I recently met with a promising SaaS startup that had just hit their growth stride: 50 employees, expanding customer base, and finally some budget for cybersecurity. When I asked their CEO about their data management practices, she gave me a look I’ve seen so many times: part confusion, part panic. “We… store things in Google Drive?”
She’s not alone.
Most growing companies focus on product development and customer acquisition. Data management falls into that “we know we should do something about it” category. And that’s exactly the stage when you need to get your data house in order.
The reality: without knowing what data you hold and where it lives, you can’t protect it effectively, meet regulatory obligations, or respond when customers ask you to delete their information.
Why Data Management Matters Now Here’s what your data storage likely looks like: Your company stores customer data across multiple systems including a production database, CRM, analytics platform, maybe a data warehouse… and data is definitely scattered across employee laptops and cloud storage!
What happens when a customer decides to leave and requests that you delete their data?
It sounds simple, except it’s not. Where exactly is their data? Who has access to copies? How do you verify it’s actually gone? And what about backups? Do you keep those forever?
Without established data management practices, you’re stuck playing a time-consuming game of hide-and-seek with potentially sensitive information. Worse, you might be retaining data far longer than necessary, expanding your attack surface and increasing the potential damage from a breach.
The cost of getting data management wrong compounds over time. The longer you wait to implement proper practices, the more data you have to wrangle retrospectively, and the more complex your systems become.
Growing Companies Should Start Small You’ve probably heard of the major cybersecurity frameworks: CIS Controls, NIST Cybersecurity Framework, ISO 27001. These are comprehensive, battle-tested approaches to security. They also present a huge workload for small and mid-sized organizations trying to get started on their first real security program.
Consider what you’re facing with traditional frameworks:
CIS Controls includes 153 controls across 18 categories
NIST CSF encompasses five functions with numerous categories and subcategories
ISO 27001 requires 93 controls and extensive documentation
For smaller companies, it’s better to start small. These are the first data management controls we recommend implementing:
Data Classification and Labeling
Encryption (at rest and in transit)
Backup and Restore
Privacy Management
Vendor Management
Data Separation and Disposal
The Data Management Controls That Matter Data Classification and Labeling Before you can protect your data, you need to understand what you have and how sensitive it is. Data classification establishes categories based on confidentiality, integrity, and availability requirements, so that you can designate appropriate protection measures for each category.
Public: Information meant for public disclosure (marketing materials, published documentation, public website content)Internal: Information for internal use that doesn’t need special protection (operational procedures, non-sensitive business data)Confidential: Sensitive information requiring protection from unauthorized disclosure (customer data, employee information, financial records and intellectual property)Restricted: Highly sensitive information requiring maximum protection (payment card data, protected health information, authentication credentials, and encryption keys)
To have fully implemented this control, you should have:
A document detailing your classification scheme with clear definitions and examples.
Established training for employees to recognize and properly classify data
Established labeling standards showing how to apply classification labels such as adding “Confidential” watermarks to documents, setting metadata tags in cloud storage, and tagging database fields with sensitivity levels
Defined handling requirements for each level, including encryption needs, access controls, and retention periods
Encryption: Protecting Data at Rest and in Transit Encryption is the process of converting readable data into an encoded format that can only be decoded with the correct decryption key. It ensures that unauthorized parties cannot read data even if they gain access to storage systems or intercept network communications. Modern platforms provide encryption capabilities that organizations can enable with minimal configuration.
Implementation focuses on two primary areas:
Data at rest : Start with endpoint devices; activate BitLocker or FileVault for employee laptops to protect data if devices are lost or stolen. Then extend encryption to databases, file storage systems, and cloud infrastructure. Enable encryption for cloud storage buckets and ensure database instances use encrypted storage volumes.
Data in transit: Any time data moves between systems from a customer’s browser to servers, between microservices, or to a third-party API, it should travel over encrypted connections. Transport encryption means implementing Hypertext Transfer Protocol Secure (HTTPS) for all web traffic, Transport Layer Security (TLS) 1.3 or higher for database and application connections, and encrypted Virtual Private Network (VPN) connections for remote access.
A quick implementation guide:
List all places where you store confidential or restricted data including production databases, file servers, cloud storage (like S3 or Azure Blob), employee laptops, and mobile devices
Turn on BitLocker (Windows) or FileVault (Mac) on all employee laptops and ensure mobile device encryption is enabled
Activate encryption settings in your cloud storage services
Work with your technical team to enable encryption at rest for your database instances
Create a spreadsheet or document tracking which systems have encryption enabled, what type of encryption they use, and when it was implemented
Determine where encryption keys are stored (often in a key management service like AWS KMS or Azure Key Vault) and who has access to them. Ensure keys are not stored alongside the encrypted data.
Verify that encryption implementation is actually working through testing
Start with your most sensitive data first such as customer payment information, health records, or personal identification data then expand encryption to other systems.
Backups: Ensuring Business Continuity Backups protect against data loss from system failures, human error, and security incidents like ransomware. However, backups are only valuable if they actually work when you need them; untested backups create a false sense of security.
For modern cloud-native companies, a practical backup approach includes maintaining your production data, automated daily snapshots stored in a lower-cost archival storage (where retrieval takes longer but storage costs significantly less), and replicated copies in a separate cloud region or with a different provider. This creates multiple recovery points while balancing cost and protection.
Testing backup restoration is critical. Schedule quarterly restoration tests by selecting random systems or datasets, restoring them to test environments, and verifying data completeness and usability. Document restoration time and any issues encountered.
Practicing your backup processes will get them running faster, saving valuable time in the event of a real incident.
Retention requirements vary based on regulatory obligations, contractual commitments, and business needs. A typical SaaS organization might maintain daily backups for 30 days and monthly backups for one year, but specific retention periods depend on industry regulations and operational requirements.
