If you have feedback for TechNet Subscriber Support, Mary If you have feedback for TechNet Subscriber Support, Thomas, Please remember to mark the replies as answers if they help. Microsoft does not guarantee the accuracy of this information.Īnd if you need to run data Deduplication, please also check the blogs about Sizing Volumes for Data Deduplication in Windows Server Please Note: Since the web site is not hosted by Microsoft, the link may change without notice. Then you could disable it.Īnd after you disable data deduplication on a volume, you can perform all read-only deduplication cmdlet operations on the volume.įor details about d isabling Deduplication, please refer to the article below, On a volume, use the Start-DedupJob cmdlet and specify Unoptimization for the Type parameter first. After you directly disable data deduplication, the volume remains in a deduplicated state and the existing deduplicated data is accessible.
It works on the philosophy of ‘First Time Right’ where it tries and corrects the data at the time of being entered into the system.Based on my knowledge, Disabling Data De-duplication doesn't undupe the data already duped. An insightful reporting and analysis module facilitates comparative studies of all matched records. The deduplication engine allows for a highly configurable score based rule definition and search algorithms to catch even well-disguised matches. The data quality filter standardizes, refines, enriches and validates the data so that anomalies are removed.
The two combine with other features to address data quality issues in a systematic manner.
Duplicate records leading to multiple mailers being sent out to the same customer, or the inability to catch a potential fraud customer even when details exist are some ways that a business can be affected.Īs the name suggests, miFIN™ Data Quality & Deduplication software has two logical components – a Data Quality filter and a Deduplication Engine. Data quality has severe direct and indirect financial impact on a business. Most businesses that run on large volumes of data realize that data doesn’t always translate into information or insight, and this is because of quality issues.
0 kommentar(er)
