Nasuni and AWS are continuing to expand our partnership around helping customers build advanced solutions for unstructured data management. In this post I’ll focus on how we’re moving forward assisting customers with analyzing and searching large amounts of file data. This is just the first of a series of posts about how we are tightly integrating our platform with AWS and helping customers increase their data value leveraging some incredible AWS tools.
Traditionally, unstructured data within large enterprises had (or has) been siloed at numerous locations, from large data centers to small remote offices. The cloud, and a cloud file storage solution, allows companies to consolidate all that file data in a central object storage volume. This, in turn, leads to benefits relating to scale, cost savings, data protection, and collaboration. A few years ago, though, we realized our customers deserved a chance to do more with that unstructured data. Once their file data was in the cloud, not anchored to all those islands of storage, what else could they do with those files? What could they learn from them?
We’re not in the data analytics business, but the Nasuni Analytics Connector makes it easier for customers to extract value from file data using third-party cloud services — including those offered by AWS. Typically, customer data stored with Nasuni is not accessible to these tools. We developed the Analytics Connector to deliver that capability in a secure way. What this means today is that Nasuni and AWS customers can leverage tools like Macie, Rekognition, and Kendra to uncover hidden insights in their files.
This intelligent search service, powered by machine learning, basically reinvents enterprise search, allowing your employees and customers to easily find the content they’re looking for, regardless of where it resides. It’s a fully managed service, and with the Nasuni Analytics Connector, you can finally use it to perform natural language searches over your file data.
A project-based advertising firm preparing a new pitch, for example, might want to search for specific keywords to see if they’ve done similar work in the past. If the project is in Brazil, they could use Amazon Kendra and Nasuni to find all the campaigns or photo and video shoots they’ve done in that country over the prior ten years. A company might also use it as a sort of automated FAQ to search through product documentation.
Managing growing volumes of sensitive data at scale can be difficult, yet it’s arguably more important than ever as data security and privacy regulations across the world grow increasingly strict. Amazon Macie uses machine learning and pattern matching to discover and protect sensitive data, such as personally identifiable information (PII). This helps companies comply with HIPAA and GDPR, among other things, and the Nasuni Analytics Connector makes it even easier for large enterprises to use Macie.
By consolidating file data in the cloud, then making it available to Amazon Macie through the Connector, Nasuni is helping organizations ensure the security and compliance of their file data. Here is a how-to video on how to set up the Connector with Macie.
The image and video search capabilities of Amazon Rekognition allow companies to identify objects, people, text, scenes, and activities in images and videos. (Rekognition flags inappropriate content, too.) Together, Nasuni and Rekognition mean firms can search through old CAD or BIM models, for example.
When one of our customers, the architectural firm Perkins+Will, starts a new project, its designers can search through graphics and models to see how similar projects were approached. With Nasuni, Perkins+Will architects can use tools like Rekognition on more than 500,000 drawings and photos of previous projects. They now have unlimited institutional knowledge and experience at their fingertips.
Expanding Integration with AWS
These are just a few examples, but I hope it’s clear why we’re excited about our expanding integration with AWS. After all, giving our customers access to tools like Rekognition, Macie, and Kendra is the reason we built the Nasuni Analytics Connector in the first place. And it’s all part of our larger mission to ensure that file data is not an expensive hassle for large enterprises, but fuel for growth and innovation.
Nasuni is participating AWS re:Invent 2020 through Dec. 18, 2020. If you are a registered attendee, please visit our virtual booth, and get your file data analytics with Nasuni and AWS questions answered.