Big data migration: process, types, and all the golden rules to follow

If you have been using a PC or laptop for a while, you know that moving one file from one folder to another with simple clicks of the mouse is easy. But as your business grows, there appear millions of data you need to deal with daily.

The research showed that around 55% of projects revolving around data migration come out with over-budget spending. The process can be more complex than you might imagine. But before going deeper into challenging big data migration, you must understand its basic concept first.

Defining Data Migration

Data migration implies moving the existing data to new storage, system, or even file format.

Although it sounds so simple, the process is complex. We are talking about the massive amount of data that require a lot of resources to handle.

A successful migration requires good preparation, including planning, backup, testing, as well as maintenance. A particular activity ends after all data are moved and the old system is ended.

Kind of Data Migrated

Depending on the type of your business, you might have distinct types of data that you will want to migrate.

Data migration is not a standalone ride. It has always been a crucial part of big projects, such as changes of the system, software replacement, system updates, moving on-premises to the cloud environment, mergers between companies, and so on.

Data Migration vs. Data Integration and Data Replication

It is important to understand that data migration is different from data integration and replication. People often mistake them for one another. It is important to know the differences.

During data integration, data are taken from multiple sources in and out of your company, which you blend. The data are “consolidated” rather than “moved.”

Data migration has one direction, which is to move particular assets to the determined destination. This also sets it apart from data replication. During data replication, you will not delete the source of replication. That means you will have two exact data collections of different origins. Data replication is usually included in the integration. But in the future, it can also be data migration if you decide to remove it from the first source.

Types of Data Migration

Big data migration can be of different types depending on the assets to be moved. But you probably find out various names to appoint each sector of the migration. Here are the major types that you need to know.

• Storage migration. Storage migration usually happens when you update new technologies in your business infrastructure. It can be from print to digital form, from digital to a cloud environment, or from cloud environment to SSDs. It can be a good option when you need to scale your business up.
• Database migration. This migration is supervised by the DBMS ­ Database Management System. As the name suggests, the database will be the one that migrates. For instance, it is possible to move MySQL to Oracle or vice versa. On many occasions, it is possible to move one database to another in more detail.
• App or software migration. When your business changes the software solution for improving operations, you will need to move data from one place to another. The infrastructures can come with different data models. It will be challenging to move one app from one environment to another. ERBIS professional help will be feasible here.
• Data Center Migration. Datacenter relies on a single infrastructure used by companies or organizations to secure their assets. This means to revolve around relocating the data center to another place, which can be a new location or storage.
• Business data migration. This will happen when there is a merger or joint venture in the business. For instance, when Facebook bought Instagram, there was the movement of business apps and databases consisting of members, operations, as well as all assets from and to different environments.
• Cloud migration. It is about moving all kinds of data from the physical environment to the cloud environment or between cloud environments.

How Much Time Is Spent on Migration?

When we talk about big data migration, you should not expect that everything can be done in only an hour or two. Regardless of the scale of your business, this process could take days, weeks, months, or even years.

Factors that contribute to the time of progress are available resources, workforce, the complexity of the project, bandwidth, and so on.

Approaches

There are two main approaches to data migration: Big Bang and Trickel.

Big Bang is about moving all data assets from the source to a particular destination in one go. It usually ends in a shorter time. But it is a highly expensive procedure that comes with huge risks of failing. The challenge lies in the server’s downtime.

However, this method can be feasible for startups or small enterprises that have relatively small data amounts. It will be less risky to take care of this method.

If it is big data migration that we are focusing on, the Trickle approach can be the right option. It comes with zero downtime and less risk. However, it will use more resources and energy. The trickle approach can be the right option for medium to large businesses, companies, and enterprises that have huge amounts of data.

Data Migration Phase

Each cloud mitigation provider may have different strategies to help clients to move their big data. But the project will go through the following stages:

• Planning
• Data auditing
• Backup
• Design
• Executing
• Testing

Golden rules

Here are common golden rules that can help you migrate the data safely and successfully:

• Look for errors in data migration
• Hire the data migration services provider to help you with the project
• Minimize data amount
• Mind the timeline

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