Privacera Highlights at AWS re:Invent 2021: re:Inventing Cloud Data Access Governance & Security for Analytics

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We had an incredible time at AWS re:Invent where we got to meet our amazing partners and customers and demonstrate how our unified platform can help address the enterprise access control and security challenges with the attendees. We’d like to thank all the attendees who stopped by our booth, our partners for their support, and our customers for their continued support and trust in us. Finally, kudos to one of our most important allies, Amazon Web Services, for running a fantastic in-person event. It has been a long time coming since the outbreak of the pandemic, but we couldn’t have imagined a more successful event. 

For those of you whom we didn’t get a chance to talk to, we are sorry that we missed you. Here is a short recap of the Privacera highlights at AWS re:Invent and please follow us on Twitter or LinkedIn for future updates on the company. 

Highlight #1: Unified Data Governance, Access Control, and Security is Key for Enabling Cloud Analytics

To put data to work and extract value from it through analytics, machine learning, or predictive modeling, having comprehensive data governance, access control, and security is essential to ensure that data is protected, compliant, and fit for consumption. Rahul Pathak, VP of AWS Analytics, said it best in his leadership session that “customers sometimes think that access control and governance is in conflict with velocity, it’s NOT true. If you actually have good guardrails and protection on your data, you’re able to set it free and allow people to experiment and iterate because you’re confident that your data is well protected and only the right people have access to it.”

Courtesy: Reinvent your business for the future with AWS Analytics, leadership session at AWS re:Invent

Data governance is a critical component that underpins the entire data analytics continuum in which data is consumed in purpose-built data stores, data lakes, and analytics services that are designed for machine learning and data science modeling. This resonates with the work that we have been doing at Privacera to help customers maximize the visibility and usability of data by enabling unified data governance, fine-grained access control, and enhanced data security through a single console across multiple cloud services. In addition, we provide automated sensitive data discovery, tagging, and classification so that you know where all your sensitive information resides to eliminate data and regulatory blindspots. The comprehensive set of data security and governance capabilities that Privacera delivers sets your data scientists and analysts free to innovate with trusted and faster access to data without compromising data privacy and compliance.  

Highlight #2: Using Apache Ranger to Secure Amazon EMR Data Lake

For those who are not familiar with Apache Ranger, it is one of the leading open-source projects used by Fortune 500 companies for data governance. With more than 15 major and minor software releases under its belt – as well as contributions from Microsoft, Accenture, eBay, and ING – Apache Ranger has become a leading security and authorization component adopted by the market leaders, such as Amazon EMR, Google Cloud Dataproc, and more, to securely manage their data ecosystems. Due to its robustness and proven scalability, Privacera has chosen Apache Ranger as its underlying engine for access control and it has advanced its capability with many out-of-the-box features.

Courtesy: What’s new with Amazon EMR, product session at AWS re:Invent
Courtesy: What’s new with Amazon EMR, product session at AWS re:Invent

In the “what’s new with Amazon EMR” session, the speaker emphasized the use of Apache Ranger and AWS Lake Formation to perform fine-grained access controls (FGAC) for securing EMR clusters. A question that immediately came to mind is how does Privacera integrate with Ranger on EMR and what benefits does Privacera provide? Look no further, here’s the answer for you. Privacera-protected EMR environment can leverage AWS’s tight native integration with Apache Ranger or use Privacera’s extended plugin support for Spark, Hive, and PrestoSQL—even when accessed through third-party tools. In addition, PrivaceraCloud provides an exclusive enterprise-ready, fully-managed Apache Ranger-based SaaS solution for both native EMR/Ranger integration and Privacera’s plugins. As a result, there are no custom catalogs to maintain, no manual tagging, and no need to create separate policies for resources defined in Hive Catalog, Glue, or just raw in S3. 

To learn more, watch the following demo on connecting PrivaceraCloud with AWS EMR Hive:

Highlight #3: Enabling Distributed Data Governance by Building a “Hot” Data Mesh with Privacera and Starburst

We had the privilege to co-sponsor the “Hot Data Mesh & Margaritas” happy hour with our amazing partner Starburst. With the two together, we are able to shift to the new paradigm of data mesh by enabling cross-cloud analytics on data distributed globally, while leveraging data access governance powered by Privacera to ensure regulatory compliance is not compromised at the expense of enabling rapid access to analytics to drive business initiatives.  

For example, one of Starburst’s customers has data stored in: AWS East, AWS Frankfurt, AWS Paris, Azure Central US, and two on-prem data centers. Its analysts and data scientists need to derive insights and train models based on data in all of these regions. Until now, they were replicating data so analysts could get the data they needed in one place.

Starburst Stargate enables that customer to link catalogs and data sources supported by one Starburst cluster to other catalogs and data sources in remote Starburst clusters. Privacera’s automated data discovery inventories everything connected to the Starburst cluster and automatically applies a basic set of tags for personal identifiable information(PII) out-of-the box. Privacera’s discovery engine can also find sensitive data in locations data stewards can’t physically check (e.g., thousands of files, new tables created by analysts, etc.), even for enterprise-specific classifications (e.g., “everything in this system is constrained by GDPR” or “any identifier that matches this list is a customer account number.”)  Privacera’s tag-based policies automatically protect sensitive elements in data against unauthorized access, extendable beyond Starburst to protect data even when it is accessed outside the distributed query environment, such as BI tools on data warehouses, or direct access to cloud storage like AWS, S3, Azure ADLS, or Google Cloud Storage.

We Look Forward to Meeting You in Future Events

With such a great event behind us, we are already looking forward to the next. Want to know where our team will be next? Check out our events page for the latest updates, and be sure to visit Why Privacera? to learn how Privacera can help you with your data governance, access control, and security needs.

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