IBM Unveils New Data Fabric Capabilities &#038; Advanced Data Privacy Features For IBM Cloud Satellite
IBM recently unveiled new data fabric capabilities for its Cloud Satellite that further connect data and make it readily available for use even in the most stringent regulatory environments. The IBM Cloud Satellite has now been updated with the inclusion of distributed data processing. Clients can now execute cloud runtimes remotely using IBM Cloud Satellite, which means workloads can be executed wherever the data resides. Because of this ability to execute runtimes in place, data movement needs are further reduced, helping to save up to 47% by minimizing data egress costs, eliminating the need to use different tools on different workloads, and maintaining data sovereignty by allowing data to remain in the geographic area it was created. Advanced Data Privacy features are also being introduced into the data fabric. Through this capability, in addition to dynamic masking of structured data, masking of unstructured data can now be automatically applied consistently, as opposed to the typical manual process. Static masked structured or unstructured data copies can be sent to clients’ desired target data sources. This capability is particularly important for facilitating anonymized training data and the creation of data test sets. In other words, it provides one more way in which the data fabric allows businesses to take full advantage of their data while respecting their customers’ privacy and local regulations.
Clients can now execute cloud runtimes remotely using IBM Cloud Satellite, which means workloads can be executed wherever the data resides.
One more way in which the data fabric allows businesses to take full advantage of their data while respecting their customers’ privacy.
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["programming_languages:R", "AI", "data processing", "Cloud Computing in IT Industry", "R", "Machine Learning", "cloud adoption in emerging markets", "Cloud Computing", "Data Privacy", "IBM", "Data Fabric", "Cloud Data AI", "Cloud Platform"]
["AI", "R", "programming_languages:R"]
Victor is an aspiring Data Scientist &amp; is a Master of Science in Data Science &amp; Big Data Analytics. He is a Researcher, a Data Science Influencer and also an Ex-University Football Player. A keen learner of new developments in Data Science and Artificial Intelligence, he is committed to growing the Data Science community.