CLOUD migration

Why Choose Us?

We specialize in migrating data between AWS, Azure, and Snowflake in a seamless and secure manner. Our team of experts has the knowledge and experience to ensure a smooth transition of your data to your desired cloud platform.

COMPETITIVE AND FLEXIBLE PRICES

We offer competitive pricing and flexible pricing options

SUCCESSFUL TRACK RECORD

Our team has a proven track record of successful data migrations

DATA SECURITY

We prioritize security and ensure the confidentiality of your data

PERSONALIZED SUPPORT

We offer personalized support and assistance throughout the entire migration process

How it works

Contact us to discuss your data migration needs and receive a quote.
Our team will work with you to determine the best plan and timeline for your migration.
We will handle the entire migration process, including data transfer, testing, and verification.
We will provide ongoing support and assistance to ensure a successful transition to your new cloud platform.

Steps for Migrating Oracle on-premise data to Snowflake

There are several approaches you can take to migrate data from Oracle on-premises to Snowflake, a cloud-based data warehousing platform. Here is one possible architecture:

Extract data from Oracle: You can use tools like Oracle Data Pump or Oracle’s Export utility to extract data from your Oracle database and write it to flat files, such as CSV or JSON.
Transfer data to the cloud: You can use a tool like AWS S3 or Azure Blob Storage to store the data files in the cloud. Alternatively, you can transfer the data directly to Snowflake using a service like AWS Direct Connect or Azure ExpressRoute.
Load data into Snowflake: Once the data is in the cloud, you can use Snowflake’s COPY command to load the data into a Snowflake table. You can also use tools like Fivetran or Matillion to automate the data loading process.
Transform and cleanse data: You may need to transform and cleanse the data to fit the target schema in Snowflake or to fix any issues that were introduced during the migration process. You can use tools like Snowflake’s SQL commands or custom scripts to perform these tasks.
Perform data validation: It’s important to validate the data in Snowflake to ensure that it was migrated correctly and that no data was lost or corrupted during the migration process. You can use SQL queries or tools like Datical to perform this validation.
Cut over to Snowflake: Once the data has been migrated and validated, you can cut over to Snowflake and start using it as your primary data store. You may need to update any applications or systems that rely on the data to use Snowflake as the data source.

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