Without a secure-by-design approach, organizations inevitably encounter critical hurdles in securely utilizing AI to process customer data, governing user and role access to specific AI functions, and ensuring that every AI action is secure, compliant, and auditable.

Navigating this landscape with an immature platform or a bespoke DIY approach often results in discovering these gates reactively—such as unchecked AI agent access to sensitive data or overly permissive user roles—delaying time-to-value, introducing reputational and security risks, and forcing internal teams to solve complex, foundational security problems from first principles.

A mature customer data platform (CDP) proactively addresses potential challenges. By integrating a secure-by-design approach from inception, CDPs leveraging AI agents and features must meet strict security requirements through adherence to the fundamental tenets of Defense-in-Depth and Zero Trust. Treasure Data’s AI Agent Foundry exemplifies this by embedding granular security controls directly into the architecture. 

As further evidence of our commitment to Responsible AI, the AI Agent Foundry has earned TrustArc’s TRUSTe Responsible AI Certification. As the first-ever AI certification focused explicitly on data protection and privacy, TrustArc’s certification is a strong third-party validation that Treasure Data’s processes align with Responsible AI principles – including fairness, transparency, accountability, and more.

Let’s walk through how Treasure Data’s secure-by-design methodology converts potential impediments into manageable, secure functionalities.

Top challenge 1: Controlling AI agent processing of customer data

The challenge: The risk associated with leveraging AI agents to process customer data is twofold: 

• Protecting customer data from exfiltration by a compromised agent
• Preventing the agent from being manipulated into processing unauthorized or out-of-scope data. 

In modern Retrieval-Augmented Generation (RAG) architectures, an agent directly retrieves data from a database to perform queries. This introduces a significant vulnerability where a maliciously crafted prompt can coerce the agent into accessing and exposing sensitive information far beyond a user’s authorized scope.

Risk management strategy: Risks in modern CDPs that leverage AI agents must be managed through Zero Trust principles, assuming a breach is always possible. The core principle is continuous verification of an agent’s instructions and execution environment:

• Strict input controls: All prompts and parameters must be validated and sanitized before reaching the agent to filter malicious instructions.
• Explainability: On a platform full of rich personal data such as a CDP, transparency in data processing is critical. AI agents must demonstrate the step-by-step chain of thoughts in its reasoning. Any change actions must be confirmed by the human in the workflow design.
• Principle of least privilege: The agent must be granted credentials that only permit access to specific, pre-approved segments of data, providing a final layer of enforcement at the data source.

A best practice (collaborative governance): Effective AI security hinges on continuous human cooperation. Security engineers, data scientists, and developers must integrate security from the start, applying strict input controls, explainability, and least privilege. End-user collaboration, through training and clear guidelines, creates a collective human firewall by enabling users to understand AI interactions and report suspicious activity.

Top challenge 2: Maintaining granular, context-aware permissions

The challenge: Within a modern CDP, numerous users with diverse roles interact with various AI agents. Static, one-size-fits-all permission models represent a significant liability. They create a high risk of privilege escalation, unauthorized data exposure, and misuse of agents beyond their intended scope. Such vulnerabilities can lead to severe privacy violations and security breaches involving sensitive customer data.

Risk management strategy (Defense-in-Depth): This challenge is addressed by implementing a Defense-in-Depth technology stack. The core tenets of Zero Trust are crucial for managing granular access:

• Continuous monitoring and validation: Access to customer data via AI agents cannot be treated as a static, one-time permission grant; it requires constant authentication and authorization, verifying the user’s identity, the agent’s context, and the specific data being accessed in real-time.
• Least-privilege access: Users are granted the minimum necessary access to data through specific agents. Concurrently, the agents themselves are given the required minimum permissions based on the user’s permissions and the particular task. This model ensures a user can only access data relevant to their task and that the agent acts strictly within that defined scope.

A best practice (collaborative governance): Effective management of AI agent permissions necessitates a collaborative approach that involves cross-departmental teams. Business leaders, data owners, and security architects should collaborate to define user roles and the necessary data access for AI agents, ensuring alignment with business needs and compliance regulations. 

Security and compliance teams are then responsible for translating these policies into technical controls. Continuous education is also vital, teaching users about the principle of least privilege and the importance of reporting any violations.

