From a high-level point of view, data migration is simple: moving data between two or more locations. Yet, in 2021, data migration is much more than moving a folder from one filing cabinet to another. In practice, migrating data is one of the trickiest and most complex data management initiatives for any IT department, especially if you want to follow data migration best practices. With data breaches expected to reach an all-time high by the end of this year and data governance frameworks like HIPAA and GDPR becoming increasingly complicated, you need a data migration strategy that incorporates security, speed, and data compliance. 

Why do so many data migration projects encounter serious challenges? It's often because practitioners fail to observe some of the well-established data migration best practices. In this article, we’ll discuss the seven best practices for data migration.

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With data breaches on the rise, and penalties for data governance non-compliance potentially costing hundreds of thousands of dollars, you need a data migration platform that protects your most prized asset: business-critical information. Integrate.io is the all-in-one ETL/ELT tool that requires no code, so you can move data from one place to another without breaking a sweat. Schedule a demo now.

Recommended reading: Top Challenges of Data Migration?

Why Data Migration Best Practices Are Essential in 2021

Data migration is a necessary part of maturing as a data-driven organization. As the volume, variety, and velocity of big data continue to increase, you’ll likely find that your old systems, software, and databases are no longer suitable for your needs.

That means that you’ll have to move data from the old system to the new one quickly, efficiently, and while keeping downtime to a minimum: in other words, by following data migration best practices. However, this feat is easier said than done. The major issues surrounding data migration initiatives include:  

  • Data Gravity: “Data gravity” is a term coined by software engineer Dave McCrory that refers to the tendency for data and software to “attract” each other over time. As more and more data accumulates in a single location, organizational inertia makes it harder and harder for the data to move away from that location without breaking the applications that depend on it.
  • Compliance and Security: You must protect data from security threats during the migration, both while in transit and at rest. Strict regulations also governed data for certain industries, such as healthcare and finance. Data governance frameworks like HIPAA and Sarbanes-Oxley come with harsh penalties for misusing or mishandling sensitive information. Other data governance principles like GDPR stipulate strict criteria about transferring data from one location to another. Breaching these guidelines can also impact the reputation of your organization and cause you to lose customers. So you'll need to plan a data migration strategy that adheres to the required standards and prevents a PR nightmare.  
  • Legacy Systems: Legacy systems are a fundamental part of many organizations’ data management strategies. However, there comes a time when maintaining your aging, out-of-date infrastructure becomes more painful than the migration itself. Moving data away from legacy systems will require you to define certain data transformations and normalizations to adapt the information to its new resting place.
  • Data degradation: This term refers to the decline in data quality from storing information in one location for long periods. Data can lose its value or contain outdated code or meta information when stored for too long in a legacy system, for example. Remove this data or update it when executing data migration.

The good news is that you can overcome these challenges and ensure a successful migration project if you follow the data migration best practices and recommendations. However, if you don’t carefully strategize and set up the right infrastructure for the move, it’s all too easy for a promising project to fail, preventing businesses from achieving digital transformation.

In the next section, we’ll go over what these data migration best practices are, and what impact they’ll have on your data migration project.

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7 Data Migration Best Practices

Setting the Mission Scope

The path to following data migration best practices starts with defining the parameters of your data migration project well before you begin.

Like any other large IT undertaking, data migration is vulnerable to “scope creep,” in which a project's goals expand over time, causing delays and further complexity. Instead, it’s a good idea to start small when migrating data—for example, moving only the contents of a single database—and then expanding the scope when the pilot is a success.

Start by choosing a date for your data migration project. Doing this can minimize disruption to your day-to-day activities and help you delegate data migration tasks to the right people.

Establishing a Realistic Time Frame

Establishing a concrete time frame is another of the most important data migration best practices. Be aware that large projects can take several months or even as much as a year.

The migration shouldn’t slow down your existing business operations, so spreading it out over time will allow the project to be as minimally disruptive as possible. Give yourself enough room to allow for unexpected delays and extra work.

Investing in the right data migration tool can reduce the time to transfer data from one location to another. The best software automates many of the tasks associated with migration so you can focus on other areas of your business while data transfer takes place. 

Analyzing Data

Data migration initiatives range from the simple to the very complex, based on a few important factors: the size of the data, the type of data you want to migrate, and the source and target systems.

Before the migration begins, take the time to understand how much data you need to move. Are there fields or records that you don’t use? Can you leave that data behind? Is there missing information that you need to fill in from another data source? Also, think about data quality. If data in legacy systems has degraded, you might not want to transfer it to your new location.

