BigID Introduces Business-First Hybrid Scanning for Cloud Native Workloads


Within the period the place organizations need to speed up their migration to cloud infrastructure, a brand new expertise development for cloud-native workloads has emerged – hybrid scanning.

BigID, a knowledge discovery and intelligence platform, has launched hybrid scanning for cloud-native workloads. This industry-first innovation combines side-scanning and direct-scanning strategies for information discovery, administration, and safety. 

Based on BigID, combining these two scanning strategies permits for speedy onboarding and scanning of enormous volumes of knowledge. Aspect scanning is used for preliminary discovery, whereas direct scanning is used to course of and collect deeper insights. 

Conventional scanning strategies have struggled to maintain tempo with the complexities of contemporary cloud infrastructure. Nonetheless, now with hybrid scanning, organizations can profit from unparalleled pace, effectivity, and adaptability of their potential to handle cloud information.  

“The exponential progress of cloud information presents important challenges for organizations looking for complete information safety and privateness,” stated Dimitri Sirota, CEO of BigID. “BigID’s hybrid scanning expertise is a game-changer. By combining the pace and scalability of side-scanning, with the depth and accuracy of direct scanning, organizations can obtain unmatched visibility and management over their cloud information, making certain compliance and safeguarding delicate info.”

Cloud-native workloads are optimized to run on cloud infrastructure, leveraging its native capabilities for improved scalability, agility, resilience, and growth expertise. Organizations are additionally turning to cloud-native structure for enhanced competitiveness and an accelerated time-to-market. 

Whereas there are a number of advantages of cloud-native workloads, there are additionally some key challenges. Cloud-native structure will be considerably extra complicated, making it more difficult to fulfill information safety, compliance, and connectivity necessities. 

BigID’s hybrid scanning strategy tackles a few of these points by robotically figuring out and onboarding cloud information sources. This supplies the required connection info for each scanning strategies so organizations can tailor their scanning technique primarily based on particular wants. 

The hybrid scanning technique additionally facilitates higher safety as direct scanning can handle quick information dangers, whereas aspect scanning can present deeper insights to uncover hidden vulnerabilities. This may facilitate higher information masking, deletion, and encryption. 


Organizations may use hybrid scanning to reinforce compliance administration by gaining a complete understanding of their cloud information and making knowledgeable selections to assist compliance. 

In March this yr, BigID secured $60M in growth funding to advance its AI information safety improvements together with new information hygiene capabilities for GenAI information pipeline and new controls for safeguarding delicate information. The information discovery and intelligence platform additionally patented a new technology this year that enhances the method of knowledge cleaning, curation, and cataloging for AI. 

The addition of hybrid scanning capabilities to BigID’s united platform additional enhances its enchantment to organizations, who can be eager on utilizing the platform to harness the total potential of the cloud with confidence. Not solely does the hybrid scanning supply a safer and compliant cloud atmosphere, nevertheless it represents a big step ahead in empowering organizations to unlock extra worth from their information. 

Associated Gadgets

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack

Databricks Enhances Enterprise AI with RAG Applications and Improved Model Serving

Normalyze Innovates to Secure LLMs and Data Lakes Against Emerging Threats

Leave a Reply

Your email address will not be published. Required fields are marked *