How Treasure Data delivers Zero Trust security for AI Agent Foundry

We support customers with Zero Trust expectations for their AI initiatives by embedding security principles directly into our platform architecture. 

We deliver a rigorous Zero Trust security posture for the AI Agent Foundry by adhering to the core pillar of “Never Trust, Always Verify.” This is achieved through per-request authentication and permission checks for all human and agent actions, which defends against both internal and external misuse by eliminating any form of implicit trust. 

This foundation is supported by a comprehensive set of compensating controls that emphasize least-privilege policies and deep visibility through auditability for all AI agent workflows.

1. Policy-based permissions (PBP): Enforcing least privilege access

At the core of our Zero Trust strategy for AI Agent Foundry is our Policy-Based Permissions (PBP) model, designed for fine-grained control over access and actions. This system enforces the principle of Least Privilege Access by applying permissions at the most granular level possible—down to individual projects, agents, and datasets.

Permissions in the AI Agent Foundry are assigned through policy configurations to different user roles, such as prompt engineers, data product managers, or general end users. These permissions include:

• Agent and knowledge base management: The ability to create, edit, and delete custom agents, knowledge bases, and user prompts.
• Integration management: Control over internal integrations, like connecting to Parent Segments for audience generation, as well as external connections, such as Webhook or Slack integrations.
• Generic chat access: Permission for users to interact with chat features without having any administrative rights to create or modify the underlying agents.

This granularity enables precise security postures. For example, a marketing user might only have permission to use the Audience Agent chat feature, while a prompt engineer can create and edit agents but not expose them via external integrations.

2. Premium audit logs: Deep visibility and traceability into AI Agent Foundry actions

We provide deep visibility and accountability for all activities in the AI Agent Foundry through premium audit logs, which are designed for high-integrity security monitoring.

• Comprehensive event capture: Actions performed within AI Agent Foundry are captured in detailed, immutable audit logs.
• Seamless SIEM integration: Customers can export audit logs for as long as they wish and integrate them directly with their own Security Information and Event Management (SIEM) platforms.

Building trust as the foundation for AI innovation

The journey to leveraging AI on sensitive customer data is a foundational test of trust. As we’ve explored, the two critical hurdles of controlling AI agent access and maintaining granular user permissions are not insurmountable obstacles, but rather essential security gates that must be addressed proactively.

Attempting to navigate this complex terrain with bespoke solutions or immature platforms often leads to reactive, costly, and high-risk fire drills. In contrast, an Intelligent CDP like Treasure Data provides the necessary guardrails for secure innovation. By embedding security into the architecture—through concrete features like Policy-Based Permissions and comprehensive audit logs—enterprises can confidently deploy powerful AI capabilities without compromising on safety or compliance.

Ultimately, the goal is to transform security from a barrier into an enabler. A secure-by-design approach doesn’t just mitigate risk; it accelerates time-to-value, builds lasting trust with customers, and unlocks the strategic advantage of AI. This commitment to security and responsibility is the cornerstone of any successful enterprise AI strategy.

The post Secure AI Deployment in Enterprise Customer Data Platforms first appeared on Treasure Data.

However, implementing AI in a practical and trustworthy manner isn’t easy to pull off. For many, understanding how to best incorporate AI Agents into work processes is uncharted territory, and doing it right is critical. Workday understands this well. The HR Services provider is facing a collective-action lawsuit that says it built AI Agents that illegally discriminated against older job applicants. 

Building trust with customers has always been an important part of doing business, but it’s now more important than ever as we look at how to build trust in the AI systems we use every day. At Treasure Data, we understand the drive to incorporate AI into business processes to meet the evolving needs of our customers, and we recognize that this must be done in a manner that is well-governed, secure, and trustworthy. So, we thought we would share some insight into how we’re doing exactly that for our customers with the AI Agent Foundry and Amazon Bedrock.

The genesis of trust: Treasure Data AI Agent Foundry

The Treasure Data AI Agent Foundry is an enterprise-grade toolkit for building compliant, auditable, and secure AI Agents in the Treasure Data Customer Data Platform (CDP). The Foundry is a core component of the CDP, not a standalone offering, which means agents adhere to the CDP’s governance framework.