Once you take a closer look at the data itself, and how you use it in your organization, you should have a good idea of which data migration strategy to pursue. The two most popular options are “big bang” and “trickle” migrations, based on the speed of the move and how many phases you carry out. “Big bang” migrations are better when you can afford a designated window of downtime, while “trickle” migrations are better for systems that you shouldn’t interrupt.

Cleansing Data

Data migration is a GIGO (garbage in, garbage out) process. If you don't follow data migration best practices from start to finish, you'll simply be moving low-quality data from one place to another; the quality won’t magically improve once it arrives at its destination.

That’s why a large-scale data migration can be the opportune time to perform a “deep clean” of your enterprise data. Removing inaccurate, out-of-date, and duplicate information before the project begins will have a marked impact on your data quality. In addition, if you are executing data migration in phases, you should run testing and validation checks throughout the project to correct any issues promptly.

However, a one-off data cleansing is no replacement for solid, thorough data management policies. Establishing good data governance will pay dividends long after the migration project is complete. You can avoid expensive penalties for data governance non-compliance by adhering to principles like GDPR and HIPAA.

Aligning IT and Business

Data migration is the IT department’s responsibility under the hood, but it affects the entire organization. Getting approval from key stakeholders, and aligning the IT and business teams before the project kicks off, are crucial steps for successful data migration.

IT must understand the overarching goals of the migration, while businesses should be mindful of the technical challenges involved in a project of this nature. Both teams need to collaborate to counteract the harmful impact of data gravity and data silos, which can delay or derail a promising data migration. Many tools can even empower non-technical business users to perform data migrations themselves (see the next section).

Selecting the Right Tools and Vendors

If you don’t have the in-house experience and know-how to follow data migration best practices yourself, then using third-party migration tools and/or vendors is a wise idea. Given enough time and energy, cobbling together a data migration solution on your own is possible. However, your transition will be much faster and smoother if you invest in the right platform.

Do your research to find out which data migration platforms or vendors are best suited for your situation. Tools like Integrate.io make it easy to move data between systems for straightforward data migration projects. This tool lets you adhere to data governance principles and ensure the smooth transfer of data from its source to a final destination like a data warehouse via ETL or ELT. 

If you plan to join forces with a vendor, evaluate them based on the technology they use and their previous experience working on similar projects.

Backing Up Data

Data loss is a frighteningly realistic prospect during a migration. Many enterprises have lost data when migrating to new software from a server. Losing even a few critical records during the migration could be a data catastrophe for your organization. If you lose customer records, for example, consumers might lose trust in your organization and take their business elsewhere. 

To avoid these pitfalls, have a robust data backup and a business continuity plan in place well before the migration begins. It’s also a good idea to first run the migration in a test environment, to make sure that the entire operation is seamless before using it in production.

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In this article, we've covered these best practices for data migration:

  • Setting the mission scope
  • Establishing a realistic time frame
  • Analyzing the data
  • Cleansing the data
  • Aligning IT and business
  • Selecting the right tools and vendors
  • Backing up data

From strategic planning to choosing the right set of tools, these are the recommended steps to follow when moving data between systems. However, data migration is only the first step in the ongoing process of data management.

To ensure you don't fall behind the competition, data migration needs to be a component of your broader data integration and data management strategy to ensure that your databases and data warehouses enjoy access to up-to-date, accurate information. Fortunately, many of these same data migration best practices, such as aligning IT with business and choosing the right tools, apply to the broader field of data management as well.

Observing these data migration best practices—and enacting a long-lasting data management strategy—is a lot easier when you’re using a tool like Integrate.io. It's a powerful, feature-rich data integration and migration platform with a user-friendly, drag-and-drop interface. With over 100 pre-built connections, Integrate.io makes it easy to move data between the systems and software that you need for your data migration project, whether it’s databases and data warehouses, SaaS applications, cloud data storage, analytics tools, and more.

 

Other Integrate.io benefits include:

  • World-class customer service.
  • A powerful REST API.
  • A Salesforce-to-Salesforce connector you won't find with many other data migration tools.
  • Simple workflow creation.
  • Easy UI and drag-and-drop capabilities.
  • No-code data pipelines that make it easier to migrate data for enterprises that lack programming knowledge. Now you can facilitate data migration without complicated code.
  • A simple pricing model that charges users for the connectors they use and not the data they consume. This method could work out cheaper for many data-driven enterprises. 

Want to learn how Integrate.io can make your next data migration project a success? Schedule a demo now.