Data Migration, especially institutions and organizations that are implementing IAM programs that have legacy, proprietary or home-grown systems which serve as pseudo-IAM systems. In order to implement a next-generation IAM system in these organizations then requires migrating data from these existing systems onto a new data model and integrations.
Migrating data is from existing systems involve delicate task of off-boarding applications from old system to a new system while making sure the associated application data is ready in the new system. This transition process requires deep understanding of legacy solutions and their components while leveraging the right tools to take it to its conclusion with minimum impact to users. We have rich expertise in this field and we will work collaboratively with the customer and stakeholders to accomplish this.
Data Cleansing is required when the quality of data is suspect either in the authoritative data source or systems downstream (targets) to IAM and sometimes both. IAM systems are only as good as the data that is fed into them and the associated validation and transformation rules for that data. The consequences of an IAM system that does not have the data it interacts with sufficiently vetted, are serious and can lead to costs associated with user support tickets, spurious errors attributed to the product and last but not the least incorrect audit reports.
We have a long experience with situations where IAM programs had to start with the task of first coming up with tools and processes to clean up the data for consumption. This has allowed us to stock up a repertoire of smart tools for data cleansing efforts that are appropriate to varied situations depending on the customer’s data challenges.