Mission Launches Dedicated Data, Analytics & Machine Learning Practice

Mission Launches Dedicated Data, Analytics & Machine Learning Practice

Mission is launching a dedicated Data, Analytics, & Machine Learning practice for Amazon Web Services, according to a press release on the company’s website. The new practice provides data engineering, analytics, machine learning, and data science expertise and tools to customers. This branch is led by Dr. Ryan Ries, who has 15 years of experience leading data science and engineering initiatives.

Our MSP Buyer’s Guide contains profiles on the top managed cloud service providers for AWS, Azure, and Google Cloud, as well as questions you should ask vendors and yourself before buying. We also offer an MSP Vendor Map that outlines those vendors in a Venn diagram to make it easy for you to select potential providers.

Mission is an AWS managed service provider formed in 2018 when IT solutions and consultancy providers Reliam, Stratalux, and G2 Tech Group merged together. The company provides managed services for AWS deployments, AWS migration planning and implementation, AWS disaster recovery, and AWS consultancy services. Mission also offers cloud spend and performance optimization strategy planning, as well as delivering managed DevOps, managed cloud security, and managed application performance monitoring.

The Data, Analytics, & Machine Learning lets users gain more insight from their data on AWS through custom-built algorithms that unearth data-driven insights. Customers can run data models more efficiently with Mission-designed CI/CD pipelines and identify patterns to unlock business insights. Users will also be able to leverage powerful AWS databases via Mission’s expertise with cloud-native services such as Amazon Redshift.

In the company’s press release, Mission’s VP of Consulting Services Jaret Chiles stated: “Organizations have a huge opportunity to let their data affect change. Regardless of company size, regardless of industry – connecting disparate data sources and deriving insight from that data continues to be a monumental challenge for businesses that don’t have the requisite (and expensive) expertise in-house. We are launching our new practice to move data and analytics modernization from goal to reality – quickly and with processes and technologies built for our customers’ long-term success.”

Learn more about Mission Data, Analytics, & Machine Learning here.


Daniel Hein