Data storage processes are rapidly shifting with the adoption of cloud-native data services, and enterprises are being forced to transition if they hope to accommodate the mass of data generated by an increasingly tech-connected consumer market. The challenges of data migration, hybrid infrastructure management and future-proofing are being mitigated by new computing systems created to streamline the expanding world of big data.

“What we’ve learned through our customers is they need to have a solution that is integrated with all the technologies that they’ve adopted in the enterprise,” said Matthew Baird (pictured), co-founder and chief technical officer of AtScale Inc. AtScale’s vision for data’s future, Data Lake 2.0, is focused on improving analytics and governance at scale in enterprise data processes.

Baird spoke with Lisa Martin (@LuccaZara) and  George Gilbert (@ggilbert41), hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed the challenges and opportunities posed by big data and AtScale’s vision for a more efficient future. (* Disclosure below.)

Integrating enterprise analytics and self-service

The popularity of cloud and new regulations around data posed by the European Union’s General Data Protection Regulation have made airtight data management more crucial than ever. With many of its customers working in healthcare, insurance and finance, AtScale works to ensure enterprise data is both accessible and secure.

“There’s a lot of movement into the cloud. The new data lake is kind of focused more on these large data stores … S3, Google’s object storage, and Azure ADLS,” Baird said.

AtScale integrates multiple data access tools and simplifies processes so customers can work with the appropriate tools to access the data by use case. The company focuses on abstraction in the data storage process to facilitate informed decisions for customers in every industry, according to Baird.

“If you can set up at the abstraction layer … on your on-prem data in hours you can move it into the cloud. … Once it’s in the cloud, you take the same AtScale instance, you re-point it at that new data source, and it works,” Baird said. This approach results in an agile process that allows for experimentation and greater data visibility across the business, he added.

With so many different data sources and storage options available, AtScale provides what Baird calls the “best data engineering team in the world in a box” by letting the customer dictate migrations, then moving and analyzing data automatically at their direction. “They drop the schema in the same way that it exists on their current technology, and then behind the scenes … we’re looking at signals … queries … all the different ways that people access the data naturally, and then we restructure those summary tables using algorithms and statistics,” he said.

By providing simplicity and greater insight through a customizable self-service platform, AtScale hopes to help customers make better data-driven decisions faster. “We’ve taken the two approaches of enterprise analytics and self-service and tried to create a scenario where you get the best of both worlds,” Baird concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event. (* Disclosure: AtScale Inc. sponsored this segment of theCUBE. Neither AtScale Inc. nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE