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What is Data Migration?

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What is data migration?

Data migration can be defined as the process of transferring the data from one system to another system.

While this might seem to be pretty, it involving a changes in storage and database or application.

In the context of the extract/transform/load (ETL) process, in any data migration will involve at least the transform and load steps. It means that the data which is extracted, needed to go through a functions series in preparation, after which it can be loaded in to a target location.

Organizations which undertake data migrations for a number of reasons. They might need to overhaul an entire system, upgrade databases, establish a new data warehouse, or merge the new data from an acquisition or other source.

Data migration is also required to when deploying another system that sits alongside in the existing applications.

Read more about: What is Data Analytics

Types of Data Migration

In data migration, there are 4 types having which is required to fulfill the planning and validation in the system information.

  • Storage migration
  • Database migration
  • Application migration
  • Business process migration

1. Storage Migration

In this storage migrations, when the information is migrating from one system to another storage system. While we using this Technology, it has refreshes to us as  great time to transfer the information. When new technology becomes compactible, it migrates our data to that technology can be attractive, it has been  efficiency, cost, or experience of accessing and using the data in the built in format files.Many tools and products are available to ease in migrating your stored data.

2. Database Migration

In the database migration, it is the heart of the technology in these modern days.It has been changing the databases, software should be upgrade or transferring the data from the database to the cloud. Before this transferring databases, the companies should mention these process in their plan:

  • Access the database size.
  • To test their database applications.
  • To guarantee their data confidentiality into the database.
  • To transfer the data process, test their compatibility.

3. Application Migration

In this migration, it provide their take place when  the companies switch vendors or platforms. For examples, to include their implementation a new HR system or switching from one CRM to another system. In these Companies, transferring applications should make sure their information can be communicated between these two applications. Each application may have a unique data model, so attention must be paid to how that data is formatted. In Companies, it should have plenty of steps in which they can transferring the applications successfully.

  1. It may use the middleware to the bridge technology gaps.
  2. It may use the scripts to transferring the data automatically.
  3. It may protected the integration of data with the help of an API.

4. Business Process Migration

In this business process migration, it is the complex the migrating applications and in the databases containing data about customers, products, and operations. Data migrations can be easy, but they must be planned for and validated once they’re finished to end on time and within budget.

Data Migration process

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6 Key Steps in a Data Migration Strategy

1. Explore and Assess the Source

2. Define and Design the Migration

3. Build the Migration Solution

4. Conduct a Live Test

5. Flipping the Switch

6. Audit

How to do Data Migration?

In the data migration, the whole process should be viewed as the taking place in three phases follows as:

  • The Preparation Phase
  • The Migration Phase
  • The Post-Migration Phase.

The Preparation Phase

In many respects, this phase may be the most important. One slip-up here and the rest of the data migration process will suffer. Many of the steps of the Preparation Phase might seem pretty basic, but without them, the chances of further mistakes later on only increase.

One of the first things you need to do is identify exactly what data you’re choosing to migrate.

This covers a number of areas, from the format of that data, where it currently resides, and where you intend to store it after migration.

All of this is standard information, but it’s information that will help you plan out the rest of the process.

For example, as you identify the data you want to move, you may recognize it as data of a sensitive nature. That would lead to greater protective measures being taken during migration.

Another important step as part of preparing for the next phase is to back up all of the data you intend to move.

Problems can arise during data migration, some of them seemingly coming out of nowhere.

The last thing you want is to permanently lose the valuable data you’re moving. By backing up the data, you’ll have something on hand to restore any data you accidentally lose.

The Preparation Phase also includes a variety of assessments for the equipment, tools, and teams involved in data migration.

This is another area where you can identify any potential problems before they become serious. In the case of assessing your staff, determine what skills and experience they already have to see if there might be a lack in data migration expertise.

Assess the true scope of the project, including how big the project is and how much time it’s expected to take.

Assess the tools you’re using to see if they will be able to handle the data migration project you’re executing. By assessing these factors, you can determine if you need new tools, additional resources, or outside help to ensure everything goes smoothly.

The Migration Phase

The actual migration part of the data migration process is probably what most people think of when referring to data migration.

This phase is comprised of a number of steps designed to get the data from its current location to its destination. As long as the established plan is followed, everything should run pretty smoothly.

The first step in data migration is often referred to as data extraction. The data is taken from the source system where it resides into a temporary setup, which allows any needed changes to be made.