Because the AI Agent Foundry is deeply embedded in the CDP, agents are trained on clean, unified, and permission-controlled customer data (what we call the Diamond Record). Every response, recommendation, or action from an agent is rooted in accuracy, reducing the risk of hallucinations or out-of-context guessing. 

Whether you want to improve personalization or identify opportunities to innovate or develop more efficient processes, AI Agents can provide many benefits. 

The Foundry includes a number of pre-built AI Agents that automate many marketing use cases, including:

• Segment discovery (Audience Agent)
• Campaign planning (Deep Research Agent)
• Content generation (Content Generator Agent)
• Journey optimization (Journey Optimizer Agent) 

You can use any of these agents, customize them to fit your needs, or build custom agents to support your organization’s unique challenges. You can also implement multi-agent orchestration, where an agent can call or delegate tasks to other agents to complete an end-to-end workflow.

Why Amazon Bedrock?

The AI Agent Foundry is built on the Amazon Bedrock infrastructure. Amazon Bedrock is a fully managed service that provides access to a number of foundation models (FMs) from leading AI companies, including Anthropic, DeepSeek, Luma, Meta, Stability AI, and Amazon’s own AI models, along with a broad set of capabilities needed to build generative AI applications. Our decision to use Amazon Bedrock’s infrastructure is based on privacy, security, and scalability.

Bedrock allows us to scale AI applications effortlessly, ensuring our customers have the flexibility they need to grow and adapt. 

With Amazon Bedrock, you can put guardrails in place to build AI Agents safely and responsibly. You retain full control over the data you use to customize a foundation model for your AI Agents, and that data stays under your control. It’s never shared with an FM or used to train their base models. 

Let’s look at some of the reasons Amazon Bedrock is the right AI infrastructure for the AI Agent Foundry. 

Built-in security for trustworthy AI

Amazon Bedrock provides a multi-layered security architecture. From end-to-end data encryption, to virtual private cloud (VPC) and network isolation capabilities, to robust identity and access management control (IAM), and built in threat detection, you get the security and control you need to safely adopt generative AI.

For example, with fine-grained IAM controls, you can precisely define who has access to which data, models, or actions. Resource-based policies add another layer by attaching permissions directly to individual assets. Together, these controls help ensure sensitive data is only accessible to the right people.

To keep your data protected in transit, Bedrock supports private connectivity through Amazon VPC endpoints, which keep traffic off the public internet. Identity-based authentication further strengthens security by verifying every user or system requesting access and enabling full monitoring.

Governance and compliance, built in

The requirement to stay compliant with industry regulations is critical and Bedrock builds governance into its foundation. It aligns with key industry standards and regulatory requirements through automated compliance checks, helping you maintain compliance with less manual effort, and provides automated reasoning tools to act as intelligent guardrails, proactively ensuring compliance and reducing the risk of human error. 

Bedrock also includes two tools that actively monitor and track system activity:

• Amazon CloudWatch provides real-time monitoring, detecting and addressing anomalies and potential breaches.
• AWS CloudTrail provides detailed audit logs documenting all activity ensuring transparency and accountability.

How Amazon Bedrock protects your data

We mentioned the security of your data above but let’s go a bit deeper because it’s essential to understand how secure your data is. First of all, no sensitive data is persistently stored within Bedrock. It also applies data anonymization and data masking to enhance data privacy so even when sensitive information is processed, it’s obscured and protected.

To further strengthen data protection, Bedrock includes secure claims management using Amazon DynamoDB, which helps ensure that all data interactions remain secure and reliable. And it includes automated backup systems that help preserve data integrity and enable quick recovery in the event of a failure or incident. 

Operational benefits that reduce risk

Amazon Bedrock is a fully managed service, which means you don’t need to worry about maintaining security infrastructure or applying security patches. The service does it all for you. 

In addition, real-time security monitoring and proactive threat detection means potential risks are identified and verified before they can impact your operations.  

Building trust with our customers

At Treasure Data, we believe that exceptional experiences and AI hinge on trust. The more you adopt AI into your processes and the more autonomous your AI Agents become, the more critical trust becomes. 

