Self-Service Data Migration

This documentation explains – in detail – the Akamai Identity Cloud data migration process: the act of moving user data from a legacy system to the Identity Cloud’s user profile store. Suppose that, up until now, you’ve been ...

Data migration is the process of importing user records from legacy systems into the Akamai Identity Cloud. The data migration process can be simple or complex, based on: 1) the state of data at rest in legacy systems; and, 2) the new target da...

In addition to dataload.py (a Python script), a number of other files are required in order to carry out a data migration. These files can be downloaded from the dataload Github repository ( https://github.com/janrain/dataload ). To download the fil...

Because dataload.py is a Python script, you must have Python installed in order to do a data migration. More specifically, you must have Python 3.0 or later installed; previous versions (such as Python 2.7. x , which comes preinstalled on many Macin...

Although there might be  some  exceptions, any data currently stored in your legacy system can be migrated to your Identity Cloud user profile. The one catch is that each field in your legacy system must map directly to an attribute in the...

To carry out a data migration, you must export your legacy data to a comma-separated values (CSV) file; all the user information that you want to copy to the Identity Cloud user profile store must be contained within that file. That sounds easy and,...

The secret to a successful data migration is really no secret at all: if you have “clean” data (defined as data that can be imported as-is into the Akamai user profile store) then the data migration process should go pretty smoothly. For...

The whole idea behind the data migration process is to smooth the transition from your legacy system to the Akamai Identity Cloud: if all goes well, users will travel to your website (or use your app), log on using their same email address and passw...

If a user has only one instance of something – one display name, one birthday, one primary phone number – then databases are easy to construct and to maintain. For example: displayName ...

Data transformations are defined in the Python script transformations.py; if you open that file you’ll see a series of functions similar to this: def transform_plural(value):    """    Transfor...

Dataload.py (with an assist from transformations.py) can convert data from one format to another; for example, you can convert a  Yes  to a  True , or convert the date  7/12/ 1967  to  1967-07-12 . As we’ve seen,...

Before You Begin . If you are using webhooks as part of your Identity Cloud implementation it’s absolutely  imperative  that you disable those webhooks before you do an actual data migration. (You can leave webhooks running if...

Dataload.py includes a parameter  (-x  or  --dry-run , depending on how you call it) that lets you run the script without actually copying data to the user profile store. But why would you even want to do that?  Well, ...

Akamai supports the import of 10,000 records per minute when using dataload.py, which equates to 600,000 records per hour. These upper limits can be helpful in planning, but your actual run time can vary depending on the complexity of the ...

A Delta Migration occurs when you have records that already exist in the Akamai Identity Cloud but might require an update from a legacy system. (For example, the Identity Cloud might include records for beta testers who also have user accounts in y...

There might be times during the execution of dataload.py when network or server errors prevent a batch of records from completely loading into the Akamai Identity Cloud.  Depending on the nature of the error, some records from the batch mi...

During a data migration, dataload.py updates the following log files in real time: dataload.log dataload.log provides a running commentary on pretty much  everything  that happens during a data migration. For example: [2018-...