, etc. With the help of the CRM system, an organization can manage all this data more effectively to build better relationships with clients and generate sales. If your company has never used a CRM system or wants to shift to a more advanced one, you will need to start a data migration process. Within this, all the information on your clients will be moved and structured in the CRM system.

Data migration is a kind of step forward. It is about awareness and willingness to develop. Systematizing duties, automating processes, and organizing data are the basis of effective management. As we wrote earlier, the implementation of CRM in the company internal system increases work efficiency. Here we want to emphasize that apart from the fact that it is an indispensable element of CRM integration, it is also a part of the development puzzle. After all, the database is a knowledge base. Customer data, documents, internal company information - these are crucial components of the company operations. That is why it is worth taking care of security and proper data storage.

Data migration is often connected with business management. The process of data portability is not only about moving information from one storage to another. Indeed, it has to do with systematization and the organization of data. So, what’s the connection between data migration and business management? To put it simply, data migration allows companies to manage and understand all the processes better. No matter whether you’re introducing an improved storage system for your customers’ information or want to boost sales, data migration can be a solution for both these problems. How? Further, we’ll talk about CRM (Customer Relationship Management) implementation. SoftwareSupp has extensive experience in CRM implementation for different companies and businesses.

Now, we will explain the difference between data migration, data integration, and data replications. All these processes may seem pretty similar at first glance when, in fact, they all serve different purposes and require unique approaches.

Data migration vs data integration

Data integration is the process of merging two or more data repositories into one. It means that various information- types or information formats will be stored together. Contrary to data migration, where all information is transferred from one storage to another in the same format.

Data migration vs data replication

Let’s imagine data migration as a one-time and one-way journey. During this process, the information travels from its original storage or location to the new one. After this process, the primary storage is usually abandoned.

Data replication is a continuous process during which the information is periodically transported to the target location. The original source of information is never deleted or abandoned. Both the original and target locations serve as backup. If the data source is no longer needed, data replication turns into a data migration process. At the same time, data replication can be a part of the data integration process that was described above.

Advantages of data portability to CRM

‍Let’s briefly go through the benefits of a CRM implementation:

• effective management of leads and deals,
• automation of processes
• tracking communications
• collecting performance data
• a single database of customers that is easy to organize and use.
  

All in all, a CRM system gives structured and organized information on current sales funnels and daily tasks. A CRM implementation can boost any business revenue because it provides statistical data on clients and improves the mistakes and gaps in the sales process and marketing strategy.

6 types of data migration

Data migration can be divided into the 6 most common types. However, some of them can be combined to enhance the process as a whole. Below, we’re providing more details on all 6 types of data migration.

• Storage migration

This one happens due to the storage equipment upgrade. The information is moved from one physical storage medium to another one. Examples of such data migration can be digitizing paper documents or going from mainframe computers to a cloud storage system. In both cases, the storage technologies become more advanced.

• Database migration

Databases are where the data is organized and structured with the help of the database management systems (DBMS). Database migration involves transferring data to a new DBMS.

• Application migration

This one is needed when an organization changes the application software or vendor. The key issue here is the difference in data formats and types. It’s crucial to preserve all the information when moving it to a new application. Such application migrations often require data information to fit in with the current software.

• Cloud migration

It is a data movement from an on-premises location to a cloud environment. Information can also be transferred between different cloud environments. SolarWinds Report on IT trends stated:

95% of IT professionals surveyed migrated critical applications and IT infrastructure to the cloud

No wonder that in 2021, a cloud solution is a must for a successful business.

• Business process migration

This type of data migration has to do with business applications and information on all business processes. Business process migration to a new environment is usually driven by business optimization or merging and acquisition.

• Data Center migration

To put it simply, a data center consists of servers, computers, storage devices, network routers, and other similar equipment. The role of the data center is to maintain the most important applications with the help of data storage infrastructure. When an organization conducts data center migration, it means that- it can be transferred from one physical location to another or from one piece of equipment to another.  

Data migration strategies

Regardless of what type of data migration works best for the company, there are two approaches for moving information. Let’s have a closer look:

“Big Bang” migration

The name of this strategy says: all data is transferred at once during a limited time. One significant disadvantage of this approach is that all live systems go down during the data migration process. For instance, if any service is updating their mobile application by implementing the “Big Bang” approach, their users can have issues if they use mobile apps at the same time. However, one of the main benefits of this strategy is that data migration does not take long (usually up to a few hours). Thus, a company can plan and prepare a downtime and warn both the clients and the employees to prepare everybody for a smooth transition.

“Trickle” migration

This strategy cannot be implemented at once but is divided into phases. Both old and new systems run in parallel to ensure access to all the applications during the data migration process. The information is transferred continuously with almost no downtime for all the systems.

All in all, the first strategy is less expensive and easier to implement. Because all changes happen at once, the risks of a failure skyrocket too. “Trickle” migration, in its turn, is costly and more complicated to perform because the two systems are running simultaneously.

ETL process

There are three distinguishing phases in the data migration process:

• extraction
• transformation (if necessary)
• loading

In some cases, one more stage is added. It’s called the preparation stage. The ETL process is the same. No matter if an organization chooses a “Big Bang” or “Trickle” migration strategy.

Let’s see what an ETL process looks like based on a real-life example. Here SoftwareSupp experts had to set up a Pipedrive and conduct data migration for a luxury travel agency.

On the screenshot below, you can see the following stages of the ETL process:

• exporting or data extraction
• adjustment of data or preparation
• data import or loading

Risks and things to consider

The data migration process isn’t an effortless thing that companies perform daily. It’s a pretty challenging procedure that can have serious consequences if something goes wrong.

We’re briefly talking about some risks and challenges to keep in mind during the data migration process:

• migration time
• losing data
• data security
• testing new systems
• backing up information before starting data migration
• type and amount of data

The database migration should be carried out by an experienced specialist. It is a large project requiring expert knowledge, and if properly conducted, it does not bring any risk. It is a business technology update process. Finally, modern business focuses on the following technology.

With SoftwareSupp, your data migration process is at minimum risk. We know how to move and optimize information to benefit your business. With a large pool of dedicated experts in different industries, data migration becomes a natural process that will result in better access to information, flawless performance, and a profound understanding of how your business works.