We believe that our partnership with Amazon Bedrock improves both our operational capabilities and our ability to ensure you are implementing trusted AI Agents. Our commitment to you is a reliable and trustworthy foundation that is secure, compliant, and efficient. 

A trusted foundation for AI Agents

As AI becomes more deeply embedded in how businesses operate, building trustworthy, well-governed AI Agents is no longer optional. It’s essential. Treasure Data’s AI Agent Foundry, built on the robust and secure infrastructure of Amazon Bedrock, offers enterprises a powerful yet responsible path forward. 

With built-in governance, compliance, and data protection, it ensures AI Agents not only perform effectively but do so in a way that inspires confidence and trust. For organizations looking to scale AI adoption without sacrificing security, transparency, or control, this is the foundation that makes trustworthy AI a reality.

We invite you to join us in transforming your business with trustworthy AI Agents. Contact us to explore how you can leverage the built-in AI Agents in the AI Agent Foundry or create your own trusted agents built on the secure foundation of Amazon Bedrock. 

The post Building Trustworthy AI Agents with Treasure Data’s AI Agent Foundry and Amazon Bedrock first appeared on Treasure Data.

“With great power comes great responsibility.” – Uncle Ben, Spider-Man

It starts with the right mindset

We talk about the 2 billion customer profiles managed in our CDP a lot. And we know that, as customers ourselves, our profiles are included in that number. So we have a vested interest in the security of that data, and we treat it with the seriousness it deserves – never compromised, never lost, never overlooked. 

Aisha Khan, CIO and Chief Information Security Officer (CISO) at Treasure Data, explains how we build trust into every layer of our company culture. 

“We don’t want to be a company that does bare minimum security. Many people think compliance equals security, so they will only go and chase compliance frameworks. Compliance does not equal security. It can help you on your journey, but having a comprehensive security strategy is the key.”

How we keep your customer data safe and secure

It’s not enough to say we keep 2 billion customer profiles secure. Treasure Data walks the walk. It starts with having the right mindset, but equally important is having the right frameworks, protocols, and processes in place, including trustworthy AI. 

Let’s look at three broad areas – security and privacy, AWS infrastructure, and trustworthy AI – in a little more depth.

Area 1: Security and privacy 

With the safety and security of our operations and data a top priority, we follow some of the most stringent security and privacy protocols available. For example, Treasure Data meets a broad range of the certifications required by global enterprise customers, including ISO/IEC 27001, SOC 2 Type 2, HIPPA and ISO/IEC 27701 etc.

But it doesn’t stop there. At Treasure Data, we take a comprehensive approach that spans security, privacy, responsible AI, and data governance. Learn more in our Trust Center.

Area 2: AWS partnership

Treasure Data is a proud partner of Amazon Web Services (AWS). We are an AWS Advanced Technology Partner Independent Software Vendor (ISV) and have achieved various competencies that demonstrate our deep partnership.

The Treasure Data CDP is built on an AWS technical infrastructure bedrock, giving it the benefits of all of AWS’s policies, architecture, and operational processes. It gives us the flexibility and agility to manage security with confidence.

Ronak Shah, Principal Architect at AWS, shared how seriously we take security:

“So at AWS, we lead with security. We say, security is job zero. And Treasure Data’s team demonstrated that day in, day out.”

Area 3: Trustworthy AI

Treasure Data believes that AI is the future. It gives our customers superhuman powers, and we’re on a mission to incorporate AI into every part of our platform. 

But with that mission comes important questions and things to consider, especially in terms of security and compliance. How do we ensure the AI can be trusted with our customers’ customer data?

For starters, when building AI capabilities, we include controls to ensure AI behaves ethically, legally, and within the scope of your business policies. In addition, our AI-native approach minimizes the reliance on third-party AI tools. This reduces the risk of data spillage.

Second, we choose to partner with AWS and build our own AI Agent Foundry on top of Amazon Bedrock. This partnership ensures that our AI solutions are not only powerful but also trustworthy and secure.

Finally, we believe in transparency by design. We’re building toward a future where every action is traceable, explainable, and auditable. Our users will always understand how their AI agents operate.