Cleaning the data is the next part of the Migration Phase. Those familiar with data cleansing will know what this entails.

Essentially, this means any inaccuracies within the data are fixed. This step also eliminates any duplicate information as well as cleaning up corrupted data where it applies. Once this step is completed, the data will be in a good state to move on.

The next step involves the validating the data, where the data is tested before it is finally delivered to its destination.

The purpose of the testing is to ensure that the data will work within the new system without any problems.

Multiple tests should be conducted for the best results. Finally, the data will be loaded into the new system. This is the end step of the data migration process. Once done, the Migration Phase is over and the next phase can begin.

The Post-Migration Phase

Just because the data is now where it needs to be doesn’t mean the whole process is complete. There are still steps to follow as part of the Post-Migration Phase. The first begins with testing the new system with the relocated data.

While it’s true that a form of testing already took place during the Migration Phase, this testing ensures that everything went well.

The test will make sure that there aren’t any connectivity problems and that the data arrived at its proper destination securely and in its correct form. Numerous tests can be done at this point, including volume, web-based application, system, unit, and batch application tests.

Once those tests are done, there’s still no guarantee that you have a problem-free system on your hands. To check for any errors that might have creeped in, you’ll need to perform a full audit of both the system and the data.

For any mistakes that are identified, you can replace the data with what you already backed up, which only further emphasizes the importance of backing up all of the data before migration.

With enough planning and a careful approach, data migration can go off without a hitch, leading organizations to reap the full rewards of using and analyzing all the data they collect.Data migration can be particularly tricky when it comes to integrating web data.

Why data migration is important?

Data migration is important  because it is a required component to the upgrading or consolidation of the server and storage in the hardware, or adding data-intensive applications like databases, data warehouses, and data lakes, and large-scale virtualizated projects.

Data migration strategies

 In planning and strategizing the work, teams required to give the migrations their full attention, rather than making them subordinate to do an another project with a large scope. A strategic data migration plan should include the consideration of these critical factors:

Knowing the data — Before migration, source data that should needs to undergo a complete audit. Unexpected problems or failures, it can surface if this step is ignored. Cleanup — Once you identify any problem or failure with our source data, they must be resolved with the help of the strategy. This may required an additional software tools and third-party resources because of the work effort.

Maintenance and protection —The source Data undergoes the degradation after a period of time, making it unreliable. This means there should be controls in place to maintain the data quality.

Governance — Tracking and reporting on the data quality is important because it had enabled the better understanding for the integration of data. The process and tools have been used to produce the data information should be highly usable and automate the  functions where if can be possible. In addition to a structured, step-by-step procedure, a data migration plan should include the  steps  for bringing on the right software and tools for the project. An organization’s which can be specifically, the business should needs and requirements will help establish what’s most appropriate. In addition to, the best strategies fall into one of two categories: “big bang” or “trickle.”

“Big Bang” Migration àIn a big bang data migration, the full transfer is completed within a limited window of time. In the Live systems experience, downtime while the information or data goes through ETL processing and transitions to the new database. The drawback on this method is, of course, that it all happens in one time-boxed event, needs it will be relatively little time to complete. The pressure, though, can be intense, as the business operates with one of its resources offline. This risks a compromised implementation. In this big bang approach, it makes the most sense for your business, consider running through the migration process before the actual event.

“Trickle” Migration Trickle migrations, in contrast, complete the migration process in phases. During implementation, the old system and the new are run in parallel, which eliminates downtime or operational interruptions. In this steps,there will be running in real-time can keep be the data continuously migrating. While Compared to the big bang approach, these implementations can be fairly complex in design; the added complexity — if done right — usually reduces risks, rather than adding them.

Benefits of Data Migration

  • To Maintain the integration of data.
  • Advanced ROI, it decreases the costs of media and storage.
  • To Minimizing the unnecessary interrupted activity.
  • To Minimizing the regular manual effort for the business operations.
  • Boosting the organization production.
  • Maintaining the business growth in the data migration.

Data Migration Examples

Data Migration Tools

  • Amazon RDS
  • Oracle
  • MySQL
  • Amazon Aurora 
  • Microsoft SQL Server
  • PostgreSQL

Data Migration Tutorial

1. Explore and Assess the Source

2. Define and Design the Migration

3. Build the Migration Solution

4. Conduct a Live Test

5. Flipping the Switch

6. Audit