First, your legacy assets are likely to be found on a legacy or end-of-life operating system; with metadata that is barely, if at all, usable. If you have retained legacy assets on an obsolete operating system, you: Whichever your situation, moving forward will inevitably require metadata to: This prompts further considerations of security and absent…
Given that data sources may include the following, the chances of your migration (to cloud) working first time round, are very small: Each cloud has its own characteristics and may be informed by: Different data sources require different discovery and preparation: If the source data is in a packaged application, this does not necessarily guarantee…
Data validation tests the accuracy, consistency (of format and standards), quality and integrity of the data (& associated metadata) for onward information engineering, data provisioning and curation. Note that ‘reliable’ data still needs to be validated. Even though this is not its primary purpose, data anomalies revealed by validation techniques can reveal hitherto unnoticed business…
Experience teaches that organisations should consider data discovery services if there is: Since organisations typically have upwards of 80% dark data (data that is unknown to them, and not understood), can you be confident that your organisation is aware of these common data issues? In the age of GDPR companies are expected to know what…
A data audit will help your organisation identify potential: For example, ‘dark’ data: data which is not analysed and from which no value accrues, is now expected to normalise at over 90%+ of unstructured organisational data according to IDC. That means: Dark data may be junk, or it may be a hoard with potential value…
Sorkin’s epitaph to failure should have been the all-time cure for any risk manager suffering from insomnia. but…