Bigstep, the big data cloud provider, announced the launch of Bigstep DataLab, a solution designed to enable data science and analytics at scale. Bigstep DataLab is an enterprise-ready data research service that gives domain experts, data scientists and BI specialists instant access to powerful software like Apache Spark and Jupyter for easier, more flexible and collaborative ad-hoc data exploration and research.
Our goal is to make it easy to explore data at large scale with an integrated set of technologies, as well as experiment with new technologies as they emerge,” said Bigstep Founder and CEO Lucas Roh. “There is an overwhelming set of choices when it comes to doing analytics and data science. Bigstep simplifies those choices and yet we provide the flexibility required to replace any component, such as substituting one set of data-ingestion tool with another.”
The key components of Bigstep DataLab include Bigstep Data Lake, an infinite repository system where structured, semi-structured, and unstructured data can be stored side by side and Bigstep Real-Time Spark Service, a managed, fully scalable big data computation service capable of machine learning, graph processing, and statistics.
Bigstep DataLab can easily handle large quantities of real-time and historical data, perform complex machine-learning tasks and be quickly stopped or repurposed, with on-demand scalability and pricing. It enables users to experiment with powerful data technologies, leveraging Bigstep’s award-winning bare-metal infrastructure for greater performance and security than any other cloud offering.
Combining a self-service front-end for collaborative work with data visualization and manipulation capabilities for non-technical analysts, Bigstep DataLab provides a highly secure environment with end-to-end data encryption, granular permission control, and deep integration with existing tools and services via an SQL-compatible interface.
Sign up for the free insideBIGDATA newsletter.