Cloud migrations are complicated, high-stakes projects. But there are strategies teams can use to make cloud migrations faster, easier, and less stressful. Learn how to do all of this in our latest eBook, 6 Keys for a Seamless Cloud Migration! Here’s an excerpt – download the full eBook at the bottom of the page.

1. Choose an ELT Over ETL

Data integration solutions streamline the migration of internal and external data sources into a cloud data warehouse. Many teams use data integration solutions to facilitate and expedite cloud data migrations. Your team will likely choose between two data integration technologies: ETL or ELT.

ETL (extract, transform, and load) extracts raw data from sources, transforms the data on a secondary processing server, and then loads the data into a target database. ETL is used when data must be transformed to conform to the standards of a target database.

ELT (extract, load, and transform), unlike ETL, does not require data transformations to take place before the loading process. ELT loads raw data directly into a target data warehouse, instead of moving it to a processing server for transformation. The data is transformed inside the cloud data warehouse itself.

ELT is generally more flexible, efficient, and scalable, and is ideal for:

  • ingesting large amounts of data
  • processing data sets that contain both structured and unstructured data
  • powering diverse business intelligence with raw data repositories

ETL is more suited for:

  • compute-intensive transformations
  • systems with legacy architectures
  • data workflows that require manipulation, such as PII erasure

ELT solutions have a big advantage over ETL solutions during cloud migrations. While ETL requires the data to pass through a secondary server for transformation, ELT loads raw data directly into a cloud data warehouse. By bypassing the secondary server, ELT speeds up the data migration process significantly.

2. Eliminate Technical Grunt Work

Technical grunt work bogs down many data projects, and that’s especially true for cloud data migrations. The volume of data handled during a migration is often enormous. Mundane tasks, such as developing data pipelines for each individual database table, add up and waste your team’s limited time and resources.

Make your life easier: focus on solutions that eliminate this kind of technical work. Here’s a checklist of features to consider:

  • Fully managed
  • No-code
  • Auto-scalable
  • Pre-built data connectors
  • Data process automation

Fully managed solutions handle everything on the back-end of the platform, eliminating maintenance tasks. Auto-scalability manages resource limits and system allocation automatically. No-code platforms require zero user-programming. Your developers have more important projects to work on.

Pre-built data connectors save a huge amount of time and energy. Many teams have to manage dozens of internal and external data sources, and building data connectors for each one is not feasible. Pre-built data connectors eliminate this unnecessary investment and allow your team to perform a cloud migration with plug-and-play functionality.

Automation also makes cloud migrations much more efficient. Automated features such as change data capture, Rivery’s Auto-Migration, pipeline scheduling, and automatic table merging make cloud migrations faster, smoother, and less prone to human error. This streamlines the migration process, while improving data integrity and data security.

Download the Full Ebook for More!


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