Dsco has reached an agreement to acquire LEO Enterprises, which was founded in 2014 to enable data engineering teams to innovate faster by providing cloud-based visibility and control for data streams.
The acquisition will help accelerate Dsco's momentum in modernizing supply chain data. LEO has developed a cloud-based alternative to Apache's Kafka, making it easy for enterprises to set up real time data processing systems involved in cross-asset inventory management, order and post-order processing, data mining, machine learning and predictive analytics.
LEO will bring a large team of data engineers and data consultants to support Dsco in moving the retail industry towards real-time inventory networking and modern cloud-based distributed order processing.
"In one swoop Dsco has acquired both a state of the art data integration platform and added a pool of extremely talented software engineers to our team. This adds a lot of momentum as we continue to grow," Dsco founder and CEO Jeremy Hanks says. "LEO is a fantastic company with expertise in data aggregation, intelligence and reporting. With Dsco's accelerated growth this year, our consultative relationship turned strategic and LEO became a vital part of ushering in Dsco's vision for the next generation of supply chain data technologies. These technologies will enable our enterprise retail partners and their thousands of brand partners to drive billions of dollars of consumer sales."
LEO's serverless data piping and storage is on the leading edge of big data technologies. Currently businesses have to invest large amounts of time and overhead for setting up servers in house that are able to run Apache Kafka data protocols. The LEO platform allows organizations to do this in the cloud using state of the art AWS Lambda services, making setup almost instantaneous and allowing for real time data mining.
"The LEO team and I are extremely excited to be joining Dsco," says LEO CEO Blaine Nielsen. "We built LEO as an integration platform and there's no integration process bigger than what Dsco is attempting to do. We've created over 22 billion row tables for Dsco and process billions of data events each month. I look forward to being a part of this exciting new chapter."