Wrap-up: We take trust seriously, but don’t take our word for it – see it for yourself

To earn the trust of over 2 billion consumers, we have to hold ourselves to a higher standard. Trust isn’t given, it’s earned. And we work hard to earn that trust every day, in every line of code, every security protocol, and every product decision we make.

In everything we do, we act with that trust in mind, and we invite you to get in touch to learn more.

The post Peek Inside Treasure Data’s Security Approach for 2+ Billion Customer Profiles first appeared on Treasure Data.

The increasing threat of cyberattacks makes it imperative for businesses to protect sensitive data from unauthorized access, theft, or malicious behavior. Here’s how businesses can use governance, risk, and compliance (GRC) to enable cybersecurity.

What Is GRC?

GRC, also known as governance, risk, and compliance, is a crucial business strategy that covers a firm’s governance, enterprise risk management, and regulatory compliance. Let’s break it down: 

Governance 

Data governance ensures that the business policies and operations align with strategic goals. It involves developing several risk identification, evaluation, and management processes that align with the business guidelines. Established governance policies enable senior management and C-suite leaders to monitor data and make informed decisions for the best business outcomes. 

The key components of governance include:

• Corporate management
• Policy management
• Strategy management
• Risk Management

Risk Management

Risk management allows senior management to mitigate potential cybersecurity risks and protect the business against cybercrime. 

The key components of risk management include:

• Risk identification and assessment 
• Best practices for risk mitigation
• Data monitoring 

Compliance

Compliance programs are the rules of the government, market, or specific domain in which a business operates. From a cybersecurity standpoint, compliance requirements ensure that sensitive customer data is safe and protected, and meet the data privacy and security guidelines of government entities. 

The key components of compliance for cybersecurity include: 

• Cybersecurity protocols and measures
• Internal and external audits and controls that are compliant with industry or government standards
• Best practices to demonstrate data security and legal compliance 

GRC Software and Cybersecurity

Establishing a governance, risk management, and compliance (GRC) framework helps align professionals and day-to-day operations with business goals – while managing risks and regulatory needs.

Data security teams perform rigorous tasks, such as conducting gap analysis, centralizing policies, identifying misconfigurations, and monitoring data to prevent data breaches and ensure successful GRC implementation. However, these tasks can be time consuming, and may lead to human errors that leave operations open to risk. 

Hackers can exploit insecure entry points, such as code repositories, applications, software and cloud assets, to steal a company’s data. Compromised data security can prove detrimental to a company’s reputation, which can lead to costly fines, and a breach in consumer trust that can impact ROI in the long term.  

For risk management, businesses should ensure the security of their digital assets, including cloud devices, software, and more. With the right GRC tools, businesses can automate tasks and implement a successful governance, risk, and compliance strategy.

Understanding GRC Solutions

There’s a ton of cyber asset management tools available, including network security software, endpoint security solutions, cloud security posture management (CSPM), and cyber asset attack surface management (CAASM). Unlike other GRC software, CAASM helps uncover and control vulnerabilities across connected cyber assets. It also maintains and updates cyber asset inventory, and provides a unified view of data in real time.

In addition to cyber asset management, GRC tools offer the following provisions: 

Vulnerability and Incident Response

GRC tools help supplement incidents and cyber vulnerabilities with the required context for initial assessment and response. It enables the security team to find answers to critical issues, such as the blast radius of a compromised system, and identifying applications that are at the highest risk of getting attacked. 

Governance and Compliance

GRC tools can map relationships between all frameworks and controls. This helps the security teams identify cybersecurity gaps and compliance status. Security teams can identify external users, provide access to specific systems, data, or services, revoke the rights of offboarded users, and check user activity status. GRC tools also help automate compliance testing for cybersecurity policies and frameworks, like: 

• Health Insurance Portability and Accountability Act (HIPAA)
• Payment Card Industry Data Security Standard (PCI DSS)
• National Institute of Standards and Technology (NIST)
• Service Organization Control Type 2 (SOC2) Security
• Center of Internet Security (CIS)

Power Your Organization’s Cybersecurity with GRC

Cybersecurity is crucial for all types of businesses. While cybersecurity involves protecting a company’s data, system, and network information, establishing a GRC framework communicates the best way to achieve business goals while ensuring data security.

