It’s Official: Telmai is now SOC 2 Type 2 Compliant
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Today we have a fantastic news to share ! Telmai is now SOC 2 Type 2 Compliant
This is a milestone achievement that helps us to continue to build trust with our community and customers. Telmai has always been committed to building trust with all users and we are constantly working toward aligning data security and privacy practices with the latest certifications and accreditations.
Today, we’re happy to announce Telmai is now SOC 2 Type II compliant. This is another attestment to reassure our users that their valuable data is always safe and protected with highest security standards.
What is SOC 2 compliance?
Service Organization Control 2 (SOC2) is a component of the American Institute of CPAs (AICPA)’s Service Organization Control reporting platform. SOC 2 is a technical auditing process and certification that measures security and availability and serves as an assurance to customers that their data is being managed in a controlled and audited environment.When a business is SOC 2 compliant, it signifies they implement proper security systems to ensure security, availability, processing integrity, confidentiality, and privacy of customer data.
SOC 2 compliance is essential for technology-based service organizations that store customer data in the cloud. This makes it applicable to most SaaS businesses, and any business that relies on the cloud to store its customers’ information. As of August 2022 we are now Type II compliant.
What does SOC 2 certification entail?
The SOC 2 certification is awarded to businesses by independent auditors upon assessing the extent to which they comply with one or more of these five trust principles:

Security
The security principle refers to the protection of system resources against unauthorized access. Access controls help prevent potential system abuse, theft or unauthorized removal of data, misuse of the software, and improper alteration or disclosure of information.
Availability
The principle checks the accessibility of the system, products or services as stipulated by a contract or service level agreement (SLA). It involves security-related criteria that may affect availability. Monitoring network performance and availability, site failover, and security incident handling are critical in this context.
Processing integrity
This principle addresses if a system achieves its purpose, i.e., delivers the right data at the right price at the right time. The data processing must be complete, valid, accurate, timely, and authorized.
However, processing integrity doesn’t only imply data integrity; it also includes the monitoring of data processing, along with quality assurance procedures.
Confidentiality
Information that is designated as confidential should be protected according to the User Entity’s needs. Data is considered confidential if its access and disclosure are restricted to a specified set of persons or organizations.
The principle includes encryption, which is an important control for protecting confidentiality during transmission. Network and application firewalls, along with rigorous access controls, can be used to safeguard information being processed or stored on computer systems.
Privacy
The privacy principle addresses the system’s collection, use, retention, disclosure, and disposal of personal information in conformity with an organization’s privacy notice, as well as with criteria determined by the AICPA’s Generally Accepted Privacy Principles (GAPP).
It includes protecting the unauthorized access of personally identifiable information (PII) – personal data related to health, race, sexuality, and religion is also considered sensitive and generally requires an extra level of protection.
Why is SOC 2 compliance important?
Meeting SOC 2 compliance means establishing processes and practices that guarantee oversight across a company, guaranteeing customers that their data is protected from any unusual, unauthorized, or suspicious activity.
To ensure businesses meet SOC 2 requirements, you need to receive alerts whenever unauthorized access to customer data occurs. SOC 2 compliant companies are required to set up alerts for:
- Exposure or modification of data, controls, configurations
- File transfer activities
- Privileged filesystem, account, or login access
Having a SOC 2 badge on the Telmai website represents the dedication to keeping customer information private and secure. Telmai understands the need for customers to feel safe about their data, and it’s the reason why we are excited to feature this badge:
Our Journey to SOC II
As a company, we’ve always tried to live up to the highest standards. We care about security and treat it with high priority. The SOC audit was, first of all, a benchmark we wanted to use to validate our efforts in the security area. We’re proud the approach we took naturally led us to this well-respected certification.
We started the journey by partnering with Vanta (another YC company). Their platform was invaluable in preparing us for the audit, and helped us organize information about assets, vulnerabilities and forced us to follow best practices. They also introduced us to a number of credible audit firms and we picked the one which worked best given the size, stage of our company as well as type of our customers. Barr Advisory checked all the marks and we decided to go with them.
