Ideal Scenarios
For unstructured data, the use of AI/ML supports semantic analysis and data discovery. For example, depending on the context, a date can be a date of birth, a purchase date, or delivery date in the purchasing life cycle. Each data type will need an appropriate level of protection.
In summary, for data security there is no one single panacea solution. There are evolving gaps, which are driving the need for tools that orchestrate and integrate controls across data security, identity access management (IAM), and privacy and application management tools and platforms. In the meantime, it is important as new technologies are added to address emerging data security use cases, to use a digital security guard (DSG), a data recovery agent (DRA), and a privacy impact assessment (DPIA/PIA) to create data security policies that address these product shortcomings or gaps. The emergence of new technologies such as DSP (digital security program) and DSPM (data security management) is expected to help bridge these gaps in a more orchestrated, scalable way. Continued innovation in data protection techniques has seen the emergence and growth of confidential computing, differential privacy, homomorphic encryption, zero-knowledge proofs, SMPC (secure multiparty computation), and KMaaS (key management as a security). Technologies that can monitor user activity with data are evolving, such as cloud-native DLP (data loss prevention), multi-cloud DAM (database activity monitoring), DSaaS, and DSP.
Practical Use Case for Data Governance and Data Democratization
Following is a business use case that provides a real-world example of how combining data governance and data democratization helped an organization.
An assessment was done to find out how to improve the efficiency and effectiveness of the data and education analytics landscape of AI Fabric School.
AI Fabric School (pseudonym) was under pressure to improve outcomes and efficiencies in all aspects of its operations, with severe shortages in faculty and staff adding to this pressure. The effective use of data and analytics offers a means to do so. Increased and better use of data will be a key differentiator among organization going forward.
After talking to analysts from all departments, it is found that there are multiple pain points and multiple things to do to improve the data and analytics maturity of AI Fabric School. The organization is facing multiple issues that lead to wastage of resources, time, and money.