From providing cyber asset management, to automating data security tasks and delivering enhanced visibility across the enterprise, GRC tools help businesses make informed decisions to keep their data safe.

Read more about data privacy, governance, and compliance here.

The post What is GRC, and How Does It Enable Cybersecurity? first appeared on Treasure Data.

What Is Data Security?

Data security focuses on protecting data against malicious attacks and threats like data theft, unauthorized access, exploitation, and disclosure. Data breaches remain a major concern for companies and organizations: highly publicized breaches can affect a company’s reputation as well as business operations, client relationships, and even financial stability. Targeted companies may face regulatory fines and legal penalties for compromising consumer data.

Cybersecurity professionals employ several methods to secure data from attacks.

• Data encryption: A cryptographic algorithm encodes data into another form so only authorized persons with a secret key can access or decrypt files.
• Data backup and recovery: Applies disaster recovery (DR) technology like cloud storage or off-site servers to restore original data in case of corruption or breach.
• Masking: Uses a realistic but inauthentic version of the original data to hide sensitive information from hackers.
• Destruction: Ensures data is completely and reliably destroyed from systems to prevent unauthorized retrieval and/or disclosure.

What Is Data Privacy?

Data privacy concerns controlling how data is collected, used, stored, and shared within legal bounds. For consumers, data privacy is the right to determine to what extent organizations use their personal and sensitive information. Data privacy also entitles consumers to the right to be forgotten by companies and/or organizations that store their information.

Data privacy extends to general confidential data such as intellectual property, internal reports, and corporate and legal records, among others.

Data privacy is a direct, logical result of strong data security. When data is safe from misuse and malicious attacks, it is easy to implement protocols around proper, consensual handling of personal information. When security is compromised, however, it’s a lot harder to keep information private.

Nevertheless, data privacy is NOT data security, nor vice-versa. Data security deals primarily with external threats while data privacy involves internal governance of data usage and sharing. While many different industries understand and implement data security as a straightforward concept, the definition of data privacy varies across geographical and legal contexts (e.g., national vs. international consumer privacy laws).

Data Security and Privacy Landscape

Digital transformation has radically altered the playing field for most businesses. Omnichannel readiness, digital customer experience, and dynamic personalization now offer just as much competitive advantage as a company’s products and services. As the consumer-brand relationship becomes increasingly digitized, concern about data privacy and security has incurred a multitude of regulations around the world.

Let’s take a look at how national and international privacy laws are shaping the data security landscape today and what businesses need to do to maintain compliance.

United States

The U.S. has had its eye on consumer data privacy for some time. The coming new year will see a number of bills become state laws, including:

• January 1, 2023: The California Privacy Rights Act and the Virginia Consumer Data Protection Act take effect.
• July 1, 2023: The Colorado Privacy Act and the Connecticut Data Privacy Act take effect.
• December 31, 2023: The Utah Consumer Privacy Act takes effect.

These are merely precursors to more privacy bills that are already on the way. A privacy legislation tracker from the International Association of Privacy Professionals (IAPP)  shows active bills from Michigan, New Jersey, Ohio, and Pennsylvania.

These bills grant consumers the right of access, certification, deletion, restriction, portability, and the ability to opt out of sales and automated decision-making. Businesses are obliged to comply with opt-in defaults, transparency requirements, risk assessments, limitations on processing, and discrimination prohibitions.

Europe

Europe is also updating privacy regulations. Major legislative efforts like the Trans-Atlantic Data Privacy Framework (TADPF), Privacy Shield 2.0 updates, and amendments to the French Blocking Institute are focusing on cross-border data requests and transfers. Tighter controls around disclosure will require companies to provide more information to authorities tasked with verifying data access requests.

China

China enacted the Security Assessment Measures for Cross-Border Data Transfers as recently as September 2022. Previously, China has implemented the Cybersecurity Law (2017), Data Security Law (2021), and Personal Information Protection Law (2021). Together with existing privacy laws, the new regulation requires companies to obtain consent and certification for cross-border transfers of data, including personal information.

