Protecting Your Data Across the Hybrid Cloud: A Comprehensive Guide

In recent years, an increasing number of organisations have chosen to store their sensitive data in the cloud or across multiple environments. This shift has led to a rise in data breaches and data democratisation—a term used to describe the expanded access to data within an organisation. While data democratisation offers various benefits, it also poses security concerns, as it increases the likelihood of human errors or potential data breaches. With data being rapidly moved to the cloud and stored across multiple environments, many enterprises are losing visibility of their sensitive data, leading to a significant data security and compliance problem.

Understanding Data Democratisation and its Challenges

Data democratisation is the practice of providing access to sensitive and business-valuable data to everyone within an organisation. While expanding data access has several benefits, it also poses security concerns, as it increases the likelihood of human errors or potential data breaches. With data being rapidly moved to the cloud and stored across multiple environments, many enterprises are losing visibility of their sensitive data, leading to a significant data security and compliance problem.

Three Essential Steps to Protecting Your Data Across the Hybrid Cloud

Step 1: Find and Understand Where Your Data is Stored

To protect data effectively, organisations must first understand where it is located, which is particularly challenging when data resides in different places and is managed by various policies. Failure to understand the whereabouts and usage of sensitive data throughout an organisation exposes them to risk. The risks include non-compliance to regulatory requirements and can lead to excessive hoarding of sensitive data when it’s not necessary. It’s both a data security and privacy issue.

Automated, near real-time discovery, network mapping, and tracking of sensitive data at the enterprise level, across multi-platform environments can be achieved with a data discovery and classification platform. Using techniques such as artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and network analytics, it generates a master inventory of sensitive data down to the PII or data-element level. The inventory associates disparate data elements with the relevant data object and provides data lineage, business context, transaction history, and the location of all copies of every data element.

By analysing traffic on an autonomous and continuous basis—as well as data repositories connected to the network—it can detect all elements on the network that are storing, processing, and sharing sensitive data both outside and inside the network. It can “crawl” any repository or database when it is confirmed to or suspected of processing sensitive data, whether it is known or unknown to the enterprise.

In this way, it can give a truly holistic view as to how and where sensitive data is being used, whether it is in motion or at rest, structured or unstructured, in the cloud, on-premises, or on a mainframe.

Adopting a zero-trust approach to data security and privacy means never assuming anyone or anything is trustworthy. This concept requires continuously verifying whether access to personal data should be granted based on each user’s contextual information. The solution’s continuous discovery, monitoring, and cataloguing help round out most of the necessary security capabilities.

Step 2: Monitor and Protect Your Data Across the Enterprise

Now that your organisation is aware of where your sensitive and valuable data resides, the next step is to protect your data throughout the entire lifecycle. Empowering security teams to safeguard sensitive data through discovery and classification, data activity monitoring, vulnerability assessments, and advanced threat detection is crucial. This extends comprehensive data protection across heterogeneous environments, including databases, data warehouses, mainframes, file systems, file shares, cloud, and big data platforms both on-premises and in the cloud.

As enterprises adapt to changes in the business and technological landscapes, data sources continue to proliferate over geographical and organizational boundaries. An organisation’s data—stored across on-premises and cloud environments—is increasing in volume, variety, and velocity. The system is equipped to scale seamlessly from one data source to tens of thousands without disrupting operations due to the following capabilities:

  • Centralise management of operations, policies, and auditing to simplify the aggregation and normalisation of multiple data sources for enterprise reporting.
  • Utilise agent and agentless connections to data sources that help reduce the workload on infrastructure teams. Use at-source monitoring for sensitive data.
  • Monitor less-sensitive data sources with Universal Connector plugins, which offer an agentless architecture that imports native audit logs and normalises the data to prepare it for reporting and analytics, making it fast and easy to connect to modern, cloud-based data environments.
  • Enforce security policies in near real-time that protect data across the enterprise—for all data access, change control, and user activities.

Monitoring security policies for sensitive data access, privileged user actions, change control, application user activities, and security exceptions is crucial.

Step 3: Gain Insights and Analyse the Usage of Your Data

Having protection policies in place is one piece of the puzzle, but another is ensuring your organisation has access to the necessary tools that will provide insights and analyse your data. A data security platform designed to help clients improve visibility into user activity and behavioural risk, meet compliance regulations, protect data more efficiently, and enhance IT flexibility as organisations embrace new business paradigms like moving IT infrastructure and operations to the cloud.

By keeping your data inside of the system, security organisations can streamline architecture, reduce the number of appliances, improve operational efficiencies, and allow data security teams to focus on value-added data security activities rather than infrastructure management. It can ingest data from various sources, including Database-as-a-Service (DBaaS) sources (such as AWS Aurora and Azure Event Hubs) and from the data protection itself.

To help meet data compliance goals, the system provides out-of-the-box policy templates to simplify regulatory compliance. You also have the option to create your custom policies. This allows administrators to define what data is monitored and how it’s captured to meet the specific security and compliance needs of your organisation. You can specify and schedule audit milestones and tasks to help streamline the process of conducting and reporting on a data security audit.

It uses advanced analytics to help data security teams uncover areas of risk, emerging threat patterns, and potential application hijacks. The analytics engine learns which operations and data interaction patterns are normal for a given organisation, and then helps identify suspicious behaviour, potential fraud, or threat-related activities in near-real-time. Users can investigate issues by viewing granular data related to IP address, time, activity, confidence scores related to the analytics, and more. The results of the analytics are processed through the risk-scoring engine and tagged with a high-, medium–, or low-risk score based on the type of anomaly uncovered.

The data security and compliance platform is designed to help clients locate, classify, and take action to help protect sensitive data residing on-premises and in the cloud. Whether you’re looking for a SaaS or software option to help solve your data security and compliance challenges, it has the solution to support your business.

Conclusion

Many companies struggle with siloed security tools, cloud migration, and data democratisation, all of which add additional complexity to their already demanding data security and compliance workflows. Traditional security platforms also tend to be overwhelmed by data volume, often resulting in slow reporting and limited data retention.

Utilising one single tool that can help find and protect data across the hybrid cloud is extremely important, especially during a time when data breaches are more prevalent and costly than ever. A comprehensive data security and compliance strategy can help organisations effectively address these challenges and protect their data across the hybrid cloud environment. Through this comprehensive approach, businesses can ensure data protection, mitigate risks, and comply with regulations, thereby protecting their most valuable asset—their data.