Mission Expands AWS Cloud Services with Data, Analytics, & Machine Learning Practice

Mission, a managed cloud services provider and Amazon Web Services (AWS) Premier Consulting Partner, announced the launch of its dedicated Data, Analytics & Machine Learning practice. The new practice provides all of the data engineering, analytics, machine learning, and data science expertise and tools required for enterprises, SMBs, and startups to tap into the vast potential of their data on AWS and accelerate data-backed transformation within their organizations. No matter where customers are in their journey toward becoming a fully data-driven business, Mission provides the roadmap, strategy, technology integration, and hands-on execution to ensure fast and ongoing success.

The Mission Data, Analytics & Machine Learning practice is built for businesses who need to modernize their legacy data architecture and pipelines via the power of AWS and the cloud, as well as those who need to implement custom AI and ML algorithms to more acutely guide business initiatives and stay competitive. Mission brings the proven expertise, experience, and technologies required for success across the three focus areas within the practice:

• Data engineering and analytics: Mission experts can handle all aspects of migrating or setting up a data lake, lakehouse, data warehouse or data mart – including the development of data ingestion jobs, designing and building the foundation of a data lake, creating data pipelines, establishing an ETL process, and establishing business intelligence and visualization tools.
• AI and ML operations: Mission’s AI/ML services develop CI/CD pipelines to ensure data models are continually optimized, automate training jobs and QA processes, and deliver ongoing efficiency, accuracy, and accessibility around AI- and ML-fueled data models.
• Custom AI and ML algorithms: Mission’s data science and engineering experts help customers architect solutions that can thoroughly leverage AWS’ robust AI technologies, as well as build customized algorithms – utilizing predictive analytics, natural language processing, recommendation engines and more – that map directly to customer data transformation goals.

“Organizations have a huge opportunity to let their data affect change,” said Jaret Chiles, VP, Consulting Services, Mission. “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.”

The new practice is led by Dr. Ryan Ries, who recently joined Mission with 15 years of experience leading data science and engineering initiatives for customers, and with particular acumen enabling customers’ data journey into AWS and implementing ML algorithms. “The power of operationalized data is game-changing,” said Ries. “The business value is there for the taking – if you can get to it. We are here to ensure that our customers are in a position where their data goes to work for them, and where they can quickly realize the ROI gains that come from expertly-wielded data, analytics, AI and ML services on top of AWS. Whether you are looking to build your own customized data lake and connected applications built from the ground up with Mission, tap into a pre-built platform, or require data-lake-as-a-service management, this new practice will be the easiest and most cost-efficient path forward for many companies.”

The AWS Data, Analytics, & Machine Learning practice is designed to empower Mission customers to:

• Gain more insight from their data on AWS though custom-built algorithms that unearth more data-driven insights to confidently drive business initiatives forward.
• Run data models more efficiently with Mission-designed CI/CD pipelines for models that are updated with continuous training and automation.
• Identify patterns to unlock business insights through dashboards with BI tools such as Tableau, QuickSight and Power BI.
• Drive data-driven decision making by leveraging Mission to detect anomalies in new data, recommend unique activities for customer engagement, and make cross-organizational changes backed by data.
• Level up data governance with comprehensive and continual monitoring across all data sources to ensure best practices for regulatory compliance.
• Leverage powerful AWS databases via Mission’s expertise with cloud-native services such as Amazon Redshift.
• Confidently navigate the build-versus-buy decision by consulting with Mission on which data solutions and strategies are most advantageous for their organization.

To learn more and set up a consultation to discuss your data, analytics, and machine learning needs in AWS, visit: https://www.missioncloud.com/data-analytics-machine-learning