Proactive Steps Toward Compliance

As privacy laws gain momentum, securing data against cyber threats has never been more important. Below are some proactive steps companies can take to maintain compliance:

Map your data. Understand where your data is located across the organization. Make an inventory of internal and external systems, connected channels, and touchpoints. Identify storage locations/measures for sensitive and personal information. As a best practice, consolidate data silos into a centralized platform for better management. Choose a platform that maps out origin sources as well as where data resides in the consolidated model. It’s also important to use a platform capable of ingesting all types of data that feeds into one place.

Review data protocols and policies. Analyze your organization’s data processing activities to identify protocols that need to be updated to comply with regulations. Verify if data policies like consent options are being implemented by internal teams and whether they are communicated clearly to data subjects. Customer data platforms (CDP) equipped with full consent management modules make it easy for teams to track geo-specific consent rules and implement them in different regions.

Exceed minimum compliance. As privacy laws undergo continuous modifications and updates, they show no signs of relaxing restrictions. Prepare for major regulatory updates by complying with, and—if possible—exceeding minimum standards. Apply best practices to ensure privacy and security. Finally, monitor newly enacted laws as well as bills under discussion in various legislatures.

Data Privacy Solutions

Data privacy solutions keep sensitive information private and protected. They serve the double purpose of preventing unauthorized access and protecting businesses from receiving regulatory fines.Three data privacy solutions to consider when securing sensitive data include:

• Data and file monitoring tools. These devices monitor activity around data assets and important files. They alert administrators to suspicious behavior patterns or logins from questionable accounts. Early detection prevents further risk or damage to data assets.
• Risk analysis tools. These instruments analyze and evaluate privacy risks in a company’s data management process. Such risks include inadequate security safeguards, malware and viruses, access by external parties, outdated systems, lack of encryption, and others. Risk analysis tools identify vulnerabilities along the data lifecycle, from collection to storage and usage. For multinational companies, analysis may also include risk factors during international data transfers.
• Automated compliance monitoring. These solutions automate compliance monitoring by continuously tracking where data (like personally identifiable information or PII) reside in a company’s systems. Once sensitive information moves beyond established protocols, automated compliance monitoring tools alert administrators to take action. Advanced tools can also confirm if requirements and data policies are up to date to maintain compliance.

Data Governance

Contemporary data governance has become incredibly complex due to the sheer amount of data generated by customers via digital channels and touchpoints. To keep up with ever-widening data streams and tightening privacy regulations, companies need a solution to simplify the governance of data security and privacy. A customer data platform (CDP) solves these challenges by centralizing data and control in a single location.

CDPs eliminate data silos. A CDP stores all customer data—from websites to offline records to CRMs and more—in one place. Centralized data storage also eliminates piecemeal data governance solutions that may overlook loopholes in data privacy and security.

A CDP centralizes control. Data administrators can manage access and permissions using a single platform, increasing transparency and accountability around data use.

A CDP unifies customer profiles.  Teams can use a CDP’s profile unification capability to track customers’ actions as well as their consent and preferences. Unified profiles also enable teams to fulfill data subject access requests (DSARs) on demand.

Ensuring Data Security and Privacy With Treasure Data’s CDP

Treasure Data Customer Data Cloud helps you earn and keep your customers’ trust through data security and privacy compliance. Our enterprise-grade CDP gives you a single, powerful platform to collect data with consent anywhere, enforce and maintain privacy compliance, and adapt to changing regulations quickly and easily.

Collect Every Data Point With Geo-Specific Consent

Treasure Data collects, secures, and activates every piece of customer information with consent across all channels, teams, and brands—wherever they may be.

Govern Data in One Place

Treasure Data unifies all of your data with consent in a centralized platform so you can govern access, enable audit logs, and pick out suspicious activity easily.

Manage Security and Privacy

Use Treasure Data Customer Data Cloud to restrict access to Personally Identifiable Information (PII), and handle automated workflows for DSARs and privacy requests. Enforce consent management, log data use, and manage emergencies from Treasure Data’s secure platform.

Treasure Data complies with the latest regulations and continually builds on a strong data security foundation.

Treasure Data Customer Data Cloud is an integrated suite of cloud-based customer data platform solutions. Treasure Data provides insight by collecting and centralizing customer data, unifying profiles, and analyzing journeys to surface hidden trends in customer behavior.

