What is Data Migration and Consolidation?


Data migration, data extraction, data integration, data blending… keeping track of all these terms can be harder than actually doing them in the first place. So what’s the definition of data migration and data consolidation, and how can you be prepared to execute them yourself successfully? We’ve got you covered—keep reading for our all-in-one guide to data migration and data consolidation.

Table of Contents

What Is Data Migration?

Data migration, as the name suggests, refers to the movement of data from one location to another. The potential sources and destinations of data migration are numerous: databases, data warehouses, data lakes, flat files, software applications, or any other storage systems where information is kept.

“Data migration” is a catch-all term that describes any migration of data or files between locations. However, the phrase “data migration” tends to refer to a one-time action, rather than a habitual process. There are many possible reasons behind a data migration, including:

  • Creating a new database based on existing information.
  • Replacing a machine (desktop, laptop, server, etc.).
  • Moving data from an on-premises location into cloud storage.
  • Updating a software application.
  • Creating data backups or copies for disaster recovery and business continuity.

Related Reading: 7 Data Migration Best Practices and Tools

What Is Data Consolidation?

Data consolidation refers to the process of combining information from multiple sources in a centralized repository (usually a specialized data warehouse or data lake). In this sense, the term “data consolidation” is often considered synonymous with data integration: data is collected from one or more sources, and then transferred to another location for ease and speed of access.

Note that data consolidation and data migration aren’t quite the same things, although they are closely related.

  • Data consolidation is a “many-to-one” workflow: multiple databases or applications feed into a single target.
  • Data migration, on the other hand, isn’t so neatly defined: it describes any movement of information from one place to another. This means that data migration can describe a “many-to-one” workflow like data consolidation, but it can also be “one-to-one” or even “many-to-many” or “one-to-many” (i.e. propagating data from a single location to multiple destinations). For example, creating a backup of an existing database would be a “one-to-one” data migration: each table is neatly copied and its backup is stored in a different (single) location.

How to Evaluate Data Migration Tools

Efficiently performing data migration and consolidation is essential for businesses that want to get the most from their data—but how do you know which data migration tool is right for the job?

Related Reading: Top 7 ETL Tools

There are a variety of facets and angles by which you can evaluate data migration tools. In this section, we’ll offer a few suggestions for what to consider.

1. Data migration capabilities

At a minimum, your choice of data migration tool should be able to work with the source files and databases that you want to include in your workflow. These may include:

  • Traditional relational SQL databases
  • Non-relational (“NoSQL”) databases
  • Legacy databases with special technical requirements
  • Data warehouses and data lakes
  • Flat file databases (e.g. CSV, XML, Excel files)
  • SaaS (software as a service) applications
  • Hadoop Distributed File System (HDFS) and other distributed file systems
  • Other data types such as message queues, social media posts, EDI (electronic data interchange), etc.

2. Data transformation capabilities

Once the information from these various sources has been extracted, what kind of transformations do you want to perform on it? Possible data transformations may include basic operations (e.g. converting between data types, string handling, simple arithmetic calculations, etc.) as well as more complex operations (e.g. data aggregation, data summarization, data joining, data splitting, etc.).

Make sure that your choice of data migration tool supports the transformations you need for your workflow—or at the very least, supports custom transformations that you can define yourself.

3. Other capabilities

The sky’s the limit when it comes to data migration tools, so think carefully about what your must-haves (and “nice-to-haves”) are. The features you may be looking for include:

  • A graphical interface to visualize the objects and relationships in your data flow easily.
  • Excellent data security practices and compliance with security and privacy regulations.
  • Collaboration and sharing features for team-based work.
  • Support for multiple deployment options, including Windows, Mac, and Linux environments, whether on-premises or in the cloud.
  • Monitoring and analytics capabilities to identify errors and bottlenecks in your workflow.

How Integrate.io Can Help With Data Migration and Consolidation

Choosing the best data migration tool is no easy feat—unless you’ve chosen Integrate.io. The Integrate.io platform is a powerful, feature-rich ETL and data integration tool, with more than 140 pre-built connectors and integrations with your favorite data sources. Despite Integrate.io's rich array of features, it doesn’t sacrifice ease of use: the platform has a straightforward, no-code visual interface that lets any user define robust pipelines to their centralized data warehouse in the cloud.

Ready to see for yourself why Integrate.io is the superior choice among data migration tools? Get in touch with our team of data integration experts today for a chat about your business needs and objectives, or to start your 14-day trial of the Integrate.io platform.

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Glossary of Terms

A guide to the nomenclature of data integration technology.