Artificial intelligence (AI) could boost company productivity by 1.5%, increasing S&P 500 profits by 30% over the next 10 years. The rapid success of generative AI technologies such as ChatGPT is an excellent example of how companies can shape their fortunes by harnessing the power of the data they hold. The insights from data enable businesses across sectors to generate new revenue opportunities, improve customer experiences, and drive process efficiencies.
With organizations anticipating these gains, data collection across the globe has skyrocketed, with IDC predicting 175 zettabytes of data worldwide by 2025. This data explosion has created new data control challenges for companies. With nearly 60% of corporate data in the cloud and 80% of organizations adopting a multi-cloud strategy, companies must carefully manage their data, especially sensitive and personal data, dispersed across various cloud providers, data systems, and SaaS applications.
For organizations to safely harness the power of data, they must be able to secure it from threats, honor individual privacy rights, govern data usage responsibly, and comply with varying regulatory requirements around the globe.
To fulfill these evolving data obligations, organizations must enable their respective data security, privacy, governance, and compliance teams with shared intelligence around sensitive data and automate tasks necessary to collaborate and enforce data controls. A unified data controls (UDC) framework helps organizations to meet this objective, allowing them to unlock the value of their data without sacrificing agility or control.
Establishing a Unified Data Controls Framework
There are several critical components to implementing a successful unified data controls architecture. Ultimately, an organization can only protect its data if it can locate its data assets, especially shadow data assets unknown to IT teams. The discovery and classification of data are critically important, particularly classifying data that may be considered sensitive per internal company policies or compliance regulations, such as the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and various other laws.
As part of the classification stage, data must be enriched with metadata insights that security, privacy, and governance teams need. This phase is also an opportunity to map data processes and review lineage to understand how data is used across the enterprise. Investing ahead to build this foundational intelligence around sensitive data can help streamline various data security, privacy, and governance controls across the company.
Data Governance teams can automatically build data catalogs with discovered datasets and metadata insights. A comprehensive catalog can then enable data analysts and scientists to quickly find the data they need and determine whether it fits their use.
The data privacy team can synchronize process changes with internal and external data privacy policies. This ensures transparency with customers and alignment with internal data user teams. When collecting or using personal data, teams can identify regulatory requirements and track individual owners of that personal data across the data landscape. These personal data insights can automate various privacy operations, from managing data consent to honoring subject rights.
From a security standpoint, organizations can prioritize the remediation of security posture risks such as system misconfigurations and unauthorized data access based on data sensitivity insights. Role-based access controls can be fine-tuned, and sensitive data elements can be masked to ensure the least privileged access and compliance with cross-border data transfer requirements. Managing data breach risk also becomes easier when organizations can assess the financial impact and automate breach response steps before and after an incident.
Benefits of Adopting a Unified Data Controls Framework
An effective UDC architecture ensures that all teams, across data security, privacy, governance, and compliance functions, operate from a common source of truth for data and automate activities to ensure faster and safer data access for value generation activities.
Besides data agility, by classifying and analyzing data just once across teams, organizations can streamline operations and achieve consistency of results to reduce the overall cost of data governance and the risk of compliance with laws and regulations.
Maximizing Data Utilization with Control
An organization’s most critical data obligation is to ensure its data is accessible and usable by business teams. With organizations using only 32% of available data to inform decisions, the potential upside of improved data utilization by implementing a UDC framework is massive. As a result, adopting a UDC strategy to manage complex but modern, hyperscale multi-cloud environments is an effective way to meet data obligations, and is quickly becoming the standard for building a data-centric culture across companies.