See Treasure Data’s enterprise customer data platform in action below:

To learn more about how you can use Treasure Data’s CDP to ensure data security and privacy, consult an expert today. Want to learn more? Request a demo, call 1.866.899.5386, or contact us for more information.

The post Data Security and Privacy: A Complete Guide first appeared on Treasure Data.

Data Privacy Regulations: Building Trust Beyond Compliance

Learn how a customer data platform (CDP) can streamline the complicated process of privacy compliance.

Effective marketers know data privacy regulations are less about compliance and more about customer trust. And part of earning and keeping trust involves targeting and personalization that makes customers feel their individual preferences are known and respected.

This paper discusses how to gain consumer trust while also capturing the insights and customer data you need for personalized customer journeys, targeting and segmentation, new customer acquisition, and profitable customer experience (CX).

You’ll learn:

• The key differences between GDPR and CCPA
• Why compliance starts with unifying all your customer data from all your data sources
• How a CDP can help you improve privacy compliance and customer trust

Privacy compliance can get complicated really fast, but you can significantly simplify the process with a CDP. Read this paper to find out how.

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Trusted by Enterprises Around the World

The post Building Trust Beyond Compliance first appeared on Treasure Data.

Take a Global Approach to Data Privacy and Governance

How can companies ensure their entire organization is up for the challenge of global compliance?

Establishing an efficient data governance strategy across complex global enterprises is an organizational challenge – especially when you consider evolving data privacy regulations, changing consumer preferences, and an abundance of data across systems, brands and teams that are subject to compliance.

With the right tech and processes in place, remaining compliant at scale is achievable.

Learn how to get started. In this article, we explore:

• The unique challenges global brands face when implementing data privacy and governance across different regions and brands.
• How leaders should view the tech stack when integrating data privacy and compliance efforts.
• What leaders need to do to align on data privacy and governance practices to future-proof their business.

Fill out the form to receive your copy now!

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The post A Global Approach to Data Governance first appeared on Treasure Data.

Data Privacy, Security, and the Importance of Trust

Build a framework for positive customer experiences in the age of data privacy

What’s a good relationship without trust?

In an increasingly digital world, data privacy, security, and trust have become key for businesses seeking to create a positive customer experience. In fact, 94% of consumers say they’re more likely to be loyal to a brand that is transparent about how their data is used.

So, how are leading brands respecting individual privacy preferences, and delivering the hyper-personalized customer experiences that consumers crave?

In this report, we’ll show you:

• How customer expectations on data privacy and security are changing
• The impact of data privacy and data security on the customer experience
• How to develop an enterprise-wide data privacy and governance framework using a CDP

Get your copy now!

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The post Data Privacy, Security, Trust, and CDP first appeared on Treasure Data.

Data Privacy is Transforming Marketing – Are You Ready?

A special collection from VentureBeat and Treasure Data</h5<

Treasure Data partnered with VentureBeat to explore what data privacy and governance trends are shaping the future of marketing, and how organizations can use technology to transform their operations, keep their data safe, and deliver experiences that meet consumer expectations.

This collection includes top tips and best practices, covering:

• Marketing in the era of data growth and privacy
• What the end of third-party cookies means for personalization
• Data privacy is expensive – here’s how to manage costs
• Putting data privacy first – a global approach to data governance

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The post VentureBeat: How Data Privacy is Transforming Marketing first appeared on Treasure Data.

Building Consumer Trust Starts with Data Privacy

Why would customers willingly trust companies that have not prioritized and protected their safety?

Getting a handle on data privacy is a prevailing issue for companies today. Data breaches and lack of compliance with global regulations pose a risk for brands that are looking to build lasting relationships with consumers who are more aware of how, and when, they share their data.

By disrupting the current trend of distrust, companies can build more meaningful relationships with customers. In this whitepaper, Treasure Data and CCW explore the current trends impacting data privacy in customer service, and how companies can use technology to create data privacy practices that meet consumer needs.

You’ll learn:

• The biggest trends influencing consumer perspectives on data privacy today
• How customer data can improve trust in the contact center
• How data-driven personalization can build trust between customers and contact center agents
• How a customer data platform can help you put data privacy first

Download your copy of the whitepaper now!

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The post Securing Customer Trust in the Digital Age first appeared on Treasure Data.