Organizations collecting email addresses, tracking website activity, or storing any personal information must implement privacy controls. Regulatory frameworks like GDPR, California Consumer Privacy Act (CCPA), and HIPAA establish baseline requirements for personal data handling.
Begin with a comprehensive data inventory documenting what personal information you collect, why you collect it, who accesses it, and how long you retain it. Create a spreadsheet with the following columns to capture:
Data type (e.g., customer email, billing address, phone number)
Collection point (where you gather it. Eg., website forms, checkout process, support tickets)
Business purpose (why you need it such as for billing, communication, service delivery)
Systems where it’s stored (Eg., CRM, database, email platform)
Who has access (which teams or roles)
Retention period (how long you keep it)
This inventory forms the foundation of any privacy program. Once you understand what data you have, establish clear procedures for how you handle it at every stage. Implement the following data handling procedures across the lifecycle:
Collection: Gather only data necessary for specific business purposes. Each additional data point increases risk and compliance burden.Use: Restrict data access to employees requiring it for their roles. Sales teams should not access detailed support tickets; developers should not work with production customer data in testing environments.Disclosure: Maintain transparency about data collection and usage. Privacy policies should clearly explain practices in accessible language rather than dense legal terminology.Retention: Define retention periods for different data types based on legal, regulatory, and business requirements. Customer financial records might require seven-year retention while marketing analytics might only need six months.
Establish systematic processes for data subject requests. When individuals request information about their data or request deletion, you need a systematic way to respond. Document the workflow, assign responsibility, and establish reasonable timelines.
For example, a basic data deletion request includes these steps:
After receiving a request through a designated channel (eg., email or form), verify customer identity
Review data inventory to identify all systems containing their data and check for legal or contractual retention requirements that apply
Remove data from production systems, development environments, and mark for removal from backups according to your retention schedule
Document what was deleted, what was retained and why, then confirm completion to the customer within your established timeframe (typically 30 days)
Retain records of the deletion request for compliance purposes
Vendor Management: Managing Third-Party Access to Your Data Your vendors have access to your data, whether it’s your CRM provider storing customer information, your payment processor handling financial transactions, or your cloud provider hosting your production environment. Each vendor relationship creates potential data security and privacy risks that you need to manage.
Effective vendor management requires:
Data inventory: Document which vendors have access to specific data types and which ones have access to your systems. Identify vendors processing confidential or restricted information that need closer oversight.Contractual protections: Ensure vendor agreements include data protection clauses covering security requirements, breach notification obligations, data location restrictions, and deletion procedures when the contract ends.Security assessments: Evaluate vendor security practices before you sign up and periodically during the relationship. Review SOC 2 reports, security questionnaires, and third-party certifications.Access controls: Limit vendor access to the minimum data necessary. Use separate accounts with restricted permissions rather than handing over broad administrative access.Monitoring: Track vendor security incidents and policy changes. Subscribe to vendor security advisories and review them for potential impact on your organization.Offboarding: When you terminate a vendor relationship, verify complete data deletion or return according to your contract. Revoke access credentials and remove integration connections.
Data Management: Customer Data Separation and Disposal This control ties everything together, addressing the complete data lifecycle from collection through deletion. When customer relationships end through churn, deletion requests under privacy laws, or contract expiration, organizations need systematic procedures for managing their data.
Identification: Locate all instances of specific customer data across systems. This requires maintaining clear data lineage and consistent identifiers. If Customer ABC’s data exists in production databases, data warehouses, CRM systems, email platforms, and backup archives, you must locate it in all locations.Retention: Distinguish between data you must keep for legal, tax, or regulatory reasons versus data you can or should delete. Financial records might require seven-year retention while marketing preferences only need to exist during active relationships.Archiving: For data requiring retention but no longer needed operationally, implement secure archiving. Archived data should be encrypted, access-controlled, and inventoried, but removed from production systems to reduce active risk exposure.Deletion: Execute thorough deletion when appropriate. Soft deletes flagging records as “inactive” are insufficient because data remains accessible and represents continued liability. Implement secure deletion procedures removing data from production systems, development environments, backups (after age-out periods), and all other locations.
Document data separation procedures and review them annually as systems evolve. Procedure documentation should specify responsibilities, timelines, and verification steps.
Bringing It All Together: That startup CEO I mentioned? Three months in, her company had done a complete data discovery, established data retention schedules,tested their backups successfully, e and created efficient processes for handling data deletion requests. When I checked in with her, she mentioned something interesting: the data management work had actually improved their product development process because they finally understood their data flows.
Once you start strengthening the basics, the rest of your data management program becomes much easier to shape and maintain. The easiest way to get started is to break the work into a few manageable phases.
First, understand your data:
Map what you have by creating a simple data inventory (what you collect, where it lives, who has access)
Classify your important data using basic labels (Public, Internal, Confidential, Restricted)
Turn on built-in protections you already own if they aren’t implemented, such as encryption for laptops, cloud storage, and databases
Tighten access controls so only the right people can see or use sensitive data
Next, make your core processes consistent and reliable:
Verify your backups are running, stored separately, and can actually be restored
Review your vendors, especially those handling sensitive data, and make sure they meet baseline security expectations
Document how you handle personal information including what you collect, who accesses it, and how long you keep it
Keep documentation simple and train your team so practices are followed consistently
Finally, build long-term maturity:
Create a repeatable customer offboarding and data separation process that covers retention, archiving, and deletion across all systems
Establish a consistent data deletion request workflow for when those requests eventually come in
Review and update your data inventory, retention schedules, and vendor list annually as your business evolves
Focus on building sustainable practices rather than achieving perfection. Start with controls you can implement consistently. Document what you do. Train your team. Review and improve as your systems grow more complex.
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