In the early days despite being a startup we decided not to take any shortcuts in architecture, tooling, processes and enterprise software best practices. On this path we had multiple checkpoints with CISOs to ensure we leave no gaps even at the planning phase. All this helped us tremendously in achieving the certifications goals smoothly.
If you have any questions around the process or need access to our report email us on security@telm.ai to request our SOCII report.
Data profiling helps organizations understand their data, identify issues and discrepancies, and improve data quality. It is an essential part of any data-related project and without it data quality could impact critical business decisions, customer trust, sales and financial opportunities.
To get started, there are four main steps in building a complete and ongoing data profiling process:
We'll explore each of these steps in detail and discuss how they contribute to the overall goal of ensuring accurate and reliable data. Before we get started, let's remind ourself of what is data profiling.
1. Data Collection
Start with data collection. Gather data from various sources and extract it into a single location for analysis. If you have multiple sources, choose a centralized data profiling tool (see our recommendation in the conclusion) that can easily connect and analyze all your data without having you do any prep work.
2. Discovery & Analysis
Now that you have collected your data for analysis, it's time to investigate it. Depending on your use case, you may need structure discovery, content discovery, relationship discovery, or all three. If data content or structure discovery is important for your use case, make sure that you collect and profile your data in its entirety and do not use samples as it will skew your results.
Use visualizations to make your discovery and analysis more understandable. It is much easier to see outliers and anomalies in your data using graphs than in a table format.
3. Documenting the Findings
Create a report or documentation outlining the results of the data profiling process, including any issues or discrepancies found.
Use this step to establish data quality rules that you may not have been aware of. For example, a United States ZIP code of 94061 could have accidentally been typed in as 94 061 with a space in the middle. Documenting this issue could help you establish new rules for the next time you profile the data.
4. Data Quality Monitoring
Now that you know what you have, the next step is to make sure you correct these issues. This may be something that you can correct or something that you need to flag for upstream data owners to fix.
After your data profiling is done and the system goes live, your data quality assurance work is not done – in fact, it's just getting started.
Data constantly changes. If unchecked, data quality defects will continue to occur, both as a result of system and user behavior changes.
Build a platform that can measure and monitor data quality on an ongoing basis.
Take Advantage of Data Observability Tools
Automated tools can help you save time and resources and ensure accuracy in the process.
Unfortunately, traditional data profiling tools offered by legacy ETL and database vendors are complex and require data engineering and technical skills. They also only handle data that is structured and ready for analysis. Semi-structured data sets, nested data formats, blob storage types, or streaming data do not have a place in those solutions.
Today organizations that deal with complex data types or large amounts of data are looking for a newer, more scalable solution.
That’s where a data observability tool like Telmai comes in. Telmai is built to handle the complexity that data profiling projects are faced with today. Some advantages include centralized profiling for all data types, a low-code no-code interface, ML insights, easy integration, and scale and performance.
Data Observability
Data Quality
Leverages ML and statistical analysis to learn from the data and identify potential issues, and can also validate data against predefined rules
Uses predefined metrics from a known set of policies to understand the health of the data
Detects, investigates the root cause of issues, and helps remediate
Detects and helps remediate.
Examples: continuous monitoring, alerting on anomalies or drifts, and operationalizing the findings into data flows
Examples: data validation, data cleansing, data standardization
Low-code / no-code to accelerate time to value and lower cost
Ongoing maintenance, tweaking, and testing data quality rules adds to its costs
Enables both business and technical teams to participate in data quality and monitoring initiatives
Designed mainly for technical teams who can implement ETL workflows or open source data validation software
Start your data observibility today
Connect your data and start generating a baseline in less than 10 minutes.
No sales call needed
Start your data observability today
Connect your data and start generating a baseline in less than 10 minutes.