Figure 9 : Cloud Data Security Best Practices
identities between systems will ensure data access can be properly audited and updated quickly , as organizational changes occur and staff leave .
• Data + Data – Data lakes present a unique risk to data security because of the ability to combine data previously stored in separate silos . This presents the risk of data becoming more sensitive than its individual components . Data policies and controls need to account for data that is combined , to become sensitive and ensure adequate controls are in place to warn users and control the flow of data .
Closing
Many organizations are looking to technologies like machine learning and predictive analytics to enable them to be more effective at targeting prospects , supporting customers , building effective products and responding to market needs . To effectively leverage these technologies , an organization must first develop a solid infrastructure to store data , execute analytical workloads and protect its data assets from unexpected change or compromise . A cloud-based data lake provides organizations a flexible platform for data storage and processing , while providing near endless scalability , with high levels of availability .
When building a data lake , start with specific use cases that can be architected for and proven ; those will enable the organization to effectively grow capability as the users of the data lake increase . Cloud-based data lakes have the added benefits of easily adding new capabilities as the cloud providers increase their feature portfolio , as well as gaining advantages from leveraging the deep expertise in scale and security the cloud provider provides .
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