Old data migration is essential for digital transformation of any enterprise. There are various reasons why it is required to keep old data – 10 years retention period due to legal regulations or GDPR. Historical data are valuable even now for forecasting or as input for machine learning. They may contain information needed for your present business.
These old data are often stored in legacy systems such as Lotus Notes / IBM Domino or even as unstructured data from log files or in various other formats. We offer you the possibility to export, cleanse, and map the old data to new structures. We export data from Document Libraries, TeamRooms, DocStores (Document Stores) or extract old Mailboxes.
Another regular source of data are SQL databases based on older OpenSource systems such as WordPress, Forums, or any kind of knowledge management system similar to Wikipedia.
The target can be either structured text in folders or we can export into new SQL databases, Mongo DB or provided even into a REST Based API.
The regular steps to perform a proper migration are outlined below:
During the initial data audit, we try to understand in which format the data are, how large they are and how complex are the data structures within the data. Important is also the level of confidentiality that needs to be kept. At the end of this phase we try to secure a representative data sample for development and testing. This can be non-critical data from the source system or even synthetic data in a proper structure.
In this phase we describe the steps of the migration procedure.