About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

ALTR Integrates Cloud Native Data Security as a Service with Snowflake Data Platform

Subscribe to our newsletter

ALTR, an Austin, Texas provider of data security, has released ALTR cloud integration for the Snowflake cloud data platform. The cloud native ALTR platform extends Snowflake’s built-in security with real-time data consumption governance capabilities for observing, detecting and responding to data threats and anomalies.

The addition of ALTR to the Snowflake data cloud follows FactSet’s recent move onto the platform with its mapping solution, FactSet Concordance Service, and S&P Global Market Intelligence’s September 2020 collaboration with Snowflake to deliver financial, textual, ESG and alternative data through the Snowflake platform.

ALTR offers cloud-to-cloud integration between its data security as a service (DSaaS) platform and Snowflake’s data cloud giving Snowflake users no-code cloud integration to ALTR real-time intelligence on data consumption and the ability to mitigate risks of storing and sharing sensitive information on Snowflake. Because integration is direct and doesn’t use a proxy, users can connect using Snowflake itself or by using tools such as Tableau or Looker visualisation tools.

“Businesses are moving sensitive data workloads to integrated data platforms like Snowflake, and as they do, traditional security perimeters vanish. This has made the need for governance and protection at the data layer paramount,” says David Sikora, CEO at ALTR. “Working in parallel with Snowflake, ALTR brings zero-trust to the SQL layer and scales with the platform making it possible to process safe and secure queries at cloud scale with ease.”

While traditional data security tools are deployed into network infrastructure, the ALTR service is integrated into the critical path of data at the individual data request level of application workloads. This enables Snowflake users to observe and govern data consumption, automatically detect and respond to abnormal usage, and shield sensitive data against credential threats and attacks on data-driven applications. They can also continually optimise their experience by analysing how they use their own data.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: The Data Office at a Crossroads — AI Governance, Organisational Design, and the Evolving Mandate of the CDO

Date: 28 July 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Who owns AI governance in a capital markets firm – and is the Data Office structured to bear that weight? These questions sit at the heart of A-Team Research’s latest findings, presented here for the first time: the combined...

BLOG

The Business Conduct Risk and Data Challenge Behind AI Adoption

Poor data preparation for artificial intelligence deployments is exposing financial institutions to greater business conduct risks that could cost them as much as US$43 million per year, according to new research. An updated report by business conduct data provider RepRisk found that such AI-related incidents are on the rise as applications are rolled out at...

EVENT

ExchangeTech Summit London

A-Team Group, organisers of the TradingTech Summits, are pleased to announce the inaugural ExchangeTech Summit London on May 14th 2026. This dedicated forum brings together operators of exchanges, alternative execution venues and digital asset platforms with the ecosystem of vendors driving the future of matching engines, surveillance and market access.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...