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  • The Bluemetrix Team

Cloud Migration: Transfer Your Data to the Cloud in Three Easy Steps

In this blog, we’d like to give you an overview of the steps required to tokenize sensitive data, migrate the data to the cloud, and then de-tokenize the data once in the cloud.

We are using our BDM platform and the cloud provider is AWS.

Step 1. The pipeline

Let’s start with the pipeline. In our example, we’re getting data from an Oracle data warehouse which includes sensitive employees’ data, such as emails, credit cards details, and banking information among other data.

We can select a column we can define a routine tokenization for the data therein. Once the routine tokenization has been implemented, the email format will still exist, but the content will be masked (for more on this topic, see here ).

Each column in the table is tokenized individually and done via ‘no-code’ and in a user-friendly UI. This is advantageous for organisations, as developers are not required to perform the tokenization.

FPE Tokenization

In our example below, we are saving our anonymized data as a CSV output to an S3 bucket, and then we run the job.

Anonymize CSV to S3 bucket

Step 2. The integrity of a dataset

By using BDM, the platform allows you to preserve the integrity of a dataset while moving data to the cloud. This is ideal for departments that are concerned about data migration such as HR.

Typically, a HR Department will have a lot of sensitive data covering BICs, IBANs, emails, social security numb